A systematic review of vector-borne pathogens in bats of Mexico in the Antropocene Vector-borne zoonoses in bats of Mexico

A systematic review of vector-borne pathogens in bats of Mexico in the Antropocene Vector-borne zoonoses in bats of Mexico | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Systematic Review A systematic review of vector-borne pathogens in bats of Mexico in the Antropocene Vector-borne zoonoses in bats of Mexico Margarita García-Luis, Ángel Rodríguez-Moreno, José Juan Flores-Martínez, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8744197/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 12 You are reading this latest preprint version Abstract Introduction: Trypanosoma spp. and Leishmania mexicana are protozoan parasites of major public health relevance. Bats can act as hosts or reservoirs, but available evidence for Mexico is fragmented and limited under a One Health framework. Methods We reviewed publications (2001–2025) reporting detection of trypanosomatids of the Trypanosoma spp. and L. mexicana in wild bats from Mexico. Epidemiological and spatial variables were included. We compiled 54 localities with individuals of bats testing positive of these pathogens, of which 14 provided site-level prevalence. These localities were analyzed in QGIS and related to distances to human settlements, paved roads, the Interoceanic train corridor (CIIT), the Maya train (Tren Maya), and decreed protected areas. Results Fourteen studies documented infection in 24 bat species, mostly phyllostomids from southeastern Mexico. Site-level prevalence ranged from 0.6 to 69.5%, with half of the records below 20%. Spatial analysis showed that most detections occurred within 0–2 km of human settlements and roads, whereas distances to the CIIT and the Maya train spanned the full gradient considered, and positive points tended to cluster within 10–40 km of a Protected area. Discussion Circulation of Trypanosoma spp. and L. mexicana in bats is concentrated in landscapes modified by infrastructure and land-use change, suggesting a strong link between human disturbance, host dynamics and zoonotic risk. These patterns highlight the need to integrate bat monitoring, land-use planning and disease surveillance within explicit One Health approach. Anthropocene Chiroptera Pathogenic protozoa Leishmaniasis Zoonoses Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Bats constitute one of the most diverse and ecologically relevant mammalian groups worldwide. Their roles in pollination, seed dispersal, and insect control have been widely documented [ 1 ]. In recent decades, they have also gained prominence in public health due to their associations with multiple zoonotic pathogens. Globally, bats are considered epidemiologically relevant as reservoirs and potential amplifiers of major vector-borne zoonotic pathogens [ 2 ]. Understanding this relationship requires examining not only bat biology, but also the global environmental context shaped by anthropogenic transformations in ecosystems, which has an impact on both wildlife population dynamics and pathogen transmission cycles, facilitating potential zoonotic spillover [ 3 ]. Bats harbor a wide variety of viruses, including coronaviruses, filoviruses, and henipaviruses, some of which have zoonotic potential [ 3 , 4 ]. This viral diversity has been attributed to taxon-specific characteristics, ranging from evolutionary and life-history traits—such as longevity, flight capacity, the formation of colonies of hundreds to millions of individuals, migration, extensive daily movement patterns, hibernation, and comparatively long lifespans relative to other mammals of similar size [ 4 ] to immunological features that enable tolerance of persistent infections without developing severe disease [ 5 ]. For example, some studies show that bats harbor viruses with the highest known virulence, even if these are not necessarily the agents responsible for the greatest burden of disease in human populations [ 6 ]. Likewise, bat-associated ectoparasites represent an understudied, yet potentially critical, component in the transmission of pathogens to other mammals, including humans [ 7 ]. This underscore bats and their associated parasites as key elements for zoonotic risk surveillance, given their roles as reservoirs and amplifiers of vector-borne pathogens across different geographic scales. From an ecological perspective, bats function as hosts by sustaining intraspecific transmission cycles that may remain stable if their habitats and social dynamics are not disrupted. However, the Antropocene is characterized by human impacts on ecosystems have intensified deforestation, urbanization, and agricultural expansion that have deteriorated natural habitats with detrimental consequences on wildlife species and populations, including bats [ 8 ]. These environmental changes modify bat movement patterns, stress levels, and population aggregation—factors that can increase viral shedding and the risk of interspecific transmission [ 9 ]. For example, habitat loss in Australia has been linked to the displacement of fruit bats into urban areas, increasing exposure of horses and, subsequently, humans to Hendra virus [ 10 ]. Similarly, agricultural expansion in Southeast Asia has created conditions conducive to Nipah virus transmission from bats to pigs and humans [ 11 ]. Nonetheless, it is important to highlight that these processes indicate that bats do not represent an intrinsic threat per se . Rather, it is the anthropogenic transformation of socio-ecological systems that disrupts the natural cycles of bats and their pathogens [ 12 , 13 ]. Thus, within the Anthropocene framework, emerging zoonotic diseases should be considered a consequence of natural habitat transformations. This implies that mitigation strategies should focus on ecosystem conservation, sustainable landscape management, and reducing high-risk interfaces, rather than persecuting or eliminating bat populations [ 8 , 13 , 14 ]. Bats play a central role in maintaining zoonotic pathogen cycles, but this role becomes a risk only when environmentally human-induced impacts shape ecological and transmission dynamics. In this context, Leishmania mexicana and Trypanosoma cruzi are two of the most important protozoa pathogens producing zoonotic diseases of public health importance in Mexico and Latin America, as the etiological agents of cutaneous leishmaniasis and Chagas disease, respectively. Several epidemiological analyses have shown that the true burden of T. cruzi in Mexico is far higher than official reports, with millions of people potentially infected and limited access to timely diagnosis and treatment [ 15 – 17 ]. In the case of L. mexicana , active endemic areas persist in southeastern Mexico, where a growing number of human cases of cutaneous and mucocutaneous leishmaniasis have been reported [ 18 ]. Some recent studies have documented infection of bats and wild rodents by L. mexicana , expanding the spectrum of implicated hosts and suggesting the existence of more complex sylvatic and peri-urban cycles than previously assumed. This evidence reinforces the need to integrate the ecological dimension of wildlife reservoirs into surveillance, prevention, and control strategies for both neglected zoonotic diseases [ 19 , 20 ]. The magnitude of this challenge is when considering the high species richness of bats in Mexico and the diversity of ecological functions they perform [ 21 ]. Mexico harbors more than 146 bat species, representing around 10% worldwide and the second most diverse mammalian group nationwide [ 22 – 24 ]. Moreover, the highest species richness of bats occurs in the Neotropical region located in southern Mexico, particularly in the States of Chiapas, Oaxaca, Veracruz, and the Yucatán Peninsula [ 23 ]. The combination of a high species richness, a broad diversity of feeding habits, and habitat use (from tropical forests and cloud forests to agricultural landscapes and urban environments) implies multiple points of contact between species of vectors and wild and domestic species of potential hosts. This, in turn, facilitates a favorable scenario for the circulation and maintenance of pathogens such as Leishmania mexicana and Trypanosoma cruzi . The complex relationship between bats and zoonotic pathogens in Mexico unfolds across a highly heterogeneous environmental mosaic, where deforestation, agricultural expansion, and urbanization has deeply reshaped landscapes and transmission cycles. For example, in the Yucatán Peninsula, the conversion of tropical forests into agricultural areas and human settlements has been documented as being associated with higher prevalence of multiple zoonotic agents and vector-borne diseases [ 25 , 27 ]. Thus, intensive production systems increase opportunities for contact among wildlife, domestic animals, and humans [ 25 ]. At the national scale, spatiotemporal analyses have shown that even small losses of forest cover translate into a significant increase in dengue risk, demonstrating that deforestation not only erodes biodiversity but also enhances vector capacity to invade human-modified environments [ 26 ]. These patterns suggest that land-use change and habitat fragmentation may exert similar effects on phlebotomine sand flies and triatomines, facilitating local persistence of Leishmania mexicana and Trypanosoma cruzi in landscapes where bats, domestic reservoirs, and vulnerable human populations coexist [ 27 , 28 ]. Furthermore, they highlight that emerging zoonoses are a consequence of unsustainable landscape transformation and must be addressed within conservation planning, land-use management and sustainable development strategies [ 13 , 29 ]. Against this backdrop, the objective of this study was to systematically analyze studies compiled from the scientific literature documenting infections by Leishmania mexicana and Trypanosoma spp. in bats of Mexico. Specifically, we evaluated their spatial, taxonomic, and methodological distribution nationwide, and examined their relationships with human activities and their public health implications under a One Health approach. Materials and methods A literature search was conducted in academic databases (BioOne, Scopus, Web of Knowledge, Redalyc, Elsevier) to identify publications reporting records of leishmaniasis or Chagas disease in Mexico. In addition, repositories were consulted (Tesis UNAM, UADY, ECOSUR, and other national universities), and a manual search was performed using the reference lists of key articles. The search was conducted following the PRISMA 2020 framework [ 30 ] (Fig. 1 ). We restricted the time window to January 2001–December 2024 because the earliest bat-focused reports of T. cruzi and L. mexicana in Mexico date from this period and studies on wildlife hosts and landscape drivers have intensified since the early 2000s [e. g. 31]. In each database, the following terms—alone or in combination, in Spanish and English—were used with the Boolean operators AND, OR, and NOT: murciélagos, México, huéspedes, patógenos, leishmaniasis, tripanosomiasis , Leishmania , Trypanosoma , Trypanosoma cruzi , Leishmania mexicana , Chagas. The inclusion criteria, comprised studies with primary data or modeling-based evidence that: (a) included bats captured within Mexican territory, and (b) documented natural infection or a potential reservoir role for L. mexicana and/or Trypanosoma spp. Document types included peer-reviewed articles, book chapters, and graduate theses. We included graduate theses with primary data to reduce publication and geographic bias, this decision is consistent with methodological recommendations that emphasize the value of grey literature (including theses and technical reports) for improving coverage and minimizing bias in environmental and conservation evidence syntheses [ 30 , 32 ]. The exclusion criteria, comprised studies focused on vectors or domestic reservoirs without data on bats; review articles without primary data or Mexico-specific models; studies in which bats were mentioned only speculatively. Data compilation The variables included were year, document type, state, bat species, pathogen(s), diagnostic method, sample size, number of positives, and prevalence. Data are summarized in Table 1 (study synthesis) and Table 2 (list of bat species with detections of Trypanosoma spp. and Leishmania mexicana , including positive and negative records as reported in the studies). Of the studies reviewed, 12 provided sufficient spatial information to georeference at least one locality with individuals of bats testing positive, resulting in a total of 54 localities with presence of at least one pathogen. The remaining localities were excluded from subsequent analyses. From the full set of localities, 14 were separated in which authors explicitly reported the number of positive individuals and sample size, allowing site-level prevalence to be calculated (25.9%, 14/54). The complete set of localities was treated as pathogen presence for subsequent analyses. Spatial analysis The spatial framework was designed to be reproducible and applicable to sustainability-oriented risk assessments. To explore whether site-level prevalence or pathogen presence reflects gradients of anthropogenic disturbance, five spatial variables were selected. This selection was based on their relevance to reservoir ecology and the dynamics of vector-borne pathogens. Distance to the nearest human locality and to the road network was used as a proxy for disturbance and synanthropic gradients, given that studies have shown that T. cruzi circulation in wild and domestic mammals is associated with rural–peri-urban mosaics, settlement density, and road connectivity, which facilitate contact among reservoirs, vectors, and humans [ 33 , 34 ]. Distance to decreed protected areas (PAs) was included to contrast the location of records relative to areas under some protection regime, following previous approaches that assess vector-borne zoonosis risk as a function of natural cover and conservation designations [ 35 , 36 ]. The CIIT and Maya train were incorporated as examples of infrastructure megaprojects in southeastern Mexico that are expected to drive intense land-use change, fragmentation, and increased flows of people and goods, with potential implications for disease transmission [ 35 , 37 ]. To evaluate the spatial relationship between pathogen prevalences/detections and landscape variables, a spatial analysis was conducted in QGIS 3.43.0. First, georeferenced presence sites of Trypanosoma cruzi (including TcI, Discrete Typing Unit I), Trypanosoma spp., T. dionisii , and Leishmania mexicana were compiled from the identified studies. All points and environmental layers (human localities, road network the Corredor Interoceánico del Istmo de Tehuantepec (CIIT) and the Maya train (Tren Maya) alignments, and polygons of PAs were re-projected to a projected meter-based CRS (EPSG:4326-WGS 84 → EPSG:6372-Mexico ITRF2008/LCC) to minimize distortion and ensure that Euclidean distances were comparable. Minimum distances from each presence point to each variable were obtained using the QGIS proximity tool “distance to nearest hub” (nearest neighbor), calculating for each site identified in the research in Mexico: (1) distance to the nearest human locality, (2) distance to the nearest segment of the road network, (3) orthogonal distance to the CIIT axis, (4) orthogonal distance to the Maya train axis, and (5) distance to the nearest PAs boundary. All distances were exported in meters and subsequently converted to kilometers for ecological interpretation. As quality control, points were visually inspected and frequency histograms were generated for each distance variable; this enabled identification of outliers associated with coordinate errors (e.g., inverted longitude signs), which were corrected before recalculating distances. Points were grouped into distance classes defined as a priori but adjusted based on the distributions observed in histograms and on ecological considerations regarding bat movements and the spatial scale of infrastructure influence. For proximity to human localities and the road network, three classes were used: 0–2 km, 2–5 km, and > 5 km. The 2 km threshold reflects the immediate environment of sampling sites and falls within the typical range of local foraging for many phyllostomid bats, whose nocturnal movements from roosts to feeding areas often range from hundreds of meters to a few kilometers (e.g., Artibeus jamaicensis with mean movements 5 km reflects sites relatively farther from the immediate anthropogenic matrix, yet still reachable within the known movement capacity of several Neotropical bat species, which may travel several to tens of kilometers in a single night. In addition, studies have suggested that road effects on vertebrate abundance are strongest within the first kilometer and can extend several kilometers outward, supporting the distinction between very proximate zones (0–2 km) and peri-influence (2–5 km) [ 39 , 40 ]. For PAs, three categories were defined: 0–10 km, 10–40 km, and > 40 km from the nearest boundary. The 10 km threshold is based on studies that use 5–10 km or 10–20 km buffers to quantify the “zone of influence” or isolation of protected areas, given that the main gradients of land-cover change and human pressure around conservation polygons are concentrated within these distances. The intermediate interval (10–40 km) represents a regional landscape still under indirect influence of PAs (e.g., as a source of dispersing individuals), whereas > 40 km is interpreted as a context largely functionally disconnected from these habitat cores, at least at the scale of daily movements. For the CIIT and Maya train, the scale of these projects is continental (e.g., distance values range from hundreds to more than one thousand kilometers). Given that these scales far exceed daily movement distances of bats, broad classes were defined to distinguish regional gradients of exposure to megaprojects rather than strict ecological thresholds: 0–200 km, 200–600 km, and > 600 km for CIIT, and 0–300 km, 300–900 km, and > 900 km for the Maya train. Cutting-points were selected by combining inflection points observed in histograms (changes in frequency density) with the goal of differentiating a direct or nearby regional sphere of influence, an intermediate sphere, and a remote sphere relative to each infrastructure corridor. Lastly, distance categories for each variable were incorporated as new fields in the attribute table using the QGIS field calculator and were used in descriptive and comparative analyses of the distribution of presences for each pathogen. This approach explicitly integrated bat movement scales and the spatial scale of human infrastructure into the interpretation of spatial infection patterns, while maintaining a reproducible methodology based on quantitative distance metrics; these data were used to construct Table 3 and Supplementary material 1. Table 3 Distance from human locality, road nerwork, CIIT (Corredor Interoceánico del Istmo de Tehuantepec), Maya train, and Protected Areas (PAs) to localities with site-level prevalence of Leishmania mexicana and Trypanosoma spp. No. Pathogen Site-level prevalence 0–5 km > 5 km E1 Trypanosoma cruzi 7/34(20.6%) Human locality 0.7 Road network 0.1 CIIT 357.8 Maya train 770.2 PAs 14 E3 Trypanosoma cruzi 15/172(8.7%) Human locality 0.9 Road network 0.5 CIIT 550.5 Maya train 41.2 PAs 48.8 E4 Trypanosoma cruzi 11/184(6%) Human locality 0.5 Road network 0.1 CIIT 458.9 Maya train 36.3 PAs 2.9 E6 Leishmania mexicana 11/124(8.9%) Human locality 11.9 Road network 18.6 CIIT 296.1 Maya train 128.2 PAs 0 E6 Trypanosoma sp. 2/124(1.6%) Human locality 11.9 Road network 18.6 CIIT 296.1 Maya train 128.2 PAs 0 E8 Leishmania mexicana 2/12(16.7%) Human locality 2 Road network 1.1 CIIT 0 Maya train 352.9 PAs 0 E8 Leishmania mexicana 2/18(11%) Human locality 0.6 Road network 0.1 CIIT 0 Maya train 346.3 PAs 0 E9 Trypanosoma cruzi 10/26(38.5%) Human locality 2 Road network 0.3 CIIT 431 Maya train 0.1 PAS 1.1 E9 Trypanosoma cruzi 16/23(69.5%) Human locality 1.9 Road network 0.9 CIIT 699.7 Maya train 55.2 PAs 18.2 E10 Trypanosoma cruzi 1/19(5.2%) Human locality 0.6 Road network 0.1 CIIT 0 Maya train 346.3 PAs 0 E11 Trypanosoma cruzi TcI 18/110(16.4%) Human locality 1.6 Road network 0.3 CIIT 84.5 Maya train 154.2 PAs 3.2 E12 Trypanosoma cruzi TcI 7/72(9.7%) Human locality 1.6 Road network 1.6 CIIT 617.3 Maya train 0 PAs 86.2 E12 Trypanosoma dionisii 1/72(1.4%) Human locality 1.6 Road network 1.6 CIIT 617.3 Maya train 0 PAs 86.2 E12 Trypanosoma sp. 1/72(1.4%) Human locality 1.6 Road network 1.6 CIIT 617.3 Maya train 0 PAs 86.2 Results A total of 14 studies conducted in Mexico between 2001 and 2024 were recorded. Of these, three were theses, one was a book chapter, two were short communications, and eight were journal articles. The year with the highest number of publications was 2015 (n = 3), followed by 2021 and 2024 (n = 2 each). Studies have been reported in 40.6% (n = 13) of the country. The States with the highest number of published studies were Chiapas and Yucatán (n = 4 each), followed by Morelos and Veracruz (n = 3), Tabasco and Campeche (n = 2), while seven States had only one study; one study addressed leishmaniasis at the national level [ 41 ] Figs. 2 and 3 , Table 1 ). Table 1 Publications by year on Trypanosoma sp. and Leishmania sp. in bats from Mexico. * The authors do not report positive individuals; therefore, overall prevalence cannot be calculated. No. Type Authors (year) Title Journal/Book Diagnostic method Sample size Municipality/State 1 Communication Villegas-García & Santillán-Alarcón, 2001 Sylvatic focus of American trypanosomiasis in the state of Morelos, Mexico Revista de Biología Tropical Xenodiagnostic / serology 34/*(*) Ticumán and Tlaltizapán, Morelos 2 Communication Villegas-García & Santillán-Alarcón, 2004 American trypanosomiasis in central Mexico: Trypanosoma cruzi infection in triatomine bugs and mammals from the municipality of Jiutepec in the state of Morelos Annals of Tropical Medicine & Parasitology Xenodiagnostic / serology 77 /*(*) Jiutepec, Morelos 3 Book chapter Córdova, Escobedo, Hernández y Ruiz, 2013 Los murciélagos en el ciclo de transmisión de Trypanosoma cruzi en el peridomicilio rural Estudios multidisciplinarios de las enfermedades zoonóticas y ETVs en Yucatán PCR/ literature review 172/ 15 (8.7%) Molas, Mérida, Yucatán 4 Article López-Cancino, Tun-Ku, de la Cruz, Ibarra-Cerdeña, Izeta-Alberdi, Pech-May, Mazariegos-Hidalgo, Valdez-Tah y & Ramsey, 2015 Landscape ecology of Trypanosoma cruzi in the southern Yucatan Peninsula Acta Tropica PCR/ spatial analysis 184/ 11 (6%) Campeche, México 5 Article Berzunza-Cruz, Rodríguez-Moreno, Gutiérrez-Granados, González-Salazar, Stephens, Hidalgo-Mihart, Marina, Rebollar-Téllez, Ballón-Martínez, Domingo, Ibarra-Cerdeña, Sánchez-Cordero & Becker, 2015 Leishmania (L.) mexicana infected bats in Mexico: novel potential reservoirs PLoS Neglected Tropical Diseases PCR/sequencing 420/ 41 (9.8%) Chiapas, Tabasco, Jalisco 6 Thesis Víquez, 2015 Detección de L. mexicana y Trypanosoma spp. en murciélagos de Chiapas Master’s (thesis), UNAM PCR T. cruzi 124/ 2 (1.6%) L. mexicana 124/ 11 (8.9%) Selva Lacandona, Chiapas 7 Article Stephens, Gonzalez-Salazar, Sánchez-Cordero, Becker, Rebollar-Tellez, Rodriguez-Moreno, Berzunza-Cruz, Domingo, Gutiérrez-Granados, Hidalgo-Mihart, Ibarra-Cerdeña, Ibarra, Iñiguez & Ramírez, 2016 Can you judge a disease host by the company it keeps? Predicting disease hosts and their relative importance: a case study for Leishmaniasis PLoS neglected tropical diseases PCR/ spatial modeling 413/ 38 (9.2%) México 8 Thesis Sánchez, 2019 Detección de Leishmania mexicana en murciélagos de la región de los Tuxtlas, Veracruz, México Undergraduate (thesis), UNAM PCR 43/ 3 (6.9%) San Andrés Tuxtla y Santecomapam, Veracruz 9 Article Torres-Castro, Cuevas-Koh, Hernández-Betancourt, Noh-Pech, Estrella, Herrera-Flores, Panty-May, Waleckx, Sosa-Escalante & Peláez-Sánchez, 2021 Natural infection with Trypanosoma cruzi in bats captured in Campeche and Yucatán, México Biomedica PCR (kDNA) 86/ 26 (30.2%) Tzucacab y Panabá, Yucatán 10 Thesis Juárez, 2021 Detección de Trypanosoma sp. en murciélagos de “Los Tuxtlas”, Veracruz, México Licenciatura, UNAM PCR 43/ 1 (2.3%) Los Tuxtlas, Veracruz 11 Article Gómez-Sánchez, Ochoa-Díaz-López, Espinoza-Medinilla, Velázquez-Ramírez, Santos-Hernández, Ruiz-Castillejos, Vidal-Lopez, Moreno-Rodriguez, Flores-Villegas, Lopez-Argueta & De Fuentes-Vicente, 2022 ໿Mini-exon gene reveals circulation of TcI Trypanosoma cruzi (Chagas, 1909)(Kinetoplastida, Trypanosomatidae) in bats and small mammals in an ecological reserve in southeastern Mexico Zookeys mini-exon gene PCR 110/ 18 (16.4%) El Zapotal, Chiapas 12 Article Moo-Millan, Tu, Montalvo-Balam, Ibarra-López, Hernández-Betancourt, May-Concha, Ibarra-Cerdeña, Barnabé, Dumonteil, Waleckx, 2024 Presence of Trypanosoma cruzi TcI and Trypanosoma dionisii in sylvatic bats from Yucatan, Mexico. Transactions of the Royal Society of Tropical Medicine and Hygiene PCR/multilocus sequencing Trypanosoma cruzi 72/ 7 (9.7%) Trypanosoma dionisii 72/ 1 (1.4%) Trypanosoma spp 72/ 1 (1.4%) Sudzal, Yucatán 13 Article Rengifo-Correa, Rodríguez-Moreno, Becker, Falcón-Lezama, Tapia-Conyer, Sánchez-Montes, Suzán, Stephens & González-Salazar, 2024 Risk of a vector-borne endemic zoonosis for wildlife: Hosts, large-scale geography, and diversity of vector-host interactions for Trypanosoma cruzi Acta Tropica PCR 524/ 75 (14.3%) Does not include only bats in the prevalence calculation Veracruz, Tabasco, Chiapas, Yucatan, Campeche, San Luis Potosí, Nuevo León, Chihuahua, Baja California Sur, Jalisco, Nayarit and Mexico state. 14 Article Ramsey, J. M., Gutiérrez-Cabrera, A. E., Salgado-Ramírez, L., Peterson, A. T., Sánchez-Cordero, V., & Ibarra-Cerdeña, C. N., 2012 Ecological Connectivity of Trypanosoma cruzi Reservoirs and Triatoma pallidipennis Hosts in an Anthropogenic Landscape with Endemic Chagas Disease PLOS ONE PCR 116/0(0) Morelos Regarding the pathogen identification technique used, 12 studies employed PCR (including all variants, e.g., conventional PCR, kDNA-based assays, etc.), followed by xenodiagnosis and serology, both used in two studies [ 42 , 43 ]. Sample sizes per study ranged from 34 individuals in Morelos [ 42 ] to 524 individuals surveyed across 12 States [ 44 ]. Overall prevalence across studies ranged from 0% in Morelos [ 45 ] to 30.2% in Yucatán [ 46 ] (Table 1 ). Further, regarding pathogen detection, Trypanosoma cruzi , T. cruzi TcI (Discrete Typing Unit I), Trypanosoma dionisii , Trypanosoma sp., and Leishmania mexicana were identified in 45 species of bats from six families, representing 31% of the species of bats nationwide (146) [ 23 ]. The family Phyllostomidae ranked highest including 29 species, followed by Vespertilionidae with seven; Noctilionidae had the fewest records, with a single species ( Noctilio leporinus ). At the species level, Artibeus jamaicensis and Sturnira parvidens were the most frequently included in the surveyed studies, mentioned in 79% (n = 12) of all publications; seven species were addressed in only one study (Table 2 ). Table 2 Bat species in which Leishmania mexicana and Trypanosoma sp. have been detected in studies conducted in Mexico. * Prevalence cannot be calculated because the authors do not specify whether all positives correspond to the same individual or to different individuals. E = study (each number corresponds to the study No. in Table 2 ), e = examined individuals, P = positives. Positive individuals reported in each study are highlighted in bold. Host Trypanosoma cruzi Trypanosoma cruzi TcI Leishmania mexicana Familia Emballonuridae Balantiopteryx plicata E1 2/0(*), E14 56/0(0) Saccopteryx bilineata E10 12/0(0), E13 1/*( * ) E5, E7 1/0(0) E8 12/0(0) Familia Noctilionidae Noctilio leporinus E9 6/0(0) Familia Mormoopidae Mormoops megalophylla E11 2/0(0) Pteronotus fulvus E3 1/0(0) - E9 2/0(0) - E10 13/0(0) E11 1/0(0) E8 13/ 1 (7.0%) Pteronotus mesoamericanus E1 6/ 5 (*)- E2 13/10(*)- E9 6/ 4 (66.7%) - E10 2/0(0) - E14 8/0(0) E11 3/0(0) E5 5/0(0), E7 4/0(0) E8 2/ 1 (50%) Pteronotus psilotis E10 1/0(0) E5 4/ 1 (25%), E7 4/ 1 (25%), E8 1/0(0) Familia Phyllostomidae Micronycteris microtis E14 1/0(0) E5, E7 1/0 (0) Desmodus rotundus E2 12/ 11 (*) - E14 2/0(0) E11 2/0(0) -E12 16/0(0) E5, E7 14/ 1 (7.1%) Diaemus youngi E5 1/0(0) Diphylla ecaudata E3 4/0 (0) Lonchorhina aurita E6 E5 1/0(0), E7 1/0(0) Mimon cozumelae E12 4/0(0) Phyllostomus discolor E5, E7 1/ 1 (100%) Anoura peruana E5 6/0(0) Choeroniscus godmani E10 3/ 1 (33.3%) E5, E7 13/ 3 (23.0%), E8 3/0(0) Choeronycteris mexicana E1 1/ 2 (*) - E14 3/0(0) Glossophaga commisarisi E13 1/- (*) E5, E7 8/ 6 (75.0%) Glossophaga mutica E1 1/ 1 (*), E3 11/0(0), E9 5/ 4 (80.0%), E12 1/0(0) - E14 2/0(0) E11 8/ 1 (12.5%) E5 26/ 7 (26.9%), E7 16/ 7 (43.8%) Leptonycteris yerbabuenae E2 25/ 18 (*) - E14 2/0(0) E11 2/0(0) E5, E7 2/ 1 (50%) Macrotus waterhousii E14 6/0(0) Carollia perspicillata E4 3/ 2 (66.7%) E11 7/ 2 (28.5%) E5, E7 8/0(0) Carollia sowelli E6 83/ 2 (1.6%) - E9 2/0(0) E5 45/ 2 (4.4%) - E6 83/ 5 (6%) - E7 44/ 2 (4.6) Artibeus jamaicensis E1 7/ 6 (*) - E2 47/23 (*) - E3 99/5 (2.9%)- E4 62/ 2 (3.2%) - E9 45/ 10 (22.2%)- E10 10/0 (0) - E12 55/ 6 (10.9%) - E14 9/ 0 (0) E11 64/ 10 (15.6%) Trypanosoma dionisii E12 55/ 1 (1.8%) Trypanosoma spp. E12 55/ 1 (1.8%) E5, E7 86/ 5 (5.81%) Artibeus lituratus E3 37/ 9 (5.23%)- E4 33/ 1 (3%) - E9 2/2 (100%) – E14 10/0(0) E11 16/ 3 (18.7%) E5 41/ 3 (7.31%)- E7 39/ 3 (7.7%) Centurio senex E11 2/0(0) E5 1/0(0) - E7 1/0(0) - Chiroderma villosum E9 7/ 4 (57.1%) E5 5/0(0) - E7 5/0(0) - Dermanura sp. E14 1/0(0) Dermanura phaoetis E4 10/ 1 (10%) - E9 3/0(0) - E12 8/0(0)- E13 1/*(**) E5 37/ 3 (8.1%) - E7 36/ 1 (2.78%) - Dermanura tolteca E10 1/0(0) E5 1/0(0), E8 1/0(0) Dermanura watsoni E12 1/0(0) E5, E7 2/0(0) Platyrrhinus helleri E10 1/0(0) E5 5/0(0), E7 3/0(0), E8 1/0(0) Sturnira hondurensis E4 18/ 1 (5.6%) E5, E7 25/ 1 (4%) Sturnira parvidens E1 17/ 16 (*) - E2 19/ 19 (*) - E3 19/ 1 (0.6%)- E4 51/ 3 (5.9%) - E6 41/0(0) - E9 1/ 1 (100%) - E12 1/ 1 (100%) - E14 1/0(0) E11 3/2 (66.6%) E5 63/ 7 (11.1%) - E6 41/ 5 (8.2%) - E7 64/ 6 (9.4%) Uroderma convexum E9 1/0 (0) E5, E7 4/0(0) Vampyrodes major E5, E7 1/0(0) Familia Molossidae Molussus nigricans E13 1/*(*) E5, E7 1/0(0) Tadaria brasiliensis E5, E7 1/0(0) Familia Vespertilionidae Antrozous pallidus E5, E7 1/0(0) Eptesicus fuscus E5, E7 1/0(0) Myotis auriculus E5, E7 2/0(0) Myotis extremus E5, E7 2/0 (0) Myotis pilosatibialis E4 7/ 1 (14.3%) E5, E7 2/0(0) Myotis velifer E5 3/0(0), E7 4/0(0) Rhogeessa aenea E3 1/0(0), E9 1/ 1 (100%) - E12 1/0(0) For species of bats with positive records for pathogen presence, detection of one or both pathogens were confirmed in 20 species (14% of species of bats nationwide). In Choeronycteris mexicana , Chiroderma villosum , Myotis pilosatibialis , and Rhogeessa aenea , only Trypanosoma cruzi has been identified. In Pteronotus fulvus , P. psilotis , Phyllostomus discolor , and Glossophaga commissarisi , only Leishmania mexicana has been identified; in eleven species, both pathogens have been detected (Table 2 ). For species of pathogens, Trypanosoma cruzi showed the highest prevalence (100%) in Artibeus lituratus [ 46 ], Sturnira parvidens [ 46 , 47 ], and Rhogeessa aenea [ 46 ], Figure 4 a). For T. cruzi TcI, Sturnira parvidens had the highest prevalence (66.6%, Figure 4 b). For Leishmania mexicana , Phyllostomus discolor [ 20 , 41 ] showed the highest prevalence (100%, Figure 5 ). However, it is important to note that these maximum values were obtained from very small sample sizes (one or two individuals per species per study) and therefore do not reflect robust population-level prevalence estimates. Spatial presence of pathogens For the 54 localities with confirmed positive records of Trypanosoma spp. and Leishmania mexicana in bats, pathogen presence was strongly concentrated in the nearest distance classes to human infrastructure. For distance to the nearest human locality, the dominant class was 0–2 km, which contained 74.1% of records (40/54), whereas only a small fraction of sites was located beyond 5 km. A stronger association was observed for the road network, with 87.0% of records (47/54) occurring within 0–2 km of a road segment. With respect to the CIIT, half of the records (50.0%, 27/54) fell in the closest interval (0–200 km), and the remainder were distributed between intermediate (200–600 km) and distant (> 600 km) intervals. For the Maya train, nearly two thirds of records (63.0%, 34/54) were located within 0–300 km of the rail alignment. In contrast, distances to PAs were more evenly distributed: the largest single group corresponded to sites ≤ 10 km from a PA (38.9%, 21/54), but a similar number of records occurred at intermediate (10–40 km) and large (> 40 km) distances, indicating that pathogen presence spans both human-dominated and more conserved landscapes. For T. cruzi (including TcI; 37 localities), the nearest distance class again dominated for localities and roads. Most records were located very close to human settlements, with 67.6% (25/37) occurring 0–2 km from the nearest locality, and 86.5% (32/37) within 0–2 km of the road network; no detections were recorded beyond 5 km from roads. Distances to the CIIT were more evenly divided between the two closest categories, with both the 0–200 km and 200–600 km classes concentrating 40.5% of detections (15/37 each), and only a minority of records located at > 600 km. For the Maya train, the dominant class was 0–300 km, which contained 54.1% of records (20/37), while fewer detections occurred at larger distances. Regarding PAs, the highest proportion of presence of T. cruzi and TcI records was also found in the nearest interval, with 45.9% (17/37) situated ≤ 10 km from a PA, and the remaining records between 10–40 km and > 40 km. Overall, these results highlight a strong association between T. cruzi occurrence in species of bats and modified landscapes shaped by localities and road infrastructure, whereas any gradient of association with the CIIT and Maya train becomes less evident at larger spatial scales. Leishmania mexicana (14 localities) exhibited an even more pronounced clustering in the nearest intervals to localities and roads: 92.9% of its presence (13/14) were located 0–2 km from both the nearest human locality and the road network. For the CIIT, the dominant distance interval was 0–200 km, which contained 85.7% of records (12/14), with only isolated detections at longer distances. A similar pattern was observed for the Maya train, where 78.6% of records (11/14) fell within 0–300 km of the interval. In contrast, distances to PAs tended to be longer, with the intermediate interval (10–40 km) concentrating the highest proportion of presence of L. mexicana records (42.9%, 6/14), followed by sites located > 40 km from a PA. The few detections of Trypanosoma sp. and T. dionisii (three in total) also occurred predominantly in the nearest classes to localities and roads, with two thirds of records (2/3) in the 0–2 km interval for both variables, while most of these points were assigned to the most distant categories relative to the CIIT and PAs. These results indicate that the pathogens T. cruzi , L. mexicana and other trypanosomatids are predominantly detected in bat assemblages from landscapes where human infrastructure is present at short distances, whereas their spatial presence relative to the CIIT and Maya train decreased as distance increased from the main project corridors. Spatial prevalence of pathogens A total of 14 localities with prevalence estimates of Trypanosoma cruzi , T. cruzi TcI, T. dionisii, Trypanosoma spp., and Leishmania mexicana in Mexican bats were recorded, with values ranging from 1.4% to 69.5% (median 9.3%). Most of these localities were located very close to human settlements: 11 of 14 records (78.6%) were situated at ≤ 5 km from the nearest locality. A similar pattern was observed with respect to the road network, where 11 of 14 localities (78.6%) occurred at ≤ 5 km from a road. In contrast, only three of 14 records (21.4%) were located at ≤ 5 km from the influence corridor of the CIIT, whereas 11 of 14 (78.6%) occurred at longer distances; these data indicate that most documented localities do not spatially overlap with this infrastructure project. For the Maya train, four of 14 records (28.6%) were located at ≤ 5 km from the rail alignment (including a recreational center in Campeche and the Keh Poot cenote in Yucatán), while the remaining records (71.4%) were located farther away. Notably, more than half of the localities (eight of 14, 57.1%) were located 5 km from a PAs, primarily within the Calakmul Biosphere Reserve, the Selva Lacandona, Los Tuxtlas, and the El Zapotal reserve. This suggests overlap between regions of high conservation value and the circulation of these pathogens. The remaining records corresponded to sites more isolated from localities and roads (such as the Selva Lacandona and Rancho San Francisco in Yucatán), where prevalence values can be similarly high. This indicates that risk scenarios are not restricted to strongly anthropogenic modified landscapes but can also emerge in continuous or semi-natural forest matrices (Table 3 ). Thus, no clear differences were observed in distance patterns by pathogen; instead, a shared pattern emerged of the presence of T. cruzi , L. mexicana , and other trypanosomatids in landscapes where human infrastructure (localities, roads) co-occurs with PAs. Given sample size limitations and the fact that several pathogens share the same localities, these results are preliminary and should be strengthened with targeted sampling of pathogen-by-pathogen comparisons. Discussion Zoonotic infectious diseases originate predominantly in wildlife, and their emergence is closely linked to human-induced ecosystem transformations, including deforestation, agricultural expansion, urbanization, and large-scale infrastructure development [ 48 – 50 ]. In the Anthropocene context, understanding how wildlife populations, their pathogens, and human-modified landscapes are spatially articulated is fundamental for anticipating risk and designing prevention strategies that integrate human, animal, and environment factors using a One Health approach. Our study showed species of bats testing positive to Trypanosoma spp. and Leishmania mexicana were strongly clustered near human localities and roads (Table 3 ), while distances to the CIIT, the Maya train alignment, and PAs spanned broader gradients, highlighting heterogeneous landscapes where infrastructure, forest remnants, and PAs co-occur. From a host perspective, the survey of literature indicated that close to 20% of species of bats nationwide have been examined with evidence of infection by T. cruzi or L. mexicana , although this likely underestimates the number of host species [ 4 ]. More than half of the recorded species belong to Phyllostomidae (15 species, 62.5%) (Figs. 2 – 5 ). It is likely that since phyllostomids are primarily frugivorous and nectarivorous bats fly at low heights, and are readily captured with mist nets [ 51 , 52 ], current evidence is shaped by sampling bias toward species that exploit forest edges, secondary growth, plantations, and peri-urban settings, while high-flying insectivorous bats remain underrepresented [ 53 , 54 ]. Thus, the apparent prominence of phyllostomids as reservoirs may partly reflect trophic ecology, tolerance of disturbed environments, and capture bias rather than intrinsically higher host competence. To address this hypothesis will require expanding sampling in a wide range of habitats including most species of bats, particularly along gradients from conserved forests to strongly human-modified landscapes. Pathogen-specific patterns further support a strong association with human-modified matrices. T. cruzi (including TcI) was consistently detected near human localities and roads (Table 3 ), yet it also occurred across the full range of distances to both the CIIT and the Maya train, suggesting persistence under diverse configurations of landscape transformation. Leishmania mexicana showed an even stronger proximity pattern to localities and roads, with most records falling within the closest distance categories to the CIIT and the Maya train. Although records for T. dionisii and Trypanosoma sp. were sparse, they likewise occurred mainly near localities and roads. Overall, the available evidence is consistent with bat–pathogen interactions occurring within mosaics of secondary vegetation, crops, water bodies, human settlements, and forest remnants (Figs. 2 , Table 3 , Supplementary material 1). The concentration of records in southeastern Mexico (especially Campeche, Yucatán, Chiapas, and Veracruz) support previous studies documenting T. cruzi and L. mexicana distributions [ 55 , 56 ] and reflects both the ecological significance of the Selva Maya and the extensive habitat transformation into agricultural fields expansion, extensive cattle ranching, and urban and tourism development [ 57 , 58 ] Under habitat loss and fragmentation, wildlife frequently shifts toward edges and peri-urban areas, where resources may increase but community diversity declines [ 29 , 59 ]. The spatial clustering observed appears to align with a human-induced risk, in which sylvatic cycles overlap with human activities, increasing the likelihood of contact among bats, vectors, domestic animals, and humans. These patterns also connect to the “dilution effect” hypothesis, whereby high-diversity habitats can reduce transmission of some pathogens by distributing vector bites and host–pathogen interactions across multiple, often low-competence hosts [ 60 – 62 ]. Conversely, simplified landscapes often favor disturbance-tolerant, opportunistic species that can reach high densities and maintain or amplify pathogen circulation. Several generalist phyllostomid species ( Artibeus jamaicensis , A . lituratus , Carollia perspicillata ), commonly associated with disturbed habitats and agricultural matrices [ 63 – 65 ], appear repeatedly in records for T. cruzi and L. mexicana . However, reservoir quality (infectious competence and transmission to vectors or other hosts) remains poorly characterized in these bats, precluding conclusions about whether they primarily amplify or dilute risk [ 62 , 66 ]. Although Trypanosoma spp. have been evaluated slightly more often than L. mexicana in species of bats, both are neglected tropical [ 67 ]. Integrating taxonomic evidence (infection records spanning only 20% of species of bats nationwide) with spatial evidence (54 positive localities predominantly near roads and settlements) and socio-environmental context (deforestation, megaprojects, agricultural expansion) underscores that sylvatic, peri-urban, and urban cycles of these parasites should be integrated into further analyses. A One Health agenda should integrate monitoring of wildlife, vectors, and domestic hosts with land-use and forest-cover metrics, infrastructure development, and local socioeconomic conditions [ 11 , 68 – 70 ] to realistically assess risk, anticipate human-induced landscape changes, and design interventions that protect human health, animal health, and ecosystem integrity. Human transformations in the Yucatán Peninsula and their relationship to the emergence and re-emergence of zoonoses. The Yucatán Peninsula illustrates how recent human-induced environmental changes shapes ecological landscapes facilitating for zoonotic pathogen circulation. Expansion of the agricultural frontier (particularly industrial pig and poultry production and mechanized soybean and maize cultivation) has replaced forest with agro-industrial and peri-urban mosaics and increased roads, highways, and settlements [ 71 ]. These changes can modify roost and foraging resources, favoring the use of vegetation edges, pastures, and areas near farms and rural communities by multiple bat species, including generalist phyllostomids and Desmodus rotundus [ 72 ]. Intensive tourism around cenotes and caves adds chronic disturbance through coastal urbanization, access roads, and direct modification of recreational caves, potentially altering roost use, mobility, and reproductive phenology. Because chronic stress and altered movements can affect pathogen shedding and transmission by changing contact rates within and among colonies and with other hosts, detections of T. cruzi and L. mexicana in cenotes and reserves suggest these settings may function as interaction points among wildlife, vectors, domestic animals, and people [ 12 , 73 ]. The broader regional context reinforces the need for integrative management. Livestock expansion into formerly forested areas can amplify zoonotic cycles, as illustrated by bovine paralytic rabies associated with D. rotundus in southeastern Mexico, where increased livestock availability can support persistent or growing hematophagous bat populations with notable economic and health consequences [ 74 ]. Although this study focuses on Trypanosoma spp. and L. mexicana , similar land-use and infrastructure drivers may structure risk for multiple bat-associated pathogens, with distance gradients to localities, roads, and megaprojects serving as indirect indicators of human pressure on bat assemblages and their vectors [ 71 , 75 , 76 ]. From a One Health perspective, these findings highlight the importance of linking megaproject planning (Maya train, CIIT), land-use regulation, and conservation of the Selva Maya and other southeastern ecosystems with zoonosis surveillance and coordinated management of wildlife and domestic animals. Given the consistent proximity between human localities, the road network, and pathogen-positive bat localities, interventions such as active and passive surveillance, community education, bat roost management, vector control, and strengthening of primary care should be prioritized in human–wildlife interface landscapes. One challenge is advancing development models that reduce deforestation and fragmentation, sustain ecosystem functionality, and simultaneously decrease opportunities for pathogen spillover into human and domestic ani mal populations. From a sustainability perspective, preventing zoonotic emergence requires integrating biodiversity conservation, infrastructure planning and health surveillance as interdependent components rather than isolated sectors. Implications for sustainability and One Health In this context, these patterns emphasize that bat–pathogen systems in Mexico are embedded in socio-ecological landscapes where conservation and development agendas intersect. Positive records near roads, localities and megaproject corridors suggest that decisions on transport infrastructure, agricultural expansion and tourism development can inadvertently modulate opportunities for pathogen maintenance and spillover. Conversely, the presence of infections in and around Protected Natural Areas indicates that conservation instruments must explicitly consider disease dynamics, rather than assuming that biodiversity protection automatically reduces risk. Framing these findings within a sustainability lens implies that bat conservation, surveillance of trypanosomatid infections, and territorial planning should be coordinated so that economic development and infrastructure projects do not erode ecosystem services provided by bats nor exacerbate health inequities in rural communities. Conclusion In summary, our synthesis shows that infections by T. cruzi and L. mexicana in Mexican bats are concentrated in human-modified matrices that also harbor important biodiversity values. Bats are not an intrinsic threat, but their pathogens can become a risk when unsustainable land-use change, poorly regulated infrastructure and inadequate waste management alter ecological and social interfaces [ 69 , 77 ]. Under a One Health framework, strategies to manage bat-borne zoonoses should prioritize conservation of natural habitats, improvement of housing and livestock management, and rigorous environmental governance of megaprojects, rather than persecution of bats. By linking pathogen data with spatial indicators of human pressure and conservation, this study provides an evidence base to inform more sustainable development pathways in regions where bats, people and pathogens coexist. Declarations Funding statement. This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Ethics, consent to participate, and consent to Publish declarations. Not applicable. This study is based exclusively on previously published data and did not involve new data collection from humans or animals. Clinical trial registration. Not applicable. Competing interests. The authors declare that they have no competing financial or non-financial interests relevant to the content of this article. Data availability. Not Applicable Author contributions . M.G.L. and A.R.M. Conceptualization, Methodology, Data curation, Writing- Original draft preparation, Visualization, Investigation, Writing- Original draft preparation. G.G.G. and J.J.F.M. Methodology, Writing- Original draft preparation, Visualization, Investigation, Writing- Original draft preparation. V.S.C. Data curation, Visualization, Investigation, Writing- Original draft preparation. 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González-Salazar C, Meneses-Mosquera AK, Aguirre-Peña A, Fernández-Castel KPJ, Stephens CR, Mendoza-Ponce A, et al. Toward New Epidemiological Landscapes of Trypanosoma cruzi Transmission under Future Human-Modified Land Cover and Climatic Change in Mexico. Trop Med Infect Dis. 2022;7(9):221. doi: 10.3390/tropicalmed7090221. Ramírez-Hernández G, Mas JF, Ramsey JM. Spatial patterns of human settlement infestation by Chagas disease vectors. Rev Cartogr. 2020;(100):41-59. Terraube J, Fernández-Llamazares Á. Strengthening protected areas to halt biodiversity loss and mitigate pandemic risks. Curr Opin Environ Sustain. 2020;46:35-38. doi: 10.1016/j.cosust.2020.08.014. Figueroa F, Sánchez-Cordero V. Effectiveness of natural protected areas to prevent land use and land cover change in Mexico. Biodivers Conserv. 2008;17(13):3223-3240. Hernández BEH, Vázquez-Quesada B, Vázquez-Barrios V, Nájera LB, Keinrad MB. Participatory environmental impact assessment: The Interoceanic Corridor of the Isthmus of Tehuantepec in San Juan Guichicovi, Oaxaca, Mexico. Society and Environment. 2024;(27):1-31. Ortega J, Castro-Arellano I. Artibeus jamaicensis . Mamm. Species. 2001;(662):1-9. Benítez-López A, Alkemade R, Verweij PA. The impacts of roads and other infrastructure on mammal and bird populations: A meta-analysis. Biol Conserv. 2010;143(6):1307-1316. De Jonge MMJ, Gallego-Zamorano J, Huijbregts MAJ, Schipper AM, Benítez-López A. The impacts of linear infrastructure on terrestrial vertebrate populations: A trait-based approach. Glob Change Biol. 2022;28(24):7217-7233. doi: 10.1111/gcb.16450. Stephens CR, González-Salazar C, Sánchez-Cordero V, Becker I, Rebollar-Tellez E, Rodríguez-Moreno Á, et al. Can you judge a disease host by the company it keeps? Predicting disease hosts and their relative importance: A case study for leishmaniasis. 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Ecological connectivity of Trypanosoma cruzi reservoirs and Triatoma pallidipennis hosts in an anthropogenic landscape with endemic Chagas disease. PLoS One. 2012;7(9):e46013. Torres-Castro M, Cuevas-Koh N, Hernández-Betancourt S, Noh-Pech H, Estrella E, Herrera-Flores B, et al. Natural infection with Trypanosoma cruzi in bats captured in Campeche and Yucatán, México. Biomedica. 2021;41:131-140. Moo-Millan JI, Tu W, de Jesús Montalvo-Balam T, Ibarra-López MP, Hernández-Betancourt S, Jesús May-Concha I, et al. Presence of Trypanosoma cruzi TcI and Trypanosoma dionisii in sylvatic bats from Yucatan, Mexico. Trans R Soc Trop Med Hyg. 2024;118(10):659-65. Taylor LH, Latham SM, Woolhouse ME. Risk factors for human disease emergence. Philos Trans R Soc Lond B Biol Sci. 2001;356(1411):983-9. Daszak P, Cunningham AA, Hyatt AD. Anthropogenic environmental change and the emergence of infectious diseases in wildlife. Acta Trop. 2001;78:103-16. Jones BA, Grace D, Kock R, Alonso S, Rushton J, Said MY, et al. Zoonosis emergence linked to agricultural intensification and environmental change. Proc Natl Acad Sci U S A. 2013;110:8399-404. Pech-Canché JM, MacSwiney C, Estrella E. Importancia de los detectores ultrasónicos para mejorar los inventarios de murciélagos neotropicales. Therya. 2010;1:221-8. Meyer CF, Aguiar LM, Aguirre LF, Baumgarten J, Clarke FM, Cosson JF, et al. Long-term monitoring of tropical bats for anthropogenic impact assessment: gauging the statistical power to detect population change. Biol Conserv. 2010;143(11):2797-807. Avila-Cabadilla LD, Sanchez-Azofeifa GA, Stoner KE, Alvarez-Añorve MY, Quesada M, et al. Local and landscape factors determining occurrence of phyllostomid bats in tropical secondary forests. PLoS One. 2012;7(4):e35228. doi: 10.1371/journal.pone.0035228. García-García JL, Santos-Moreno A, Kraker-Castañeda C. Ecological traits of phyllostomid bats associated with sensitivity to tropical forest fragmentation in Los Chimalapas, Mexico. Trop Conserv Sci. 2014;7(3):457-74. doi: 10.1177/194008291400700307. Cruz-Reyes A, Pickering-López J. Chagas disease in Mexico: an analysis of geographical distribution during the past 76 years-a review. Mem Inst Oswaldo Cruz. 2006;101:345-54. González C, Wang O, Strutz SE, González-Salazar C, Sánchez-Cordero V, Sarkar S. Climate change and risk of leishmaniasis in Mexico: A case study with Leishmania mexicana . PLoS Negl Trop Dis. 2011;5(7):e1161. Ellis EA, Navarro MA, García OM, Hernández GIU, Chacón CD. Forest cover dynamics in the Selva Maya of Central and Southern Quintana Roo, Mexico: deforestation or degradation? J Land Use Sci. 2020;15(1):25-51. doi: 10.1080/1747423X.2020.1732489. Gobierno de México [Internet]. Tren Maya [Presentación]. Proyectos México; 2022 [cited 2024 Aug 15]. Available from: https://www.proyectosmexico.gob.mx/wp-content/uploads/2022/11/Presentacio%CC%81n-11112022_T_Maya.pdf Bradley CA, Altizer S. Urbanization and the ecology of wildlife diseases. Trends Ecol Evol. 2007;22:95-102. doi: 10.1016/j.tree.2006.11.001. Ostfeld RS, Keesing F. Biodiversity and disease risk: The case of Lyme disease. Ecol Lett. 2000;3(2):105-6. Suzán G, Marcé E, Giermakowski JT, Mills JN, Ceballos G, Ostfeld RS, et al. Experimental evidence for reduced rodent diversity causing increased hantavirus prevalence. Ecohealth. 2009;6(3):289-95. Keesing F, Ostfeld RS. Dilution effects in disease ecology. Ecol Lett. 2021;24(11):2490-505. Meyer CFJ, Kalko EKV, Kerth G. Small-scale fragmentation effects on local genetic diversity in two phyllostomid bats with different dispersal abilities in Panama. Biotropica. 2008;40(1):30-38. Pardini R, Faria D, Accacio GM, Laps RR, Mariano-Neto E, Paciencia ML, et al. The challenge of maintaining Atlantic forest biodiversity: A multi-taxa conservation assessment of specialist and generalist species in an agro-forestry mosaic in southern Bahia. Biol Conserv. 2009;142:1178-90. García-García JL, Santos-Moreno A. Effects of landscape structure and vegetation on the diversity of phyllostomid bats (Chiroptera: Phyllostomidae) in Oaxaca, Mexico. Rev Biol Trop. 2014;62(1):217-39. Luis AD, Hayman DT, O'Shea TJ, Cryan PM, Gilbert AT, Pulliam JR, et al. A comparison of bats and rodents as reservoirs of zoonotic viruses: Are bats special? Proc Biol Sci. 2013;280(1756):20122753. doi: 10.1098/rspb.2012.2753. World Health Organization (WHO) [Internet]. Neglected tropical diseases; 2024 [cited 2024 Mar 12]. Available from: https://www.who.int/es/news-room/questions-and-answers/item/neglected-tropical-diseases Kessler MK, Becker DJ, Peel AJ, Justice NV, Lunn T, Crowley DE, et al. Changing resource landscapes and spillover of henipaviruses. Ann N Y Acad Sci. 2018;1429(1):78-99. doi: 10.1111/nyas.13910. Plowright RK, Parrish CR, McCallum H, Hudson PJ, Ko AI, Graham AL, et al. Pathways to zoonotic spillover. Nat Rev Microbiol. 2017;15(8):502-10. doi: 10.1038/nrmicro.2017.45. Bernstein AS, Ando AW, Loch-Temzelides T, Vale MM, Li BV, Li H, et al. The costs and benefits of primary prevention of zoonotic pandemics. Lancet Planet Health. 2023;7(3):e178-80. Ellis EA, Chacón Castillo D, Hernández Gómez IU, Madrid Zubirán SM, Cuervo Vega SM. Agricultural subsidies augmented tropical deforestation in the state of Campeche, Mexico. For Policy Econ. 2025;177:103525. Montiel S, Estrada A, León P. Bat assemblages in a naturally fragmented ecosystem in the Yucatan Peninsula, Mexico. J Trop Ecol. 2006;22(2):267-76. Kopczynski S, Nolen R, Hala D, Lases-Hernández F, Escobedo-Hinojosa W, Arcega-Cabrera F, et al. Investigation of Anthropogenic and Emerging Contaminants in Sinkholes (Cenotes) of the Great Mayan Aquifer, Yucatán Peninsula. Arch Environ Contam Toxicol. 2025;89(3):279-99. doi: 10.1007/s00244-025-01149-2. Anderson A, Shwiff SA, Gebhardt K, Ramírez AJ, Fowler GA, Shwiff SS. Economic evaluation of vampire bat ( Desmodus rotundus ) rabies prevention in Mexico. Transbound Emerg Dis. 2012;61(2):140-6. Jimenez-Rico MA, Vigueras-Galvan AL, Hernandez-Villegas EN, Martinez-Duque P, Roiz D, Falcon LI, et al. Bat coronavirus surveillance across different habitats in Yucatán, México. Virology. 2025;603:110401. Wyman M, Villegas ZG, Ojeda IM. Land-use/Land-cover Change in Yucatán State, Mexico: An examination of political, socioeconomic, and biophysical drivers in Peto and Tzucacab. Ethnobot Res Appl. 2007;5:59-66. Plowright RK, Reaser JK, Locke H, Woodley SJ, Patz JA, Becker DJ, et al. Land use-induced spillover: a call to action to safeguard environmental, animal, and human health. Lancet Planet Health. 2021 Apr;5(4):e237-45. doi: 10.1016/S2542-5196(21)00031-0. Epub 2021 Mar 6. PubMed PMID: 33684341; PubMed Central PMCID: PMC7935684. Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterial1.docx Cite Share Download PDF Status: Under Revision Version 1 posted Editorial decision: Revision requested 19 Mar, 2026 Reviews received at journal 10 Mar, 2026 Reviews received at journal 10 Mar, 2026 Reviewers agreed at journal 09 Mar, 2026 Reviews received at journal 03 Mar, 2026 Reviewers agreed at journal 02 Mar, 2026 Reviewers agreed at journal 01 Mar, 2026 Reviewers agreed at journal 28 Feb, 2026 Reviewers invited by journal 27 Feb, 2026 Editor assigned by journal 13 Feb, 2026 Submission checks completed at journal 13 Feb, 2026 First submitted to journal 13 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8744197","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Systematic Review","associatedPublications":[],"authors":[{"id":600109238,"identity":"489f88c9-915b-4d76-b50c-b16dd163e2aa","order_by":0,"name":"Margarita García-Luis","email":"","orcid":"","institution":"Universidad Autónoma Benito Juárez de Oaxaca","correspondingAuthor":false,"prefix":"","firstName":"Margarita","middleName":"","lastName":"García-Luis","suffix":""},{"id":600109239,"identity":"4cc5e557-24bf-4444-8a58-f376b73e8e55","order_by":1,"name":"Ángel Rodríguez-Moreno","email":"","orcid":"","institution":"Universidad Nacional Autónoma de México","correspondingAuthor":false,"prefix":"","firstName":"Ángel","middleName":"","lastName":"Rodríguez-Moreno","suffix":""},{"id":600109240,"identity":"126c0140-2bda-4f13-94e2-1959206cacf4","order_by":2,"name":"José Juan Flores-Martínez","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAnElEQVRIiWNgGAWjYBACxobDBw6TquVYAolaGBh4DJhJ08DceObj4QKGw3n80w6wbuYhzmFnNxyewXC4WOJ2AtvNGURr4WE4nNgA1HLjA3FazjwAa5kP0pJApBYGsJYNJNhyzODwDIP0xI23E9uI84vhjMOPPxdUWCfOu5187DZRIWY44wCQNIBYSIwGBgZ5fiIVjoJRMApGwQgGAMzKPEjm9bJlAAAAAElFTkSuQmCC","orcid":"","institution":"Universidad Nacional Autónoma de México","correspondingAuthor":true,"prefix":"","firstName":"José","middleName":"Juan","lastName":"Flores-Martínez","suffix":""},{"id":600109241,"identity":"f704636e-ee2d-41a7-a466-725a1afd2777","order_by":3,"name":"Gabriel Gutierrez-Granados","email":"","orcid":"","institution":"Universidad Nacional Autónoma de México","correspondingAuthor":false,"prefix":"","firstName":"Gabriel","middleName":"","lastName":"Gutierrez-Granados","suffix":""},{"id":600109242,"identity":"6e612a57-f050-4f67-badc-afc0bfaca9df","order_by":4,"name":"Víctor Sánchez-Cordero","email":"","orcid":"","institution":"Universidad Nacional Autónoma de México","correspondingAuthor":false,"prefix":"","firstName":"Víctor","middleName":"","lastName":"Sánchez-Cordero","suffix":""}],"badges":[],"createdAt":"2026-01-30 18:38:33","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8744197/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8744197/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":103920953,"identity":"410485d9-c459-484b-b6bb-71764c5df198","added_by":"auto","created_at":"2026-03-04 14:12:48","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":69979,"visible":true,"origin":"","legend":"\u003cp\u003ePRISMA model of the systematic review of scientific literature. \u003cstrong\u003eStudy selection:\u003c/strong\u003etitles and abstracts were screened first, followed by full-text review. A total of 14 studies were included (Table 1).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8744197/v1/724fded3a9e1cbb80b83a042.png"},{"id":104401867,"identity":"8b8458ad-0b9a-48ba-ac0e-9ebc56dea50d","added_by":"auto","created_at":"2026-03-11 12:13:47","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":201655,"visible":true,"origin":"","legend":"\u003cp\u003eLocation of sampling sites in studies on \u003cem\u003eTrypanosoma cruzi\u003c/em\u003e and \u003cem\u003eLeishmania mexicana\u003c/em\u003e in Mexico during the period 2001–2025. Dots show records where individuals of bats tested positive to species of \u003cem\u003eLeishmania \u003c/em\u003eand \u003cem\u003eTrypanosoma\u003c/em\u003e. Decreed protected areas (PAs) are shown in green polygons; the municipalities included in the CIIT are shown in brown polygons; the Maya train is depicted in the large red polygon in the Yucatan peninsula.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8744197/v1/7a62680b9988cbbc05c78303.png"},{"id":103920951,"identity":"4e8f51d0-014d-4dfc-8134-0adefcf20d07","added_by":"auto","created_at":"2026-03-04 14:12:48","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":192622,"visible":true,"origin":"","legend":"\u003cp\u003eKernel density map (resolution 0.5°) of bat localities in which infections by \u003cem\u003eLeishmania\u003c/em\u003espp. and/or \u003cem\u003eTrypanosoma\u003c/em\u003espp. have been recorded in Mexico. Red tones indicate a higher concentration of sampled localities. PAs are shown in green, and the municipalities are delineated with lines, highlighting the concentration of studies in western and southeastern Mexico. See Methods for details.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8744197/v1/b07c70e0ac487fcf5e31a48a.png"},{"id":103920955,"identity":"81eeacdf-53ae-40d7-99f5-b8617a9d381d","added_by":"auto","created_at":"2026-03-04 14:12:49","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":92301,"visible":true,"origin":"","legend":"\u003cp\u003e(a) Prevalence estimated across studies conducted in Mexico for \u003cem\u003eTrypanosoma cruzi\u003c/em\u003e. (b) Prevalence estimated across studies conducted in Mexico for \u003cem\u003eTrypanosoma cruzi\u003c/em\u003e TcI (Discrete Typing Unit I). E3: Córdova et al., 2013; E4: López-Cancino et al., 2015; E6: Víquez, 2015; E9: Torres-Castro et al., 2021; E10: Juárez, 2021; E11: Gómez-Sánchez et al., 2022; E12: Moo-Millan et al., 2024.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8744197/v1/9ceb796fffe1e9298b31e749.png"},{"id":103920944,"identity":"a210a1ce-6a2f-49aa-be72-3aa0497cccac","added_by":"auto","created_at":"2026-03-04 14:12:44","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":70884,"visible":true,"origin":"","legend":"\u003cp\u003ePrevalence estimated across studies conducted in Mexico for \u003cem\u003eLeishmania mexicana\u003c/em\u003e; only one study detected \u003cem\u003eLeishmania\u003c/em\u003esp., which is therefore included in the same plot using the genus identifier. E5: [7]; E6: Víquez, 2015; E7: Stephens et al., 2016; E8: Sánchez, 2019.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8744197/v1/6395faf614d20186e5fe8241.png"},{"id":104410638,"identity":"7cc29889-c3fe-43fb-aded-fec2461a913c","added_by":"auto","created_at":"2026-03-11 12:53:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2006010,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8744197/v1/4acd698f-8e6d-4b73-9aed-f8036758e98c.pdf"},{"id":103920952,"identity":"ed7f4979-1283-4449-a28a-4fa6a6be9434","added_by":"auto","created_at":"2026-03-04 14:12:48","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":33737,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8744197/v1/4356602297a28e2530127879.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"A systematic review of vector-borne pathogens in bats of Mexico in the Antropocene Vector-borne zoonoses in bats of Mexico","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBats constitute one of the most diverse and ecologically relevant mammalian groups worldwide. Their roles in pollination, seed dispersal, and insect control have been widely documented [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In recent decades, they have also gained prominence in public health due to their associations with multiple zoonotic pathogens. Globally, bats are considered epidemiologically relevant as reservoirs and potential amplifiers of major vector-borne zoonotic pathogens [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Understanding this relationship requires examining not only bat biology, but also the global environmental context shaped by anthropogenic transformations in ecosystems, which has an impact on both wildlife population dynamics and pathogen transmission cycles, facilitating potential zoonotic spillover [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBats harbor a wide variety of viruses, including coronaviruses, filoviruses, and henipaviruses, some of which have zoonotic potential [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. This viral diversity has been attributed to taxon-specific characteristics, ranging from evolutionary and life-history traits\u0026mdash;such as longevity, flight capacity, the formation of colonies of hundreds to millions of individuals, migration, extensive daily movement patterns, hibernation, and comparatively long lifespans relative to other mammals of similar size [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] to immunological features that enable tolerance of persistent infections without developing severe disease [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. For example, some studies show that bats harbor viruses with the highest known virulence, even if these are not necessarily the agents responsible for the greatest burden of disease in human populations [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Likewise, bat-associated ectoparasites represent an understudied, yet potentially critical, component in the transmission of pathogens to other mammals, including humans [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. This underscore bats and their associated parasites as key elements for zoonotic risk surveillance, given their roles as reservoirs and amplifiers of vector-borne pathogens across different geographic scales. From an ecological perspective, bats function as hosts by sustaining intraspecific transmission cycles that may remain stable if their habitats and social dynamics are not disrupted.\u003c/p\u003e \u003cp\u003eHowever, the Antropocene is characterized by human impacts on ecosystems have intensified deforestation, urbanization, and agricultural expansion that have deteriorated natural habitats with detrimental consequences on wildlife species and populations, including bats [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. These environmental changes modify bat movement patterns, stress levels, and population aggregation\u0026mdash;factors that can increase viral shedding and the risk of interspecific transmission [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. For example, habitat loss in Australia has been linked to the displacement of fruit bats into urban areas, increasing exposure of horses and, subsequently, humans to Hendra virus [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Similarly, agricultural expansion in Southeast Asia has created conditions conducive to Nipah virus transmission from bats to pigs and humans [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNonetheless, it is important to highlight that these processes indicate that bats do not represent an intrinsic threat \u003cem\u003eper se\u003c/em\u003e. Rather, it is the anthropogenic transformation of socio-ecological systems that disrupts the natural cycles of bats and their pathogens [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Thus, within the Anthropocene framework, emerging zoonotic diseases should be considered a consequence of natural habitat transformations. This implies that mitigation strategies should focus on ecosystem conservation, sustainable landscape management, and reducing high-risk interfaces, rather than persecuting or eliminating bat populations [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Bats play a central role in maintaining zoonotic pathogen cycles, but this role becomes a risk only when environmentally human-induced impacts shape ecological and transmission dynamics.\u003c/p\u003e \u003cp\u003eIn this context, \u003cem\u003eLeishmania mexicana\u003c/em\u003e and \u003cem\u003eTrypanosoma cruzi\u003c/em\u003e are two of the most important protozoa pathogens producing zoonotic diseases of public health importance in Mexico and Latin America, as the etiological agents of cutaneous leishmaniasis and Chagas disease, respectively. Several epidemiological analyses have shown that the true burden of \u003cem\u003eT. cruzi\u003c/em\u003e in Mexico is far higher than official reports, with millions of people potentially infected and limited access to timely diagnosis and treatment [\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In the case of \u003cem\u003eL. mexicana\u003c/em\u003e, active endemic areas persist in southeastern Mexico, where a growing number of human cases of cutaneous and mucocutaneous leishmaniasis have been reported [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Some recent studies have documented infection of bats and wild rodents by \u003cem\u003eL. mexicana\u003c/em\u003e, expanding the spectrum of implicated hosts and suggesting the existence of more complex sylvatic and peri-urban cycles than previously assumed. This evidence reinforces the need to integrate the ecological dimension of wildlife reservoirs into surveillance, prevention, and control strategies for both neglected zoonotic diseases [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe magnitude of this challenge is when considering the high species richness of bats in Mexico and the diversity of ecological functions they perform [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Mexico harbors more than 146 bat species, representing around 10% worldwide and the second most diverse mammalian group nationwide [\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Moreover, the highest species richness of bats occurs in the Neotropical region located in southern Mexico, particularly in the States of Chiapas, Oaxaca, Veracruz, and the Yucat\u0026aacute;n Peninsula [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The combination of a high species richness, a broad diversity of feeding habits, and habitat use (from tropical forests and cloud forests to agricultural landscapes and urban environments) implies multiple points of contact between species of vectors and wild and domestic species of potential hosts. This, in turn, facilitates a favorable scenario for the circulation and maintenance of pathogens such as \u003cem\u003eLeishmania mexicana\u003c/em\u003e and \u003cem\u003eTrypanosoma cruzi\u003c/em\u003e.\u003c/p\u003e \u003cp\u003eThe complex relationship between bats and zoonotic pathogens in Mexico unfolds across a highly heterogeneous environmental mosaic, where deforestation, agricultural expansion, and urbanization has deeply reshaped landscapes and transmission cycles. For example, in the Yucat\u0026aacute;n Peninsula, the conversion of tropical forests into agricultural areas and human settlements has been documented as being associated with higher prevalence of multiple zoonotic agents and vector-borne diseases [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Thus, intensive production systems increase opportunities for contact among wildlife, domestic animals, and humans [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. At the national scale, spatiotemporal analyses have shown that even small losses of forest cover translate into a significant increase in dengue risk, demonstrating that deforestation not only erodes biodiversity but also enhances vector capacity to invade human-modified environments [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. These patterns suggest that land-use change and habitat fragmentation may exert similar effects on phlebotomine sand flies and triatomines, facilitating local persistence of \u003cem\u003eLeishmania mexicana\u003c/em\u003e and \u003cem\u003eTrypanosoma cruzi\u003c/em\u003e in landscapes where bats, domestic reservoirs, and vulnerable human populations coexist [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Furthermore, they highlight that emerging zoonoses are a consequence of unsustainable landscape transformation and must be addressed within conservation planning, land-use management and sustainable development strategies [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Against this backdrop, the objective of this study was to systematically analyze studies compiled from the scientific literature documenting infections by \u003cem\u003eLeishmania mexicana\u003c/em\u003e and \u003cem\u003eTrypanosoma\u003c/em\u003e spp. in bats of Mexico. Specifically, we evaluated their spatial, taxonomic, and methodological distribution nationwide, and examined their relationships with human activities and their public health implications under a One Health approach.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cp\u003eA literature search was conducted in academic databases (BioOne, Scopus, Web of Knowledge, Redalyc, Elsevier) to identify publications reporting records of leishmaniasis or Chagas disease in Mexico. In addition, repositories were consulted (Tesis UNAM, UADY, ECOSUR, and other national universities), and a manual search was performed using the reference lists of key articles.\u003c/p\u003e\n\u003cp\u003eThe search was conducted following the PRISMA 2020 framework [\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e] (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). We restricted the time window to January 2001\u0026ndash;December 2024 because the earliest bat-focused reports of \u003cem\u003eT. cruzi\u003c/em\u003e and \u003cem\u003eL. mexicana\u003c/em\u003e in Mexico date from this period and studies on wildlife hosts and landscape drivers have intensified since the early 2000s [e. g. 31]. In each database, the following terms\u0026mdash;alone or in combination, in Spanish and English\u0026mdash;were used with the Boolean operators AND, OR, and NOT: murci\u0026eacute;lagos, M\u0026eacute;xico, hu\u0026eacute;spedes, pat\u0026oacute;genos, \u003cem\u003eleishmaniasis, tripanosomiasis\u003c/em\u003e, \u003cem\u003eLeishmania\u003c/em\u003e, \u003cem\u003eTrypanosoma\u003c/em\u003e, \u003cem\u003eTrypanosoma cruzi\u003c/em\u003e, \u003cem\u003eLeishmania mexicana\u003c/em\u003e, Chagas. The inclusion criteria, comprised studies with primary data or modeling-based evidence that: (a) included bats captured within Mexican territory, and (b) documented natural infection or a potential reservoir role for \u003cem\u003eL. mexicana\u003c/em\u003e and/or \u003cem\u003eTrypanosoma\u003c/em\u003e spp. Document types included peer-reviewed articles, book chapters, and graduate theses. We included graduate theses with primary data to reduce publication and geographic bias, this decision is consistent with methodological recommendations that emphasize the value of grey literature (including theses and technical reports) for improving coverage and minimizing bias in environmental and conservation evidence syntheses [\u003cspan class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e32\u003c/span\u003e]. The exclusion criteria, comprised studies focused on vectors or domestic reservoirs without data on bats; review articles without primary data or Mexico-specific models; studies in which bats were mentioned only speculatively.\u003c/p\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003eData compilation\u003c/h2\u003e\n \u003cp\u003eThe variables included were year, document type, state, bat species, pathogen(s), diagnostic method, sample size, number of positives, and prevalence. Data are summarized in Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e (study synthesis) and Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e (list of bat species with detections of \u003cem\u003eTrypanosoma\u003c/em\u003e spp. and \u003cem\u003eLeishmania mexicana\u003c/em\u003e, including positive and negative records as reported in the studies). Of the studies reviewed, 12 provided sufficient spatial information to georeference at least one locality with individuals of bats testing positive, resulting in a total of 54 localities with presence of at least one pathogen. The remaining localities were excluded from subsequent analyses. From the full set of localities, 14 were separated in which authors explicitly reported the number of positive individuals and sample size, allowing site-level prevalence to be calculated (25.9%, 14/54). The complete set of localities was treated as pathogen presence for subsequent analyses.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eSpatial analysis\u003c/h3\u003e\n\u003cp\u003eThe spatial framework was designed to be reproducible and applicable to sustainability-oriented risk assessments. To explore whether site-level prevalence or pathogen presence reflects gradients of anthropogenic disturbance, five spatial variables were selected. This selection was based on their relevance to reservoir ecology and the dynamics of vector-borne pathogens. Distance to the nearest human locality and to the road network was used as a proxy for disturbance and synanthropic gradients, given that studies have shown that \u003cem\u003eT. cruzi\u003c/em\u003e circulation in wild and domestic mammals is associated with rural\u0026ndash;peri-urban mosaics, settlement density, and road connectivity, which facilitate contact among reservoirs, vectors, and humans [\u003cspan class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e34\u003c/span\u003e]. Distance to decreed protected areas (PAs) was included to contrast the location of records relative to areas under some protection regime, following previous approaches that assess vector-borne zoonosis risk as a function of natural cover and conservation designations [\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e36\u003c/span\u003e]. The CIIT and Maya train were incorporated as examples of infrastructure megaprojects in southeastern Mexico that are expected to drive intense land-use change, fragmentation, and increased flows of people and goods, with potential implications for disease transmission [\u003cspan class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e37\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eTo evaluate the spatial relationship between pathogen prevalences/detections and landscape variables, a spatial analysis was conducted in QGIS 3.43.0. First, georeferenced presence sites of \u003cem\u003eTrypanosoma cruzi\u003c/em\u003e (including TcI, Discrete Typing Unit I), \u003cem\u003eTrypanosoma\u003c/em\u003e spp., \u003cem\u003eT. dionisii\u003c/em\u003e, and \u003cem\u003eLeishmania mexicana\u003c/em\u003e were compiled from the identified studies. All points and environmental layers (human localities, road network the Corredor Interoce\u0026aacute;nico del Istmo de Tehuantepec (CIIT) and the Maya train (Tren Maya) alignments, and polygons of PAs were re-projected to a projected meter-based CRS (EPSG:4326-WGS 84 \u0026rarr; EPSG:6372-Mexico ITRF2008/LCC) to minimize distortion and ensure that Euclidean distances were comparable.\u003c/p\u003e\n\u003cp\u003eMinimum distances from each presence point to each variable were obtained using the QGIS proximity tool \u0026ldquo;distance to nearest hub\u0026rdquo; (nearest neighbor), calculating for each site identified in the research in Mexico: (1) distance to the nearest human locality, (2) distance to the nearest segment of the road network, (3) orthogonal distance to the CIIT axis, (4) orthogonal distance to the Maya train axis, and (5) distance to the nearest PAs boundary. All distances were exported in meters and subsequently converted to kilometers for ecological interpretation. As quality control, points were visually inspected and frequency histograms were generated for each distance variable; this enabled identification of outliers associated with coordinate errors (e.g., inverted longitude signs), which were corrected before recalculating distances.\u003c/p\u003e\n\u003cp\u003ePoints were grouped into distance classes defined as \u003cem\u003ea priori\u003c/em\u003e but adjusted based on the distributions observed in histograms and on ecological considerations regarding bat movements and the spatial scale of infrastructure influence. For proximity to human localities and the road network, three classes were used: 0\u0026ndash;2 km, 2\u0026ndash;5 km, and \u0026gt;\u0026thinsp;5 km. The 2 km threshold reflects the immediate environment of sampling sites and falls within the typical range of local foraging for many phyllostomid bats, whose nocturnal movements from roosts to feeding areas often range from hundreds of meters to a few kilometers (e.g., \u003cem\u003eArtibeus jamaicensis\u003c/em\u003e with mean movements\u0026thinsp;\u0026lt;\u0026thinsp;0.6 km from day roosts to feeding trees [\u003cspan class=\"CitationRef\"\u003e38\u003c/span\u003e]. The 2\u0026ndash;5 km interval was considered representative of an expanded daily activity radius, whereas \u0026gt;\u0026thinsp;5 km reflects sites relatively farther from the immediate anthropogenic matrix, yet still reachable within the known movement capacity of several Neotropical bat species, which may travel several to tens of kilometers in a single night. In addition, studies have suggested that road effects on vertebrate abundance are strongest within the first kilometer and can extend several kilometers outward, supporting the distinction between very proximate zones (0\u0026ndash;2 km) and peri-influence (2\u0026ndash;5 km) [\u003cspan class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e40\u003c/span\u003e].\u003c/p\u003e\n\u003cp\u003eFor PAs, three categories were defined: 0\u0026ndash;10 km, 10\u0026ndash;40 km, and \u0026gt;\u0026thinsp;40 km from the nearest boundary. The 10 km threshold is based on studies that use 5\u0026ndash;10 km or 10\u0026ndash;20 km buffers to quantify the \u0026ldquo;zone of influence\u0026rdquo; or isolation of protected areas, given that the main gradients of land-cover change and human pressure around conservation polygons are concentrated within these distances. The intermediate interval (10\u0026ndash;40 km) represents a regional landscape still under indirect influence of PAs (e.g., as a source of dispersing individuals), whereas \u0026gt;\u0026thinsp;40 km is interpreted as a context largely functionally disconnected from these habitat cores, at least at the scale of daily movements.\u003c/p\u003e\n\u003cp\u003eFor the CIIT and Maya train, the scale of these projects is continental (e.g., distance values range from hundreds to more than one thousand kilometers). Given that these scales far exceed daily movement distances of bats, broad classes were defined to distinguish regional gradients of exposure to megaprojects rather than strict ecological thresholds: 0\u0026ndash;200 km, 200\u0026ndash;600 km, and \u0026gt;\u0026thinsp;600 km for CIIT, and 0\u0026ndash;300 km, 300\u0026ndash;900 km, and \u0026gt;\u0026thinsp;900 km for the Maya train. Cutting-points were selected by combining inflection points observed in histograms (changes in frequency density) with the goal of differentiating a direct or nearby regional sphere of influence, an intermediate sphere, and a remote sphere relative to each infrastructure corridor. Lastly, distance categories for each variable were incorporated as new fields in the attribute table using the QGIS field calculator and were used in descriptive and comparative analyses of the distribution of presences for each pathogen. This approach explicitly integrated bat movement scales and the spatial scale of human infrastructure into the interpretation of spatial infection patterns, while maintaining a reproducible methodology based on quantitative distance metrics; these data were used to construct Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e and Supplementary material 1.\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDistance from human locality, road nerwork, CIIT (Corredor Interoce\u0026aacute;nico del Istmo de Tehuantepec), Maya train, and Protected Areas (PAs) to localities with site-level prevalence of \u003cem\u003eLeishmania mexicana\u003c/em\u003e and \u003cem\u003eTrypanosoma\u003c/em\u003e spp.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNo.\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ePathogen\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSite-level prevalence\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e0\u0026ndash;5 km\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;5 km\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eTrypanosoma cruzi\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7/34(20.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHuman locality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRoad network\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCIIT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e357.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaya train\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e770.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePAs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eTrypanosoma cruzi\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15/172(8.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHuman locality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRoad network\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCIIT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e550.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaya train\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePAs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eTrypanosoma cruzi\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11/184(6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHuman locality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRoad network\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCIIT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e458.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaya train\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e36.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePAs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eLeishmania mexicana\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11/124(8.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHuman locality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRoad network\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCIIT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e296.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaya train\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e128.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePAs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eTrypanosoma\u003c/em\u003e sp.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2/124(1.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHuman locality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e11.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRoad network\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCIIT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e296.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaya train\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e128.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePAs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eLeishmania mexicana\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2/12(16.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHuman locality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRoad network\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCIIT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaya train\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e352.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePAs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eLeishmania mexicana\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2/18(11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHuman locality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRoad network\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCIIT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaya train\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e346.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePAs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eTrypanosoma cruzi\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10/26(38.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHuman locality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRoad network\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCIIT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e431\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaya train\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePAS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eTrypanosoma cruzi\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16/23(69.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHuman locality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRoad network\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCIIT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e699.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaya train\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePAs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eTrypanosoma cruzi\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/19(5.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHuman locality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRoad network\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCIIT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaya train\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e346.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePAs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eTrypanosoma cruzi\u003c/em\u003e TcI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18/110(16.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHuman locality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRoad network\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCIIT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e84.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaya train\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e154.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePAs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eTrypanosoma cruzi\u003c/em\u003e TcI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7/72(9.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHuman locality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRoad network\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCIIT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e617.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaya train\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePAs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e86.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eTrypanosoma dionisii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/72(1.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHuman locality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRoad network\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCIIT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e617.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaya train\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePAs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e86.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eTrypanosoma\u003c/em\u003e sp.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1/72(1.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHuman locality\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRoad network\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCIIT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e617.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaya train\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePAs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e86.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 14 studies conducted in Mexico between 2001 and 2024 were recorded. Of these, three were theses, one was a book chapter, two were short communications, and eight were journal articles. The year with the highest number of publications was 2015 (n\u0026thinsp;=\u0026thinsp;3), followed by 2021 and 2024 (n\u0026thinsp;=\u0026thinsp;2 each). Studies have been reported in 40.6% (n\u0026thinsp;=\u0026thinsp;13) of the country. The States with the highest number of published studies were Chiapas and Yucat\u0026aacute;n (n\u0026thinsp;=\u0026thinsp;4 each), followed by Morelos and Veracruz (n\u0026thinsp;=\u0026thinsp;3), Tabasco and Campeche (n\u0026thinsp;=\u0026thinsp;2), while seven States had only one study; one study addressed leishmaniasis at the national level [\u003cspan class=\"CitationRef\"\u003e41\u003c/span\u003e] Figs. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e, Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003ePublications by year on \u003cem\u003eTrypanosoma\u003c/em\u003e sp. and \u003cem\u003eLeishmania\u003c/em\u003e sp. in bats from Mexico. * The authors do not report positive individuals; therefore, overall prevalence cannot be calculated.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"8\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNo.\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eType\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAuthors (year)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eTitle\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eJournal/Book\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eDiagnostic method\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSample size\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eMunicipality/State\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCommunication\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVillegas-Garc\u0026iacute;a \u0026amp; Santill\u0026aacute;n-Alarc\u0026oacute;n, 2001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSylvatic focus of American trypanosomiasis in the state of Morelos, Mexico\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRevista de Biolog\u0026iacute;a Tropical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eXenodiagnostic / serology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34/*(*)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTicum\u0026aacute;n and Tlaltizap\u0026aacute;n, Morelos\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCommunication\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVillegas-Garc\u0026iacute;a \u0026amp; Santill\u0026aacute;n-Alarc\u0026oacute;n, 2004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAmerican trypanosomiasis in central Mexico: \u003cem\u003eTrypanosoma cruzi\u003c/em\u003e infection in triatomine bugs and mammals from the municipality of Jiutepec in the state of Morelos\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAnnals of Tropical Medicine \u0026amp; Parasitology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eXenodiagnostic / serology\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e77 /*(*)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJiutepec, Morelos\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBook chapter\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eC\u0026oacute;rdova, Escobedo, Hern\u0026aacute;ndez y Ruiz, 2013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLos murci\u0026eacute;lagos en el ciclo de transmisi\u0026oacute;n de \u003cem\u003eTrypanosoma cruzi\u003c/em\u003e en el peridomicilio rural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEstudios multidisciplinarios de las enfermedades zoon\u0026oacute;ticas y ETVs en Yucat\u0026aacute;n\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePCR/ literature review\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e172/\u003cstrong\u003e15\u003c/strong\u003e(8.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMolas, M\u0026eacute;rida, Yucat\u0026aacute;n\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eArticle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eL\u0026oacute;pez-Cancino, Tun-Ku, de la Cruz, Ibarra-Cerde\u0026ntilde;a, Izeta-Alberdi, Pech-May, Mazariegos-Hidalgo, Valdez-Tah y \u0026amp; Ramsey, 2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLandscape ecology of \u003cem\u003eTrypanosoma cruzi\u003c/em\u003e in the southern Yucatan Peninsula\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eActa Tropica\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePCR/ spatial analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e184/\u003cstrong\u003e11\u003c/strong\u003e(6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCampeche, M\u0026eacute;xico\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eArticle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBerzunza-Cruz, Rodr\u0026iacute;guez-Moreno, Guti\u0026eacute;rrez-Granados, Gonz\u0026aacute;lez-Salazar, Stephens, Hidalgo-Mihart, Marina, Rebollar-T\u0026eacute;llez, Ball\u0026oacute;n-Mart\u0026iacute;nez, Domingo, Ibarra-Cerde\u0026ntilde;a, S\u0026aacute;nchez-Cordero \u0026amp; Becker,\u0026nbsp;2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eLeishmania\u003c/em\u003e (L.) \u003cem\u003emexicana\u003c/em\u003e infected bats in Mexico: novel potential reservoirs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePLoS Neglected Tropical Diseases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePCR/sequencing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e420/\u003cstrong\u003e41\u003c/strong\u003e(9.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eChiapas, Tabasco, Jalisco\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThesis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eV\u0026iacute;quez, 2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDetecci\u0026oacute;n de \u003cem\u003eL. mexicana\u003c/em\u003e y \u003cem\u003eTrypanosoma\u003c/em\u003e spp. en murci\u0026eacute;lagos de Chiapas\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMaster\u0026rsquo;s (thesis), UNAM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eT. cruzi\u003c/em\u003e 124/\u003cstrong\u003e2\u003c/strong\u003e (1.6%)\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eL. mexicana\u003c/em\u003e 124/\u003cstrong\u003e11\u003c/strong\u003e(8.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSelva Lacandona, Chiapas\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eArticle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eStephens, Gonzalez-Salazar, S\u0026aacute;nchez-Cordero, Becker, Rebollar-Tellez, Rodriguez-Moreno, \u0026nbsp;Berzunza-Cruz, Domingo, Guti\u0026eacute;rrez-Granados, Hidalgo-Mihart, Ibarra-Cerde\u0026ntilde;a, Ibarra, I\u0026ntilde;iguez \u0026amp; Ram\u0026iacute;rez, 2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCan you judge a disease host by the company it keeps? Predicting disease hosts and their relative importance: a case study for Leishmaniasis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePLoS neglected tropical diseases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePCR/ spatial modeling\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e413/\u003cstrong\u003e38\u003c/strong\u003e (9.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eM\u0026eacute;xico\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThesis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eS\u0026aacute;nchez, 2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDetecci\u0026oacute;n de \u003cem\u003eLeishmania mexicana\u003c/em\u003e en murci\u0026eacute;lagos de la regi\u0026oacute;n de los Tuxtlas, Veracruz, M\u0026eacute;xico\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUndergraduate (thesis), UNAM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43/\u003cstrong\u003e3\u003c/strong\u003e(6.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSan Andr\u0026eacute;s Tuxtla y Santecomapam, Veracruz\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e9\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eArticle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTorres-Castro, Cuevas-Koh, Hern\u0026aacute;ndez-Betancourt, Noh-Pech, Estrella, Herrera-Flores, Panty-May, Waleckx, Sosa-Escalante \u0026amp; Pel\u0026aacute;ez-S\u0026aacute;nchez, 2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNatural infection with \u003cem\u003eTrypanosoma cruzi\u003c/em\u003e in bats captured in Campeche and Yucat\u0026aacute;n, M\u0026eacute;xico\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBiomedica\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePCR (kDNA)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e86/\u003cstrong\u003e26\u003c/strong\u003e (30.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTzucacab y Panab\u0026aacute;, Yucat\u0026aacute;n\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eThesis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eJu\u0026aacute;rez, 2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDetecci\u0026oacute;n de \u003cem\u003eTrypanosoma\u003c/em\u003e sp. en murci\u0026eacute;lagos de \u0026ldquo;Los Tuxtlas\u0026rdquo;, Veracruz, M\u0026eacute;xico\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLicenciatura, UNAM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43/\u003cstrong\u003e1\u003c/strong\u003e (2.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLos Tuxtlas, Veracruz\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e11\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eArticle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eG\u0026oacute;mez-S\u0026aacute;nchez, Ochoa-D\u0026iacute;az-L\u0026oacute;pez, Espinoza-Medinilla, Vel\u0026aacute;zquez-Ram\u0026iacute;rez, Santos-Hern\u0026aacute;ndez, Ruiz-Castillejos, Vidal-Lopez, Moreno-Rodriguez, Flores-Villegas, Lopez-Argueta \u0026amp; De Fuentes-Vicente, 2022\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e໿Mini-exon gene reveals circulation of TcI \u003cem\u003eTrypanosoma cruzi\u003c/em\u003e (Chagas, 1909)(Kinetoplastida, Trypanosomatidae) in bats and small mammals in an ecological reserve in southeastern Mexico\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eZookeys\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emini-exon gene PCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110/\u003cstrong\u003e18\u003c/strong\u003e (16.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEl Zapotal, Chiapas\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e12\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eArticle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMoo-Millan, Tu, Montalvo-Balam, Ibarra-L\u0026oacute;pez, Hern\u0026aacute;ndez-Betancourt, May-Concha, Ibarra-Cerde\u0026ntilde;a, Barnab\u0026eacute;, Dumonteil, Waleckx, 2024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePresence of \u003cem\u003eTrypanosoma cruzi\u003c/em\u003e TcI and \u003cem\u003eTrypanosoma dionisii\u003c/em\u003e in sylvatic bats from Yucatan, Mexico.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eTransactions of the Royal Society of Tropical Medicine and Hygiene\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePCR/multilocus sequencing\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eTrypanosoma cruzi\u003c/em\u003e 72/\u003cstrong\u003e7\u003c/strong\u003e(9.7%)\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eTrypanosoma dionisii\u003c/em\u003e 72/\u003cstrong\u003e1\u003c/strong\u003e(1.4%)\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eTrypanosoma\u003c/em\u003e spp 72/\u003cstrong\u003e1\u003c/strong\u003e(1.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSudzal, Yucat\u0026aacute;n\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e13\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eArticle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRengifo-Correa, Rodr\u0026iacute;guez-Moreno, Becker, Falc\u0026oacute;n-Lezama, Tapia-Conyer, S\u0026aacute;nchez-Montes, Suz\u0026aacute;n, Stephens \u0026amp; Gonz\u0026aacute;lez-Salazar, 2024\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRisk of a vector-borne endemic zoonosis for wildlife: Hosts, large-scale geography, and diversity of vector-host interactions for \u003cem\u003eTrypanosoma cruzi\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eActa Tropica\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e524/\u003cstrong\u003e75\u003c/strong\u003e(14.3%)\u003c/p\u003e\n \u003cp\u003eDoes not include only bats in the prevalence calculation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVeracruz, Tabasco, Chiapas, Yucatan, Campeche, San Luis Potos\u0026iacute;, Nuevo Le\u0026oacute;n, Chihuahua, Baja California Sur, Jalisco, Nayarit and Mexico state.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e14\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eArticle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRamsey, J. M., Guti\u0026eacute;rrez-Cabrera, A. E., Salgado-Ram\u0026iacute;rez, L., Peterson, A. T., S\u0026aacute;nchez-Cordero, V., \u0026amp; Ibarra-Cerde\u0026ntilde;a, C. N., 2012\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEcological Connectivity of \u003cem\u003eTrypanosoma cruzi\u003c/em\u003e Reservoirs and \u003cem\u003eTriatoma pallidipennis\u003c/em\u003e Hosts in an Anthropogenic Landscape with Endemic Chagas Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePLOS ONE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e116/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMorelos\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eRegarding the pathogen identification technique used, 12 studies employed PCR (including all variants, e.g., conventional PCR, kDNA-based assays, etc.), followed by xenodiagnosis and serology, both used in two studies [\u003cspan class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e43\u003c/span\u003e]. Sample sizes per study ranged from 34 individuals in Morelos [\u003cspan class=\"CitationRef\"\u003e42\u003c/span\u003e] to 524 individuals surveyed across 12 States [\u003cspan class=\"CitationRef\"\u003e44\u003c/span\u003e]. Overall prevalence across studies ranged from 0% in Morelos [\u003cspan class=\"CitationRef\"\u003e45\u003c/span\u003e] to 30.2% in Yucat\u0026aacute;n [\u003cspan class=\"CitationRef\"\u003e46\u003c/span\u003e] (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Further, regarding pathogen detection, \u003cem\u003eTrypanosoma cruzi\u003c/em\u003e, \u003cem\u003eT.\u003c/em\u003e cruzi TcI (Discrete Typing Unit I), \u003cem\u003eTrypanosoma dionisii\u003c/em\u003e, \u003cem\u003eTrypanosoma\u003c/em\u003e sp., and \u003cem\u003eLeishmania mexicana\u003c/em\u003e were identified in 45 species of bats from six families, representing 31% of the species of bats nationwide (146) [\u003cspan class=\"CitationRef\"\u003e23\u003c/span\u003e]. The family Phyllostomidae ranked highest including 29 species, followed by Vespertilionidae with seven; Noctilionidae had the fewest records, with a single species (\u003cem\u003eNoctilio leporinus\u003c/em\u003e). At the species level, \u003cem\u003eArtibeus jamaicensis\u003c/em\u003e and \u003cem\u003eSturnira parvidens\u003c/em\u003e were the most frequently included in the surveyed studies, mentioned in 79% (n\u0026thinsp;=\u0026thinsp;12) of all publications; seven species were addressed in only one study (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eBat species in which \u003cem\u003eLeishmania mexicana\u003c/em\u003e and \u003cem\u003eTrypanosoma\u003c/em\u003e sp. have been detected in studies conducted in Mexico. * Prevalence cannot be calculated because the authors do not specify whether all positives correspond to the same individual or to different individuals. E\u0026thinsp;=\u0026thinsp;study (each number corresponds to the study No. in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e), e\u0026thinsp;=\u0026thinsp;examined individuals, P\u0026thinsp;=\u0026thinsp;positives. Positive individuals reported in each study are highlighted in bold.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"5\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eHost\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eTrypanosoma cruzi\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eTrypanosoma cruzi TcI\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eLeishmania mexicana\u003c/em\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eFamilia Emballonuridae\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colspan=\"3\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eBalantiopteryx plicata\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eE1 2/0(*), E14 56/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eSaccopteryx bilineata\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eE10 12/0(0), E13 1/*(\u003cstrong\u003e*\u003c/strong\u003e)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE5, E7 1/0(0)\u003c/p\u003e\n \u003cp\u003eE8 12/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eFamilia Noctilionidae\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eNoctilio leporinus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eE9 6/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eFamilia Mormoopidae\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eMormoops megalophylla\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE11 2/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePteronotus fulvus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eE3 1/0(0) - E9 2/0(0) - E10 13/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE11 1/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE8 13/\u003cstrong\u003e1\u003c/strong\u003e (7.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePteronotus mesoamericanus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eE1 6/\u003cstrong\u003e5\u003c/strong\u003e(*)- E2 13/10(*)- E9 6/\u003cstrong\u003e4\u003c/strong\u003e(66.7%) - E10 2/0(0) - E14 8/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE11 3/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE5 5/0(0), E7 4/0(0)\u003c/p\u003e\n \u003cp\u003eE8 2/\u003cstrong\u003e1\u003c/strong\u003e(50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePteronotus psilotis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eE10 1/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE5 4/\u003cstrong\u003e1\u003c/strong\u003e(25%), E7 4/\u003cstrong\u003e1\u003c/strong\u003e(25%), E8 1/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eFamilia Phyllostomidae\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eMicronycteris microtis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eE14 1/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE5, E7 1/0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eDesmodus rotundus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eE2 12/\u003cstrong\u003e11\u003c/strong\u003e(*) - E14 2/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE11 2/0(0) -E12 16/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE5, E7 14/\u003cstrong\u003e1\u003c/strong\u003e (7.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eDiaemus youngi\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE5 1/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eDiphylla ecaudata\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eE3 4/0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eLonchorhina aurita\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eE6\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE5 1/0(0), E7 1/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eMimon cozumelae\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE12 4/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePhyllostomus discolor\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE5, E7 1/\u003cstrong\u003e1\u003c/strong\u003e (100%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eAnoura peruana\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE5 6/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eChoeroniscus godmani\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eE10 3/\u003cstrong\u003e1\u003c/strong\u003e(33.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE5, E7 13/\u003cstrong\u003e3\u003c/strong\u003e(23.0%), E8 3/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eChoeronycteris mexicana\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eE1 1/\u003cstrong\u003e2\u003c/strong\u003e(*) - E14 3/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eGlossophaga commisarisi\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eE13 1/- (*)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE5, E7 8/\u003cstrong\u003e6\u003c/strong\u003e(75.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eGlossophaga mutica\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eE1 1/\u003cstrong\u003e1\u003c/strong\u003e (*), E3 11/0(0), E9 5/\u003cstrong\u003e4\u003c/strong\u003e(80.0%), E12 1/0(0) - E14 2/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE11 8/\u003cstrong\u003e1\u003c/strong\u003e(12.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE5 26/\u003cstrong\u003e7\u003c/strong\u003e(26.9%), E7 16/\u003cstrong\u003e7\u003c/strong\u003e(43.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eLeptonycteris yerbabuenae\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eE2 25/\u003cstrong\u003e18\u003c/strong\u003e (*) - E14 2/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE11 2/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE5, E7 2/\u003cstrong\u003e1\u003c/strong\u003e(50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eMacrotus waterhousii\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eE14 6/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eCarollia perspicillata\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eE4 3/\u003cstrong\u003e2\u003c/strong\u003e(66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE11 7/\u003cstrong\u003e2\u003c/strong\u003e (28.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE5, E7 8/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eCarollia sowelli\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eE6 83/\u003cstrong\u003e2\u003c/strong\u003e(1.6%) - E9 2/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE5 45/\u003cstrong\u003e2\u003c/strong\u003e(4.4%) - E6 83/\u003cstrong\u003e5\u003c/strong\u003e(6%) - E7 44/\u003cstrong\u003e2\u003c/strong\u003e(4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eArtibeus jamaicensis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eE1 7/\u003cstrong\u003e6\u003c/strong\u003e (*) - E2 47/23 (*) - E3 99/5 (2.9%)- E4 62/\u003cstrong\u003e2\u003c/strong\u003e (3.2%) - E9 45/\u003cstrong\u003e10\u003c/strong\u003e (22.2%)- E10 10/0 (0) - E12 55/\u003cstrong\u003e6\u003c/strong\u003e (10.9%) - E14 9/\u003cstrong\u003e0\u003c/strong\u003e (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE11 64/\u003cstrong\u003e10\u003c/strong\u003e (15.6%)\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eTrypanosoma dionisii\u003c/em\u003e E12 55/\u003cstrong\u003e1\u003c/strong\u003e(1.8%)\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eTrypanosoma\u003c/em\u003e spp. E12 55/\u003cstrong\u003e1\u003c/strong\u003e(1.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE5, E7 86/\u003cstrong\u003e5\u003c/strong\u003e (5.81%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eArtibeus lituratus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eE3 37/\u003cstrong\u003e9\u003c/strong\u003e (5.23%)- E4 33/\u003cstrong\u003e1\u003c/strong\u003e (3%) - E9 2/2 (100%) \u0026ndash; E14 10/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE11 16/\u003cstrong\u003e3\u003c/strong\u003e (18.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE5 41/\u003cstrong\u003e3\u003c/strong\u003e (7.31%)- E7 39/\u003cstrong\u003e3\u003c/strong\u003e(7.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eCenturio senex\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE11 2/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE5 1/0(0) - E7 1/0(0) -\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eChiroderma villosum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eE9 7/\u003cstrong\u003e4\u003c/strong\u003e (57.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE5 5/0(0) - E7 5/0(0) -\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eDermanura sp.\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eE14 1/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eDermanura phaoetis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eE4 10/\u003cstrong\u003e1\u003c/strong\u003e(10%) - E9 3/0(0) - E12 8/0(0)- E13 1/*(**)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE5 37/\u003cstrong\u003e3\u003c/strong\u003e (8.1%) - E7 36/\u003cstrong\u003e1\u003c/strong\u003e(2.78%) -\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eDermanura tolteca\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eE10 1/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE5 1/0(0), E8 1/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eDermanura watsoni\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE12 1/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE5, E7 2/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003ePlatyrrhinus helleri\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eE10 1/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE5 5/0(0), E7 3/0(0), E8 1/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eSturnira hondurensis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eE4 18/\u003cstrong\u003e1\u003c/strong\u003e(5.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE5, E7 25/\u003cstrong\u003e1\u003c/strong\u003e(4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eSturnira parvidens\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eE1 17/\u003cstrong\u003e16\u003c/strong\u003e(*) - E2 19/\u003cstrong\u003e19\u003c/strong\u003e(*) - E3 19/\u003cstrong\u003e1\u003c/strong\u003e (0.6%)- E4 51/\u003cstrong\u003e3\u003c/strong\u003e(5.9%) - E6 41/0(0) - E9 1/\u003cstrong\u003e1\u003c/strong\u003e (100%) - E12 1/\u003cstrong\u003e1\u003c/strong\u003e(100%) - E14 1/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE11 3/2 (66.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE5 63/\u003cstrong\u003e7\u003c/strong\u003e(11.1%) - E6 41/\u003cstrong\u003e5\u003c/strong\u003e(8.2%) - E7 64/\u003cstrong\u003e6\u003c/strong\u003e(9.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eUroderma convexum\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eE9 1/0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE5, E7 4/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eVampyrodes major\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE5, E7 1/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eFamilia Molossidae\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eMolussus nigricans\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eE13 1/*(*)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE5, E7 1/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eTadaria brasiliensis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE5, E7 1/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eFamilia Vespertilionidae\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eAntrozous pallidus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE5, E7 1/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eEptesicus fuscus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE5, E7 1/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eMyotis auriculus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE5, E7 2/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eMyotis extremus\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE5, E7 2/0 (0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eMyotis pilosatibialis\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eE4 7/\u003cstrong\u003e1\u003c/strong\u003e(14.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE5, E7 2/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eMyotis velifer\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eE5 3/0(0), E7 4/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cem\u003eRhogeessa aenea\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eE3 1/0(0), E9 1/\u003cstrong\u003e1\u003c/strong\u003e(100%) - E12 1/0(0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eFor species of bats with positive records for pathogen presence, detection of one or both pathogens were confirmed in 20 species (14% of species of bats nationwide). In \u003cem\u003eChoeronycteris mexicana\u003c/em\u003e, \u003cem\u003eChiroderma villosum\u003c/em\u003e, \u003cem\u003eMyotis pilosatibialis\u003c/em\u003e, and \u003cem\u003eRhogeessa aenea\u003c/em\u003e, only \u003cem\u003eTrypanosoma cruzi\u003c/em\u003e has been identified. In \u003cem\u003ePteronotus fulvus\u003c/em\u003e, \u003cem\u003eP. psilotis\u003c/em\u003e, \u003cem\u003ePhyllostomus discolor\u003c/em\u003e, and \u003cem\u003eGlossophaga commissarisi\u003c/em\u003e, only \u003cem\u003eLeishmania mexicana\u003c/em\u003e has been identified; in eleven species, both pathogens have been detected (Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). For species of pathogens, \u003cem\u003eTrypanosoma cruzi\u003c/em\u003e showed the highest prevalence (100%) in \u003cem\u003eArtibeus lituratus\u003c/em\u003e [\u003cspan class=\"CitationRef\"\u003e46\u003c/span\u003e], \u003cem\u003eSturnira parvidens\u003c/em\u003e [\u003cspan class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e47\u003c/span\u003e], and \u003cem\u003eRhogeessa aenea\u003c/em\u003e [\u003cspan class=\"CitationRef\"\u003e46\u003c/span\u003e], Figure \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003ea). For \u003cem\u003eT.\u003c/em\u003e cruzi TcI, \u003cem\u003eSturnira parvidens\u003c/em\u003e had the highest prevalence (66.6%, Figure \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003eb). For \u003cem\u003eLeishmania mexicana\u003c/em\u003e, \u003cem\u003ePhyllostomus discolor\u003c/em\u003e [\u003cspan class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e41\u003c/span\u003e] showed the highest prevalence (100%, Figure \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e). However, it is important to note that these maximum values were obtained from very small sample sizes (one or two individuals per species per study) and therefore do not reflect robust population-level prevalence estimates.\u003c/p\u003e\n\u003ch3\u003eSpatial presence of pathogens\u003c/h3\u003e\n\u003cp\u003eFor the 54 localities with confirmed positive records of \u003cem\u003eTrypanosoma\u003c/em\u003e spp. and \u003cem\u003eLeishmania mexicana\u003c/em\u003e in bats, pathogen presence was strongly concentrated in the nearest distance classes to human infrastructure. For distance to the nearest human locality, the dominant class was 0\u0026ndash;2 km, which contained 74.1% of records (40/54), whereas only a small fraction of sites was located beyond 5 km. A stronger association was observed for the road network, with 87.0% of records (47/54) occurring within 0\u0026ndash;2 km of a road segment. With respect to the CIIT, half of the records (50.0%, 27/54) fell in the closest interval (0\u0026ndash;200 km), and the remainder were distributed between intermediate (200\u0026ndash;600 km) and distant (\u0026gt;\u0026thinsp;600 km) intervals. For the Maya train, nearly two thirds of records (63.0%, 34/54) were located within 0\u0026ndash;300 km of the rail alignment. In contrast, distances to PAs were more evenly distributed: the largest single group corresponded to sites\u0026thinsp;\u0026le;\u0026thinsp;10 km from a PA (38.9%, 21/54), but a similar number of records occurred at intermediate (10\u0026ndash;40 km) and large (\u0026gt;\u0026thinsp;40 km) distances, indicating that pathogen presence spans both human-dominated and more conserved landscapes.\u003c/p\u003e\n\u003cp\u003eFor \u003cem\u003eT. cruzi\u003c/em\u003e (including TcI; 37 localities), the nearest distance class again dominated for localities and roads. Most records were located very close to human settlements, with 67.6% (25/37) occurring 0\u0026ndash;2 km from the nearest locality, and 86.5% (32/37) within 0\u0026ndash;2 km of the road network; no detections were recorded beyond 5 km from roads. Distances to the CIIT were more evenly divided between the two closest categories, with both the 0\u0026ndash;200 km and 200\u0026ndash;600 km classes concentrating 40.5% of detections (15/37 each), and only a minority of records located at \u0026gt;\u0026thinsp;600 km. For the Maya train, the dominant class was 0\u0026ndash;300 km, which contained 54.1% of records (20/37), while fewer detections occurred at larger distances. Regarding PAs, the highest proportion of presence of \u003cem\u003eT. cruzi\u003c/em\u003e and TcI records was also found in the nearest interval, with 45.9% (17/37) situated\u0026thinsp;\u0026le;\u0026thinsp;10 km from a PA, and the remaining records between 10\u0026ndash;40 km and \u0026gt;\u0026thinsp;40 km. Overall, these results highlight a strong association between \u003cem\u003eT. cruzi\u003c/em\u003e occurrence in species of bats and modified landscapes shaped by localities and road infrastructure, whereas any gradient of association with the CIIT and Maya train becomes less evident at larger spatial scales.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eLeishmania mexicana\u003c/em\u003e (14 localities) exhibited an even more pronounced clustering in the nearest intervals to localities and roads: 92.9% of its presence (13/14) were located 0\u0026ndash;2 km from both the nearest human locality and the road network. For the CIIT, the dominant distance interval was 0\u0026ndash;200 km, which contained 85.7% of records (12/14), with only isolated detections at longer distances. A similar pattern was observed for the Maya train, where 78.6% of records (11/14) fell within 0\u0026ndash;300 km of the interval. In contrast, distances to PAs tended to be longer, with the intermediate interval (10\u0026ndash;40 km) concentrating the highest proportion of presence of \u003cem\u003eL. mexicana\u003c/em\u003e records (42.9%, 6/14), followed by sites located\u0026thinsp;\u0026gt;\u0026thinsp;40 km from a PA. The few detections of \u003cem\u003eTrypanosoma\u003c/em\u003e sp. and \u003cem\u003eT. dionisii\u003c/em\u003e (three in total) also occurred predominantly in the nearest classes to localities and roads, with two thirds of records (2/3) in the 0\u0026ndash;2 km interval for both variables, while most of these points were assigned to the most distant categories relative to the CIIT and PAs. These results indicate that the pathogens \u003cem\u003eT. cruzi\u003c/em\u003e, \u003cem\u003eL. mexicana\u003c/em\u003e and other trypanosomatids are predominantly detected in bat assemblages from landscapes where human infrastructure is present at short distances, whereas their spatial presence relative to the CIIT and Maya train decreased as distance increased from the main project corridors.\u003c/p\u003e\n\u003ch3\u003eSpatial prevalence of pathogens\u003c/h3\u003e\n\u003cp\u003eA total of 14 localities with prevalence estimates of \u003cem\u003eTrypanosoma cruzi\u003c/em\u003e, \u003cem\u003eT. cruzi\u003c/em\u003e TcI, \u003cem\u003eT. dionisii, Trypanosoma\u003c/em\u003e spp., and \u003cem\u003eLeishmania mexicana\u003c/em\u003e in Mexican bats were recorded, with values ranging from 1.4% to 69.5% (median 9.3%). Most of these localities were located very close to human settlements: 11 of 14 records (78.6%) were situated at \u0026le;\u0026thinsp;5 km from the nearest locality. A similar pattern was observed with respect to the road network, where 11 of 14 localities (78.6%) occurred at \u0026le;\u0026thinsp;5 km from a road. In contrast, only three of 14 records (21.4%) were located at \u0026le;\u0026thinsp;5 km from the influence corridor of the CIIT, whereas 11 of 14 (78.6%) occurred at longer distances; these data indicate that most documented localities do not spatially overlap with this infrastructure project. For the Maya train, four of 14 records (28.6%) were located at \u0026le;\u0026thinsp;5 km from the rail alignment (including a recreational center in Campeche and the Keh Poot cenote in Yucat\u0026aacute;n), while the remaining records (71.4%) were located farther away.\u003c/p\u003e\n\u003cp\u003eNotably, more than half of the localities (eight of 14, 57.1%) were located 5 km from a PAs, primarily within the Calakmul Biosphere Reserve, the Selva Lacandona, Los Tuxtlas, and the El Zapotal reserve. This suggests overlap between regions of high conservation value and the circulation of these pathogens. The remaining records corresponded to sites more isolated from localities and roads (such as the Selva Lacandona and Rancho San Francisco in Yucat\u0026aacute;n), where prevalence values can be similarly high. This indicates that risk scenarios are not restricted to strongly anthropogenic modified landscapes but can also emerge in continuous or semi-natural forest matrices (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). Thus, no clear differences were observed in distance patterns by pathogen; instead, a shared pattern emerged of the presence of \u003cem\u003eT. cruzi\u003c/em\u003e, \u003cem\u003eL. mexicana\u003c/em\u003e, and other trypanosomatids in landscapes where human infrastructure (localities, roads) co-occurs with PAs. Given sample size limitations and the fact that several pathogens share the same localities, these results are preliminary and should be strengthened with targeted sampling of pathogen-by-pathogen comparisons.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eZoonotic infectious diseases originate predominantly in wildlife, and their emergence is closely linked to human-induced ecosystem transformations, including deforestation, agricultural expansion, urbanization, and large-scale infrastructure development [\u003cspan additionalcitationids=\"CR49\" citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. In the Anthropocene context, understanding how wildlife populations, their pathogens, and human-modified landscapes are spatially articulated is fundamental for anticipating risk and designing prevention strategies that integrate human, animal, and environment factors using a One Health approach. Our study showed species of bats testing positive to \u003cem\u003eTrypanosoma\u003c/em\u003e spp. and \u003cem\u003eLeishmania mexicana\u003c/em\u003e were strongly clustered near human localities and roads (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e3\u003c/span\u003e), while distances to the CIIT, the Maya train alignment, and PAs spanned broader gradients, highlighting heterogeneous landscapes where infrastructure, forest remnants, and PAs co-occur.\u003c/p\u003e \u003cp\u003eFrom a host perspective, the survey of literature indicated that close to 20% of species of bats nationwide have been examined with evidence of infection by \u003cem\u003eT. cruzi\u003c/em\u003e or \u003cem\u003eL. mexicana\u003c/em\u003e, although this likely underestimates the number of host species [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. More than half of the recorded species belong to Phyllostomidae (15 species, 62.5%) (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). It is likely that since phyllostomids are primarily frugivorous and nectarivorous bats fly at low heights, and are readily captured with mist nets [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e], current evidence is shaped by sampling bias toward species that exploit forest edges, secondary growth, plantations, and peri-urban settings, while high-flying insectivorous bats remain underrepresented [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. Thus, the apparent prominence of phyllostomids as reservoirs may partly reflect trophic ecology, tolerance of disturbed environments, and capture bias rather than intrinsically higher host competence. To address this hypothesis will require expanding sampling in a wide range of habitats including most species of bats, particularly along gradients from conserved forests to strongly human-modified landscapes.\u003c/p\u003e \u003cp\u003ePathogen-specific patterns further support a strong association with human-modified matrices. \u003cem\u003eT. cruzi\u003c/em\u003e (including TcI) was consistently detected near human localities and roads (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e3\u003c/span\u003e), yet it also occurred across the full range of distances to both the CIIT and the Maya train, suggesting persistence under diverse configurations of landscape transformation. \u003cem\u003eLeishmania mexicana\u003c/em\u003e showed an even stronger proximity pattern to localities and roads, with most records falling within the closest distance categories to the CIIT and the Maya train. Although records for \u003cem\u003eT. dionisii\u003c/em\u003e and \u003cem\u003eTrypanosoma\u003c/em\u003e sp. were sparse, they likewise occurred mainly near localities and roads. Overall, the available evidence is consistent with bat\u0026ndash;pathogen interactions occurring within mosaics of secondary vegetation, crops, water bodies, human settlements, and forest remnants (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Supplementary material 1).\u003c/p\u003e \u003cp\u003eThe concentration of records in southeastern Mexico (especially Campeche, Yucat\u0026aacute;n, Chiapas, and Veracruz) support previous studies documenting \u003cem\u003eT. cruzi\u003c/em\u003e and \u003cem\u003eL. mexicana\u003c/em\u003e distributions [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e] and reflects both the ecological significance of the Selva Maya and the extensive habitat transformation into agricultural fields expansion, extensive cattle ranching, and urban and tourism development [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e] Under habitat loss and fragmentation, wildlife frequently shifts toward edges and peri-urban areas, where resources may increase but community diversity declines [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]. The spatial clustering observed appears to align with a human-induced risk, in which sylvatic cycles overlap with human activities, increasing the likelihood of contact among bats, vectors, domestic animals, and humans.\u003c/p\u003e \u003cp\u003eThese patterns also connect to the \u0026ldquo;dilution effect\u0026rdquo; hypothesis, whereby high-diversity habitats can reduce transmission of some pathogens by distributing vector bites and host\u0026ndash;pathogen interactions across multiple, often low-competence hosts [\u003cspan additionalcitationids=\"CR61\" citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]. Conversely, simplified landscapes often favor disturbance-tolerant, opportunistic species that can reach high densities and maintain or amplify pathogen circulation. Several generalist phyllostomid species (\u003cem\u003eArtibeus jamaicensis\u003c/em\u003e, \u003cem\u003eA\u003c/em\u003e. \u003cem\u003elituratus\u003c/em\u003e, \u003cem\u003eCarollia perspicillata\u003c/em\u003e), commonly associated with disturbed habitats and agricultural matrices [\u003cspan additionalcitationids=\"CR64\" citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e], appear repeatedly in records for \u003cem\u003eT. cruzi\u003c/em\u003e and \u003cem\u003eL. mexicana\u003c/em\u003e. However, reservoir quality (infectious competence and transmission to vectors or other hosts) remains poorly characterized in these bats, precluding conclusions about whether they primarily amplify or dilute risk [\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough \u003cem\u003eTrypanosoma\u003c/em\u003e spp. have been evaluated slightly more often than \u003cem\u003eL. mexicana\u003c/em\u003e in species of bats, both are neglected tropical [\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]. Integrating taxonomic evidence (infection records spanning only 20% of species of bats nationwide) with spatial evidence (54 positive localities predominantly near roads and settlements) and socio-environmental context (deforestation, megaprojects, agricultural expansion) underscores that sylvatic, peri-urban, and urban cycles of these parasites should be integrated into further analyses. A One Health agenda should integrate monitoring of wildlife, vectors, and domestic hosts with land-use and forest-cover metrics, infrastructure development, and local socioeconomic conditions [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan additionalcitationids=\"CR69\" citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e] to realistically assess risk, anticipate human-induced landscape changes, and design interventions that protect human health, animal health, and ecosystem integrity.\u003c/p\u003e \u003cp\u003e \u003cem\u003eHuman transformations in the Yucat\u0026aacute;n Peninsula and their relationship to the emergence and re-emergence of zoonoses.\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThe Yucat\u0026aacute;n Peninsula illustrates how recent human-induced environmental changes shapes ecological landscapes facilitating for zoonotic pathogen circulation. Expansion of the agricultural frontier (particularly industrial pig and poultry production and mechanized soybean and maize cultivation) has replaced forest with agro-industrial and peri-urban mosaics and increased roads, highways, and settlements [\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e]. These changes can modify roost and foraging resources, favoring the use of vegetation edges, pastures, and areas near farms and rural communities by multiple bat species, including generalist phyllostomids and \u003cem\u003eDesmodus rotundus\u003c/em\u003e [\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e]. Intensive tourism around cenotes and caves adds chronic disturbance through coastal urbanization, access roads, and direct modification of recreational caves, potentially altering roost use, mobility, and reproductive phenology. Because chronic stress and altered movements can affect pathogen shedding and transmission by changing contact rates within and among colonies and with other hosts, detections of \u003cem\u003eT. cruzi\u003c/em\u003e and \u003cem\u003eL. mexicana\u003c/em\u003e in cenotes and reserves suggest these settings may function as interaction points among wildlife, vectors, domestic animals, and people [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe broader regional context reinforces the need for integrative management. Livestock expansion into formerly forested areas can amplify zoonotic cycles, as illustrated by bovine paralytic rabies associated with \u003cem\u003eD. rotundus\u003c/em\u003e in southeastern Mexico, where increased livestock availability can support persistent or growing hematophagous bat populations with notable economic and health consequences [\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e]. Although this study focuses on \u003cem\u003eTrypanosoma\u003c/em\u003e spp. and \u003cem\u003eL. mexicana\u003c/em\u003e, similar land-use and infrastructure drivers may structure risk for multiple bat-associated pathogens, with distance gradients to localities, roads, and megaprojects serving as indirect indicators of human pressure on bat assemblages and their vectors [\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFrom a One Health perspective, these findings highlight the importance of linking megaproject planning (Maya train, CIIT), land-use regulation, and conservation of the Selva Maya and other southeastern ecosystems with zoonosis surveillance and coordinated management of wildlife and domestic animals. Given the consistent proximity between human localities, the road network, and pathogen-positive bat localities, interventions such as active and passive surveillance, community education, bat roost management, vector control, and strengthening of primary care should be prioritized in human\u0026ndash;wildlife interface landscapes. One challenge is advancing development models that reduce deforestation and fragmentation, sustain ecosystem functionality, and simultaneously decrease opportunities for pathogen spillover into human and domestic ani mal populations. From a sustainability perspective, preventing zoonotic emergence requires integrating biodiversity conservation, infrastructure planning and health surveillance as interdependent components rather than isolated sectors.\u003c/p\u003e\n\u003ch3\u003eImplications for sustainability and One Health\u003c/h3\u003e\n\u003cp\u003eIn this context, these patterns emphasize that bat\u0026ndash;pathogen systems in Mexico are embedded in socio-ecological landscapes where conservation and development agendas intersect. Positive records near roads, localities and megaproject corridors suggest that decisions on transport infrastructure, agricultural expansion and tourism development can inadvertently modulate opportunities for pathogen maintenance and spillover. Conversely, the presence of infections in and around Protected Natural Areas indicates that conservation instruments must explicitly consider disease dynamics, rather than assuming that biodiversity protection automatically reduces risk. Framing these findings within a sustainability lens implies that bat conservation, surveillance of trypanosomatid infections, and territorial planning should be coordinated so that economic development and infrastructure projects do not erode ecosystem services provided by bats nor exacerbate health inequities in rural communities.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn summary, our synthesis shows that infections by \u003cem\u003eT. cruzi\u003c/em\u003e and \u003cem\u003eL. mexicana\u003c/em\u003e in Mexican bats are concentrated in human-modified matrices that also harbor important biodiversity values. Bats are not an intrinsic threat, but their pathogens can become a risk when unsustainable land-use change, poorly regulated infrastructure and inadequate waste management alter ecological and social interfaces [\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e, \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e]. Under a One Health framework, strategies to manage bat-borne zoonoses should prioritize conservation of natural habitats, improvement of housing and livestock management, and rigorous environmental governance of megaprojects, rather than persecution of bats. By linking pathogen data with spatial indicators of human pressure and conservation, this study provides an evidence base to inform more sustainable development pathways in regions where bats, people and pathogens coexist.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding statement.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics, consent to participate, and consent to Publish declarations.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. This study is based exclusively on previously published data and did not involve new data collection from humans or animals.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial registration.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing financial or non-financial interests relevant to the content of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003eM.G.L. and A.R.M. Conceptualization, Methodology, Data curation, Writing- Original draft preparation, Visualization, Investigation, Writing- Original draft preparation. \u0026nbsp; G.G.G. and J.J.F.M. \u0026nbsp;Methodology, Writing- Original draft preparation, Visualization, Investigation, Writing- Original draft preparation. V.S.C. Data curation, Visualization, Investigation, Writing- Original draft preparation. All authors reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank the reviewers whose comments helped improve earlier versions of this manuscript. MG-L (CVU 390032) thanks SECIITI, (before CONAHCYT), and Estancias postdoctorales por México–Mujeres indígenas (2023), academic track, for the postdoctoral fellowship awarded, and SNI for the recognition. MG-L also thanks B. Hernández and J. García for their support in data curation. AR-M also thanks to the biodiversity geography laboratory of the National Biodiversity Pavilion of the Institute of Biology UNAM.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eKunz TH, Braun de Torrez E, Bauer D, Lobova T, Fleming TH. Ecosystem services provided by bats. Ann N Y Acad Sci. 2011;1223(1):1-38.\u003c/li\u003e\n \u003cli\u003eFagre AC, Kading RC. Can bats serve as reservoirs for arboviruses? Viruses. 2019;11(3):215.\u003c/li\u003e\n \u003cli\u003eWang LF, Anderson DE. Viruses in bats and potential spillover to animals and humans. Curr Opin Virol. 2019;34:79-89.\u003c/li\u003e\n \u003cli\u003eCalisher CH, Childs JE, Field HE, Holmes KV, Schountz T. Bats: Important reservoir hosts of emerging viruses. Clin Microbiol Rev. 2006;19(3):531-45. doi: 10.1128/CMR.00017-06.\u003c/li\u003e\n \u003cli\u003eBrook CE, Dobson AP. Bats as \u0026quot;special\u0026quot; reservoirs for emerging zoonotic pathogens. 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J Trop Ecol. 2006;22(2):267-76.\u003c/li\u003e\n \u003cli\u003eKopczynski S, Nolen R, Hala D, Lases-Hern\u0026aacute;ndez F, Escobedo-Hinojosa W, Arcega-Cabrera F, et al. Investigation of Anthropogenic and Emerging Contaminants in Sinkholes (Cenotes) of the Great Mayan Aquifer, Yucat\u0026aacute;n Peninsula. Arch Environ Contam Toxicol. 2025;89(3):279-99. doi: 10.1007/s00244-025-01149-2.\u003c/li\u003e\n \u003cli\u003eAnderson A, Shwiff SA, Gebhardt K, Ram\u0026iacute;rez AJ, Fowler GA, Shwiff SS. Economic evaluation of vampire bat (\u003cem\u003eDesmodus rotundus\u003c/em\u003e) rabies prevention in Mexico. Transbound Emerg Dis. 2012;61(2):140-6.\u003c/li\u003e\n \u003cli\u003eJimenez-Rico MA, Vigueras-Galvan AL, Hernandez-Villegas EN, Martinez-Duque P, Roiz D, Falcon LI, et al. Bat coronavirus surveillance across different habitats in Yucat\u0026aacute;n, M\u0026eacute;xico. Virology. 2025;603:110401.\u003c/li\u003e\n \u003cli\u003eWyman M, Villegas ZG, Ojeda IM. Land-use/Land-cover Change in Yucat\u0026aacute;n State, Mexico: An examination of political, socioeconomic, and biophysical drivers in Peto and Tzucacab. Ethnobot Res Appl. 2007;5:59-66.\u003c/li\u003e\n \u003cli\u003ePlowright RK, Reaser JK, Locke H, Woodley SJ, Patz JA, Becker DJ, et al. Land use-induced spillover: a call to action to safeguard environmental, animal, and human health. Lancet Planet Health. 2021 Apr;5(4):e237-45. doi: 10.1016/S2542-5196(21)00031-0. Epub 2021 Mar 6. PubMed PMID: 33684341; PubMed Central PMCID: PMC7935684. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-sustainability","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"disu","sideBox":"Learn more about [Discover Sustainability](https://www.springer.com/43621)","snPcode":"","submissionUrl":"","title":"Discover Sustainability","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Anthropocene, Chiroptera, Pathogenic protozoa, Leishmaniasis, Zoonoses","lastPublishedDoi":"10.21203/rs.3.rs-8744197/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8744197/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eIntroduction:\u003c/h2\u003e \u003cp\u003e \u003cem\u003eTrypanosoma\u003c/em\u003e spp. and \u003cem\u003eLeishmania mexicana\u003c/em\u003e are protozoan parasites of major public health relevance. Bats can act as hosts or reservoirs, but available evidence for Mexico is fragmented and limited under a One Health framework.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe reviewed publications (2001\u0026ndash;2025) reporting detection of trypanosomatids of the \u003cem\u003eTrypanosoma\u003c/em\u003e spp. and \u003cem\u003eL. mexicana\u003c/em\u003e in wild bats from Mexico. Epidemiological and spatial variables were included. We compiled 54 localities with individuals of bats testing positive of these pathogens, of which 14 provided site-level prevalence. These localities were analyzed in QGIS and related to distances to human settlements, paved roads, the Interoceanic train corridor (CIIT), the Maya train (Tren Maya), and decreed protected areas.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eFourteen studies documented infection in 24 bat species, mostly phyllostomids from southeastern Mexico. Site-level prevalence ranged from 0.6 to 69.5%, with half of the records below 20%. Spatial analysis showed that most detections occurred within 0\u0026ndash;2 km of human settlements and roads, whereas distances to the CIIT and the Maya train spanned the full gradient considered, and positive points tended to cluster within 10\u0026ndash;40 km of a Protected area.\u003c/p\u003e\u003ch2\u003eDiscussion\u003c/h2\u003e \u003cp\u003eCirculation of \u003cem\u003eTrypanosoma\u003c/em\u003e spp. and \u003cem\u003eL. mexicana\u003c/em\u003e in bats is concentrated in landscapes modified by infrastructure and land-use change, suggesting a strong link between human disturbance, host dynamics and zoonotic risk. These patterns highlight the need to integrate bat monitoring, land-use planning and disease surveillance within explicit One Health approach.\u003c/p\u003e","manuscriptTitle":"A systematic review of vector-borne pathogens in bats of Mexico in the Antropocene Vector-borne zoonoses in bats of Mexico","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-04 14:12:36","doi":"10.21203/rs.3.rs-8744197/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-19T12:10:59+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-11T01:02:37+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-10T21:56:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"138381568230665606437229198679245231549","date":"2026-03-09T13:35:06+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-03T16:00:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"200503424860665197909204480795435835918","date":"2026-03-02T10:34:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"3610576938077219421402242100804238834","date":"2026-03-01T19:28:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"204873539921817644167469727081808099544","date":"2026-02-28T20:45:01+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-27T09:39:23+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-14T04:42:58+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-14T01:49:52+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Sustainability","date":"2026-02-14T01:42:57+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-sustainability","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"disu","sideBox":"Learn more about [Discover Sustainability](https://www.springer.com/43621)","snPcode":"","submissionUrl":"","title":"Discover Sustainability","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"65252fe3-1b90-4ebe-94f9-fbc2339f7068","owner":[],"postedDate":"March 4th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-19T07:41:29+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-04 14:12:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8744197","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8744197","identity":"rs-8744197","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}