Mosquito-based xenosurveillance reveals circulation of Anaplasma and Neoehrlichia in livestock at a human–wildlife interface in Kenya

Mosquito-based xenosurveillance reveals circulation of Anaplasma and Neoehrlichia in livestock at a human–wildlife interface in Kenya | 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 Research Article Mosquito-based xenosurveillance reveals circulation of Anaplasma and Neoehrlichia in livestock at a human–wildlife interface in Kenya Dennis Getange, Samson Mukaratirwa, Oscar Esibi, Epaphrus Yuko, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9010968/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 9 You are reading this latest preprint version Abstract Background Hematophagous flies can serve as sentinels for detecting vertebrate pathogens or host antibodies present in the blood they ingest. Xenosurveillance, which uses blood-feeding insects as biological samplers, is emerging as a sensitive and minimally invasive approach for monitoring pathogens circulating among humans, livestock, and wildlife. However, despite its growing application in human health, the use of xenosurveillance for detecting pathogens in livestock systems, particularly within complex human–animal–wildlife interfaces, remains underexplored. To date, few studies have assessed whether mosquito blood-meals can reliably capture livestock-associated bacterial pathogens. Our study investigated whether blood-meals from mosquitoes could be used to detect infectious agents circulating in livestock in Kenya. Methods We collected a total of 4,673 mosquitoes, belonging to Culex , Anopheles , Aedes , Mansonia , and Coquillettidia genera around livestock enclosures in Kajiado and Naivasha counties, Kenya. Blood-fed mosquitoes were examined for the presence of Anaplasma , Ehrlichia , Rickettsia, Theileria , and Babesia pathogens using molecular tools and gene sequencing. Results Overall, we detected Anaplasma marginale in Culex pipiens (1/150; 0.7%) and Aedes hirsutus (2/11; 18.2%), Anaplasma sp. in Cx. pipiens (2/150; 1.4%) and Ae. hirsutus (1/11; 9.1%), and Candidatus Neoehrlichia mikurensis was found only in Mansonia africana (2/50; 4%). Pathogen detections showed strong host concordance where A. marginale was associated with cattle-derived blood-meals and Anaplasma sp. with goat-derived blood-meals, while Candidatus Neoehrlichia mikurensis was detected in Mansonia africana that had fed on cattle and on a host that could not be determined due to amplification failure. Conclusions Candidatus Neoehrlichia mikurensis is a recognized zoonotic pathogen, and detection represents the first report of its presence in mosquitoes in Africa. Although mosquitoes are not biological vectors of these pathogens, the presence of pathogen DNA in their blood-meals reveals circulation of the pathogens in livestock in Kenya. Our findings demonstrate that mosquito-based xenosurveillance offers a simple, scalable, and non-invasive method for detecting circulating vector-borne pathogens in livestock-human-wildlife ecosystems, supporting its value as an emerging tool for integrated biosurveillance. Xenosurveillance mosquitoes tick-borne pathogens vector-borne pathogens Anaplasma spp. Neoehrlichia Candidatus Neoehrlichia mikurensis Figures Figure 1 Figure 2 Figure 3 Background Over the recent years, the emergence and re-emergence of vector-borne infectious diseases have increased significantly resulting in substantial global economic and public health burdens [ 1 ]. This trend is driven largely by ecological, demographic, and climatic shifts that increase interactions among humans, livestock, and wildlife [ 2 , 3 ]. An estimated 60% of emerging infectious diseases are zoonotic, and more than two-thirds of these originate in wildlife reservoirs [ 4 , 3 ]. Although viral pathogens constitute a major proportion of these threats, bacterial and protozoan zoonoses, particularly those transmitted by arthropod vectors, remain critically important to both veterinary and human health [ 5 ]. Species within the Anaplasma , Ehrlichia , Rickettsia , Babesia , and Theileria genera circulate in complex enzootic cycles involving domestic animals, wildlife, and hematophagous arthropods [ 6 – 8 ]. These pathogens can cause debilitating diseases such as anaplasmosis, ehrlichiosis, and theileriosis, leading to significant livestock morbidity and economic losses across tropical and subtropical regions [ 8 ]. Therefore, the development of innovative surveillance tools capable of detecting diverse vector-borne pathogens is essential for strengthening early warning systems and improving integrated disease control. While ticks remain the primary vectors of many bacterial pathogens affecting livestock, growing evidence indicates that non-tick hematophagous arthropods, including mosquitoes, Hippoboscids, biting midges, and stable flies, can occasionally harbour pathogen DNA acquired through blood-meals from infected hosts [ 9 – 11 ]. This has renewed interest in their potential roles in mechanical transmission and in xenosurveillance-based pathogen monitoring. Notably, recent experimental work demonstrated that the camel-specific ked Hippobosca camelina can transmit Candidatus Anaplasma camelii to laboratory mice, indicating the potential role of non-tick blood-feeding flies in the ecology of Anaplasma spp. transmission [ 12 ]. Although mosquitoes are not biological vectors for these bacteria, their ability to carry detectable pathogen DNA offers opportunities for pathogen monitoring through molecular surveillance approaches. Moreover, mosquitoes already serve as major vectors of diverse protozoan, viral, and filarial pathogens affecting humans, livestock, and wildlife [ 13 , 14 ], highlighting their global epidemiological importance. Understanding cross-vector interactions at livestock–vector interfaces is therefore essential for unravelling the complex ecological networks that shape pathogen transmission in agro-ecological systems. Use of blood-feeding arthropods as "biological syringes" for detecting vertebrate pathogens, termed xenosurveillance or invertebrate-derived DNA (iDNA) screening, has achieved considerable momentum in recent years [ 15 ]. This non-invasive method is based on the analysis of host selection and host preferences of hematophagous arthropods, achieved through the molecular identification of their blood-meals [ 16 ]. By capitalising on the broad feeding ranges of mosquitoes and other hematophagous taxa, xenosurveillance enables these insects to serve as natural samplers of vertebrate communities, particularly in regions where conventional wildlife or livestock sampling is logistically difficult [ 15 , 17 ]. The approach has been successfully applied to detect a wide range of pathogens, including arboviruses, malaria parasites, filarial nematodes, and non–vector-borne agents such as influenza virus and Epstein–Barr virus from mosquito blood meals [ 15 , 18 – 20 ], demonstrating its versatility for broad-scale pathogen surveillance across human, livestock, and wildlife interfaces. Insights derived from these vector-host-pathogen profiles are critical for guiding disease-control strategies [ 21 ] and position xenosurveillance as a powerful component of integrated One Health surveillance systems. Although most research on mosquito-associated pathogens has focused on arboviruses and protozoa such as Plasmodium spp., increasing attention is being directed toward the detection of tick-borne bacterial pathogens in mosquitoes as part of integrated biosurveillance efforts [ 22 ]. Recent molecular studies have identified Rickettsia DNA in blood-fed mosquitoes, suggesting that these insects may acquire tick-borne bacteria incidentally during blood feeding and could potentially act as mechanical carriers [ 23 , 24 ]. While these detections do not imply biological transmission, they highlight the value of mosquitoes as passive sentinels for identifying areas of elevated pathogen circulation in livestock systems. In this study, we collected mosquitoes around cattle enclosures at night to investigate their potential role in the epidemiology and surveillance of tick-borne pathogens. Specifically, we evaluated whether mosquito-derived blood-meals can reveal the presence and distribution of Anaplasmataceae in livestock-dominated environments. Methods Study area and mosquito collection The study was conducted in two livestock-wildlife interface regions of Kenya as part of a study by Getange et al. [ 7 ]: Amboseli in Kajiado County and Naivasha in Nakuru County (Fig. 1 ). Amboseli is an arid to semi-arid ecosystem characterized by open savannah, seasonal wetlands, and dispersed Maasai pastoralist settlements. It supports high densities of domestic livestock, primarily cattle ( Bos indicus ), goats ( Capra hircus ), and sheep ( Ovis aries ), alongside free-ranging wildlife such as African buffalo ( Syncerus caffer ), elephants ( Loxodonta africana ), zebra ( Equus quagga ), giraffe ( Giraffa spp.), and multiple antelope species. The close spatial overlap of these host communities facilitates the circulation of diverse vector-borne pathogens [ 25 ]. Naivasha, in contrast, is a sub-humid agro-ecological zone with mixed livestock production, horticultural farming, and abundant wildlife associated with the Lake Naivasha ecosystem [ 26 ]. Both sites experience bimodal rainfall patterns, with mosquito populations typically increasing during the long and short rainy seasons. Mosquitoes were collected around cattle enclosures overnight (6:00pm − 6:00am) using Centres for Disease Control and Prevention (CDC) miniature light traps (Model 512, John Hock Co., Gainesville, Florida, USA) baited with carbonated dry ice (CO 2 ) during the long rainy season in April 2024, a period associated with increased vector activity. Traps were suspended approximately 1.5 m above ground level and positioned 5 m from cattle enclosures to maximize the capture of host-seeking mosquitoes. Traps operated continuously overnight and were retrieved the following morning. Mosquito samples were linked to the collection sites by geo-coding using a GPS. Captured mosquitoes were temporarily immobilized using triethylamine and transported in liquid nitrogen to International Centre of Insect Physiology and Ecology ( icipe ) Martin Lüscher Emerging Infectious Diseases (ML-EID) Laboratory in Nairobi for identification and further molecular analysis. Mosquito morphological identification Mosquitoes were identified morphologically to species level under a stereomicroscope using established taxonomic keys, including Edwards [ 27 ], Harbach [ 28 ], and Huang and Ward [ 29 ]. Following identification, specimens were pooled into groups of 1–25 individuals based on species, sex, collection site, and collection date. Blood-fed mosquitoes were processed individually and treated as pools of size 1, a deliberate decision consistent with the study’s primary objective of detecting and characterizing tick-borne bacterial pathogens from bloodmeal-derived DNA. Mosquitoes of the same species were placed in sterile 1.5 mL microcentrifuge tubes (303 pools in total) and stored at -80°C until further molecular processing. DNA extraction of mosquito pools and individuals Mosquito pools and individual mosquitoes were homogenized prior to DNA extraction to ensure thorough disruption of tissues. Specimens were not surface-sterilised prior to homogenization, as the primary objective was to detect pathogen DNA acquired through blood feeding rather than to establish vector competence. Each pool was placed in a 1.5-mL microcentrifuge tube containing five 2.0-mm zirconia/yttria-stabilized beads (BioSpec, USA) and mechanically disrupted using a Mini Bead Beater 16 (BioSpec, Bartlesville, USA) for approximately 30 seconds at ~ 3,450 rpm. Following homogenization, genomic DNA was extracted using the Isolate II Genomic DNA Kit (Bioline, UK) according to the manufacturer’s instructions. Extracted DNA from each pool was stored at -20°C until PCR screening. Mosquito blood-meal source identification All blood-fed mosquito samples were individually analysed to determine the vertebrate host origin of the blood. Host identification was performed using PCR amplification of vertebrate mitochondrial markers, specifically cytochrome b (cyt b ) and 16S rRNA (vert16S), which have been shown to reliably differentiate a wide range of vertebrate taxa [ 30 ]. For each specimen, 1 µL of extracted nucleic acid served as template in a 10 µL reaction mixture containing 2 µL of 5× HOT FIREPol® EvaGreen® qPCR Mix (Solis BioDyne, Estonia) and 10 pmol of each primer. PCR amplification and high-resolution melting (HRM) analysis were conducted on a MIC PCR Cycler (BioMolecular Systems, Upper Coomera, Queensland, Australia) following previously optimized protocols [ 31 ]. DNA from known vertebrate hosts, including human, cattle, sheep, goat, elephant, and chicken, was included in each run as positive controls to support interpretation of melting profiles. Nuclease-free water was included as a non-template control in each assay to monitor for potential reagent contamination. Representative amplicons exhibiting distinct HRM profiles consistent with our positive controls were purified using an Exo-rSAP enzymatic cleanup (New England Biolabs, UK), and outsourced to Macrogen Europe (The Netherlands) for Sanger sequencing to confirm host identity. Screening of mosquito pools for Anaplasma , Ehrlichia, Rickettsia , Theileria and Babesia All mosquito DNA samples were screened for Anaplasma , Ehrlichia , Rickettsia , Theileria , and Babesia using PCR-high-resolution melting (HRM) analysis performed on a Mic PCR Cycler (BioMolecular Systems, Upper Coomera, Queensland, Australia). Screening was conducted using previously published primer sets (Table 1 ), following the PCR-HRM protocol described by Mwamuye et al. [ 32 ] and Getange et al. [ 6 , 7 ]. Primer pairs included those amplifying fragments of the 16S rRNA gene for Anaplasma spp. (AnaplasmaJVF/JVR) and Ehrlichia spp. (Ehrlichia16S F/R), and the Rickettsia spp. 16S rRNA gene (Rick16SF/R). In addition, the 18S rRNA gene of Theileria and Babesia spp. was amplified using RLB F/R primers. Each 10-µL HRM reaction consisted of 0.5 µL of each primer (10 pmol/µL), 2 µL of FIREPol® EvaGreen® HRM Master Mix (Solis BioDyne, Tartu, Estonia), 1 µL genomic DNA, and nuclease-free water to final volume. PCR cycling and HRM conditions followed previously described protocol [ 6 , 32 ]. Table 1 Primers used for blood-meal analysis and molecular detection of TBPs in mosquito pools Primer name Gene target Target size (bp) Sequence (5’–3’) Reference Cytb F Cytb R Vertebrate cyt b CCCCTCAGAATGATATTTGTCCTCA CATCCAACATCTCAGCATGATGAAA [ 33 ] Vert16S F Vert16S R Vertebrate 16S 250 GAGAAGACCCTRTGGARCTT CGCTGTTATCCCTAGGGTA [ 30 ] Rick-F Rick-R Rickettsia 16S rRNA 364 GAACGCTATCGGTATGCTTAACACA CATCACTCACTCGGTATTGCTGGA [ 34 ] 120–2788 120–3599 Rickettsia ompB 856 AAACAATAATCAAGGTACTGT TACTTCCGGTTACAGCAAAGT [ 35 ] Ehrlichia 16S F Ehrlichia 16SR Ehrlichia 16S rRNA 200 CGTAAAGGGCACGTAGGTGGACTA CACCTCAGTGTCAGTATCGAACCA [ 36 ] PER1 PER2 Ehrlichia 16S rRNA 451 TTTATCGCTATTAGATGAGCCTATG CTCTACACTAGGAATTCCGCTAT [ 37 ] EHR16SD 1492R Anaplasma / Ehrlichia 16S rRNA 1030 GGTACCYACAGAAGAAGTCC GGTTACCTTGTTACGACTT [ 38 , 39 ] Anaplasma JF Anaplasma JR Anaplasma 16S rRNA 300 CGGTGGAGCATGTGGTTTAATTC CGRCGTTGCAACCTATTGTAGTC [ 32 ] RLB F RLB R Theileria / Babesia 18S rRNA 460–520 GAGGTAGTGACAAGAAATAACAATA TCTTCGATCCCCTAACTTTC [ 40 ] Samples with distinct HRM profiles were subjected to confirmatory PCR assays using EHR16SD–1492R primer pair for Anaplasma spp., and PER1–PER2 primers for Ehrlichia spp. (Table 1 ). These reactions were performed on a ProFlex PCR System (Applied Biosystems, Foster City, CA, USA) in a total volume of 15 µL, comprising 3 µL of 5× HOT FIREPol® Blend Master Mix (Solis BioDyne, Tartu, Estonia), 1.5 µL of template DNA, and 0.75 µL each of forward and reverse primers (10 pmol/µL). Thermocycling conditions followed previously published protocols [ 37 – 39 ]. Amplification success was assessed by electrophoresing 5 µL of PCR products on a 2% agarose gel pre-stained with ethidium bromide, followed by visualization under UV illumination. Remaining PCR products were purified using ExoSAP (New England Biolabs, UK) according to the manufacturer’s guidelines. Purified amplicons were then submitted to Macrogen Europe (The Netherlands) for Sanger sequencing. Phylogenetic and bioinformatic analyses Forward and reverse sequence chromatograms obtained through Sanger sequencing were inspected, edited, and assembled into high-quality consensus sequences using Geneious Prime v2024.0.7 [ 41 ]. Consensus sequences were compared against publicly available reference sequences in the NCBI database ( http://www.ncbi.nlm.nih.gov ) through BLASTn searches [ 42 ] to verify taxonomic identities and assess similarity to known pathogen reference sequences. For evolutionary inference, multiple sequence alignments were generated using MAFFT, after which maximum-likelihood phylogenetic trees were reconstructed in PhyML v3.0 [ 43 ]. The optimal nucleotide substitution model for each dataset was selected automatically using the Akaike Information Criterion [ 44 ]. Resulting phylogenies were visualized and annotated in FigTree v1.4.4 [ 45 ]. Pathogen detection frequencies were expressed as the proportion of positive mosquito pools relative to the total number of pools screened for each pathogen group. In addition, minimum infection rates (MIR) were calculated as the number of positive pools divided by the total number of individual mosquitoes tested per species, multiplied by 1,000, to enable standardised comparison across species with different pool sizes. Results Morphological identification of mosquitoes A total of 4,673 mosquitoes (303 pools) representing five genera ( Aedes , Anopheles , Culex , Mansonia , and Coquillettidia ), were collected in Amboseli (n = 546) and Naivasha (n = 4,127) (Table 2 ). Overall, Culex was the dominant genus, accounting for 74.3% (n = 3,473) of all collected mosquitoes, followed by Mansonia at 23.5% (n = 1,100). In contrast, Aedes and Anopheles were comparatively less abundant, contributing 1.5% (n = 70) and 0.4% (n = 19) of the total catch, respectively, while Coquillettidia aurites represented 0.24% (n = 11). At the species level, the most abundant mosquitoes were Culex pipiens ( n = 3,220; 68.9%), followed by Mansonia africana ( n = 976; 19.6%), and Culex vansomereni ( n = 126; 2.7%). These three species collectively constituted over 92.5% of the entire mosquito collection. Naivasha collections were dominated by Culex pipiens (n = 2,837; 68.7%), followed by Mn. africana (n = 942; 22.8%) and Cx. vansomereni (n = 126; 3.1%). In contrast, Amboseli was dominated by Cx. pipiens (n = 383; 70.1%), followed by Cx. univittatus (n = 90; 16.5%) and Mn. africana (n = 34; 6.2%). Table 2 Summary of mosquito species trapped at the sampling sites in Kajiado and Naivasha counties of Kenya Genus Amboseli Naivasha Total Species Pools F M F M Aedes Ae. aegypti 1 2 2 Ae. hirsutus 11 18 29 47 Ae. mcintoshi 11 10 5 15 Ae. tarsalis 2 3 3 Ae. tricholabis 2 3 3 Anopheles An. coustani 2 3 3 An. funestus 3 1 2 3 An. gambiae 1 1 1 An. pharoensis 6 9 3 12 Coquillettidia Cq. aurites 4 10 1 11 Culex Cx. annulirostris 2 3 3 Cx. bitaeniorhynchus 1 1 1 Cx. cinereus 1 1 1 Cx. pipiens 150 366 17 2827 10 3220 Cx. poicilipes 3 1 3 4 Cx. tigripes 1 1 1 Cx. univittatus 16 90 15 105 Cx. vansomereni 11 124 2 126 Cx. zombaensis 2 12 12 Mansonia Mn. africana 50 34 877 65 976 Mn. uniformis 23 4 2 83 35 124 Total 303 527 19 4011 116 4673 Mosquito blood-meal analysis Fifty-six mosquitoes that were visibly blood-fed representing eight species across four genera ( Culex, Aedes, Anopheles and Mansonia ) were analysed for vertebrate blood-meal sources using cytochrome b sequencing. Vertebrate host DNA was successfully identified in 43 mosquitoes, representing a 76.8% success rate (n = 56). The detected vertebrate hosts included humans ( Homo sapiens ), cattle ( Bos taurus ), goats ( Capra hircus ), sheep ( Ovis aries ), hippopotamus ( Hippopotamus amphibius ), dog ( Canis familiaris ), and wildebeest ( Connochaetes taurinus ) (Fig. 2 ), while the remaining 13 samples failed to amplify with any of the vertebrate primers used, likely due to advanced blood-meal digestion, low DNA quantity, or host species falling outside the primer amplification range. Overall, human (23.2%, n = 13) was the most frequently detected vertebrate blood-meal source, followed closely by cattle (19.6%, n = 11), goats (17.9%, n = 10), and sheep (7.1%, n = 4). Wildlife-derived blood-meals were less common and included Hippopotamus (5.4%, n = 3) and wildebeest (1.9%, n = 1), while dog blood was detected in a single sample (1.9%, n = 1). Culex species, particularly Cx. pipiens and Cx. univittatus , showed the greatest diversity of host use and accounted for most livestock- and human-derived blood-meals, whereas Mansonia and Aedes species contributed mainly to wildlife- and mixed-interface feeding patterns. In Nakuru, goats were the primary host (n = 9), while in Kajiado, cattle were the most frequent source of blood-meals (n = 9) (Table 3 ). Table 3 Distribution of vertebrate blood-meal sources among blood-fed mosquito species collected in Nakuru and Kajiado counties of Kenya County Mosquito Species n Human Cattle Goat Sheep Hippo Wildebeest Dog Unknown Nakuru Aedes hirsutus 3 0 0 1 0 1 0 0 1 Aedes mcintoshi 1 0 1 0 0 0 0 0 0 Aedes tricholabis 2 0 0 0 0 0 0 0 2 Aedes trisatus 1 0 0 1 0 0 0 0 0 Anopheles funestus 1 0 0 1 0 0 0 0 0 Anopheles pharoensis 4 0 0 0 2 0 0 0 2 Culex annulirostris 1 0 0 0 0 0 0 0 1 Culex pipiens 9 1 1 5 0 1 0 0 1 Culex poicilipes 2 2 0 0 0 0 0 0 0 Culex univittatus 1 1 0 0 0 0 0 0 0 Culex vansomereni 3 1 0 0 0 0 0 0 2 Mansonia uniformis 6 3 0 1 1 1 0 0 0 Nakuru Total 34 8 (23.5%) 2 (5.9%) 9 (26.5%) 3 (8.8%) 3 (8.8%) 0 (0%) 0 (0%) 9 (26.5%) Kajiado Aedes hirsutus 3 0 2 0 0 0 1 0 0 Culex cinereus 1 0 0 0 0 0 0 0 1 Culex pipiens 9 3 3 1 1 0 0 0 1 Culex univittatus 5 1 2 0 0 0 0 1 1 Mansonia africana 4 1 2 0 0 0 0 0 1 Kajiado Total 22 5 (22.7%) 9 (40.9%) 1 (4.5%) 1 (4.5%) 0 (0%) 1 (4.5%) 1 (4.5%) 4 (18.2%) Pathogen detection in mosquito pools Screening of mosquito pools for tick-borne pathogens revealed low but notable detection of Anaplasma and Neoehrlichia spp. in mosquito species from Kajiado County, and none from Naivasha County. Culex pipiens had the highest diversity of detections, with Anaplasma marginale identified in 1/150 pools (0.7%; MIR = 0.31) and an unclassified Anaplasma sp. (2/150; 1.4%; MIR = 0.62). In contrast, Aedes hirsutus showed comparatively higher pool positivity rates, with A. marginale (2/11; 18.2%; MIR = 42.55) and Anaplasma sp. (1/11; 9.1%; MIR = 21.28). Phylogenetic analysis based on partial 16S rRNA gene sequences showed that A. marginale sequences generated in this study clustered closely with reference sequences from Kenya (PV133719; 99.89%) and Uganda (KU686780; 99.79%). Similarly, Anaplasma sp. sequences aligned with reference sequences from South Africa (OQ909493; 99.44%) and Zambia (LC558313; 99.55%) (Fig. 3 ). Notably, Mn. africana was exclusively positive for Candidatus Neoehrlichia mikurensis (2/50; 4%), marking the only occurrence of this emerging pathogen within the mosquito collection (Table 4 ). Sequences identified as Ca. Neoehrlichia mikurensis clustered with reference sequences from China (GU227699; 98.1% and JQ359050; 98.1%), supporting their taxonomic assignment (Fig. 3 ). We did not detect any Rickettsia , Theileria , or Babesia DNA in this study. Table 4 Pooled positivity rates and minimum infection rates (MIR) of pathogens detected in mosquito pools from Naivasha and Kajiado counties of Kenya Pathogen detected (No. of pools) Positive pools Pool positivity (%) 95% CI (Lower - Upper) MIR (per 1,000) Culex pipiens (n = 150) Anaplasma marginale 1 0.67% 0.017% – 3.66% 0.31 Anaplasma sp. 2 1.33% 0.16% – 4.73% 0.62 Aedes hirsutus (n = 11) Anaplasma marginale 2 18.18% 2.28% – 51.78% 42.55 Anaplasma sp. 1 9.09% 0.23% – 41.28% 21.28 Mansonia africana (n = 50) Candidatus Neoehrlichia mikurensis 2 4.00% 0.49% – 13.71% 2.05 Tick-borne pathogen–positive mosquito pools were identified in three mosquito species, and their associated blood-meal sources were determined by cytochrome b analysis (Tables 3 and 5 ). Anaplasma marginale and Anaplasma sp. were detected in Cx. pipiens and Ae. hirsutus , whereas Ca. Neoehrlichia mikurensis was detected in Mn. africana . In Cx. pipiens , Anaplasma sp. was identified in two pools that had fed on goats, and A. marginale was detected in one pool with an undetermined blood-meal source, with sequence identities of 99.7–99.9% and amplicon lengths ranging from 660 to 952 bp. In Ae. hirsutus , A. marginale was detected in two pools that had fed on cattle, while Anaplasma sp. was detected in one pool with a goat-derived blood-meal, with sequence identities of 99.4–100% and fragment lengths of 391–917 bp. Candidatus Neoehrlichia mikurensis was detected in two Mn. africana pools, one associated with a cattle blood-meal and one with an unidentified host, showing 98.1% sequence identity over 372–377 bp. Overall, the detected tick-borne pathogens (TBPs) were associated primarily with livestock-derived blood-meals, particularly cattle and goats, with sequence identity values ≥ 98.1%, confirming the presence of Anaplasmataceae DNA in mosquito blood-meals. Table 5 Description of tick-borne pathogen-positive mosquito samples from Kajiado County, Kenya Sample ID Mosquito species Bloodmeal source Pathogen identity (%) Sequence Length(bp) GenBank accession MSQ278 Culex pipiens Unknown Anaplasma marginale 99.7 660 PZ069361 MSQ137 Aedes hirsutus Cattle Anaplasma marginale. 99.9 952 PZ069362 MSQ297 Aedes hirsutus Cattle Anaplasma marginale. 99.8 947 PZ069363 MSQ120 Culex pipiens Goat Anaplasma sp. 99.5 917 PZ069364 MSQ163 Culex pipiens Goat Anaplasma sp. 99.4 910 PZ069365 MSQ273 Aedes hirsutus Goat Anaplasma sp. 100 391 PZ069366 MSQ201 Mansonia africana Cattle Candidatus Neoehrlichia mikurensis 98.1 377 PZ069367 MSQ207 Mansonia africana Unknown Ca. Neoehrlichia mikurensis 98.1 372 PZ069368 Discussion Here, we investigated the feasibility of using blood-feeding mosquitoes, for the surveillance of pathogens in livestock at a human–wildlife interface. We detected A. marginale , an unclassified Anaplasma sp., and to our knowledge for the first time, Ca. Neoehrlichia mikurensis in mosquito pools collected around cattle enclosures in Kajiado and Naivasha counties of Kenya. The findings provide evidence that mosquitoes in livestock-dense ecosystems may acquire and indirectly reflect the circulation of bacterial pathogens traditionally associated with tick vectors. Although mosquitoes are not recognized as biological vectors of these bacteria, our results are consistent with previous field studies demonstrating the presence of tick-borne bacterial DNA in field-collected mosquitoes [ 24 , 46 ]. Collectively, these observations support the concept that mosquitoes can function as ecological sentinels of vertebrate infections in pastoral landscapes. Our findings add to a growing body of literature indicating that blood-feeding arthropods, including mosquitoes and other hematophagous insects, may serve as valuable, non-invasive tools for monitoring pathogen circulation in animal populations [ 47 , 48 ]. Interestingly, all pathogen detections in this study originated exclusively from Kajiado County, despite Naivasha contributing 88% of the total mosquito collection (4,127 of 4,673 specimens). Possible explanations include mosquito species composition differed between sites, with livestock-feeding species potentially more abundant in Kajiado's pastoral landscape, increasing the probability of bloodmeal acquisition from tick-infested hosts. Given that tick-borne pathogen DNA in mosquitoes represents bloodmeal content rather than vector infection, variation in livestock management practices that may influence tick burdens and pathogen exposure may also contribute [ 49 ]. Additionally, the distinct agro-ecological characteristics of Naivasha, a sub-humid zone with mixed farming [ 26 ], versus the arid pastoral landscape of Amboseli [ 25 ] may influence vector–host–pathogen dynamics. Future studies with balanced sampling designs across sites would help clarify whether this pattern reflects genuine spatial variation in pathogen circulation. Our study detected A. marginale in Cx. pipiens that fed on unknown host and Ae. hirsutus that fed on cattle, suggesting exposure of livestock to this pathogen, and that mosquito blood-meals can reflect host infection patterns. Circulation of A. marginale in the region was further supported by parallel findings from a complementary study that molecularly confirmed presence of the pathogen in cattle blood samples collected from same cattle enclosures as mosquitoes in this study using direct host-based diagnostics [ 7 ], though the infection rates were higher in blood (24.6%) than mosquitoes (1.9%). All A. marginale positive mosquitoes were detected in enclosures that contained A. marginale -positive cattle. The agreement between pathogen detection in mosquito blood-meals and cattle blood [ 7 ] provides clear empirical evidence that mosquito-based xenosurveillance can reliably reflect livestock infection status. This finding is noteworthy given the pathogen’s well-established role in bovine anaplasmosis and its economic impact across sub-Saharan Africa [ 50 ]. Transmission of A. marginale is primarily attributed to ixodid ticks and, secondarily, to mechanical transfer by biting flies [ 11 , 12 ]; however, previous studies have demonstrated that various hematophagous insects may transiently harbour Anaplasma DNA following blood feeding [ 51 ]. Experimental studies using mosquito cell lines have shown that Anaplasma and Rickettsia species can be maintained under laboratory conditions; however, this does not imply biological transmission by mosquitoes in nature [ 52 , 53 ]. Furthermore, the detection of Anaplasma DNA in the midguts of field-collected Anopheles in China, as well as in diverse mosquito species across multiple provinces, reinforces the role of these insects as effective ecological sentinels rather than biological vectors [ 46 , 51 ]. Similarly, the discovery of unclassified Anaplasma sp. in a mosquito that fed on goat mirrors previous findings of un-characterized Anaplasma diversity in livestock in Kenya [ 7 , 54 ], expanding the scope of known circulation and suggesting broad ecological reservoirs. Host–pathogen associations observed in this study were highly consistent: A. marginale detections in Ae. hirsutus were from cattle-fed individuals, while Anaplasma sp. was exclusively associated with goat-derived blood-meals in both Cx. pipiens and Ae. hirsutus . This concordance between pathogen identity and expected vertebrate host strengthens the biological plausibility of the xenosurveillance detections and suggests that mosquito blood-meals accurately capture host-specific infection patterns. We detected Ca. Neoehrlichia mikurensis, a bacterium first described as a human pathogen in Sweden in 2010 [ 55 ], exclusively in Mn. africana that fed on cattle and unknown host, representing the first report of this pathogen in mosquitoes in Africa. While Ca. Neoehrlichia mikurensis is traditionally considered a tick-borne pathogen transmitted primarily by Ixodes species in Europe and Asia, detection in mosquitoes has been previously reported. Guo et al. [ 46 ] identified Ca. Neoehrlichia mikurensis DNA in multiple mosquito species across all life stages, eggs, larvae, pupae, and adults, in China, suggesting that mosquitoes may acquire this bacterium through environmental exposure or bloodmeals from infected vertebrate hosts. Previous studies have documented Ca. Neoehrlichia mikurensis in rodents [ 56 , 57 ], bovine blood [ 58 ], ticks in Africa [ 59 ] and Europe [ 60 ], and humans across multiple European countries [ 55 , 61 – 66 ]. Given that Mn. africana readily feeds on both livestock and humans in peri-agricultural settings, our detection suggests that mosquitoes may serve as environmental sentinels, providing a non-invasive reflection of local pathogen circulation. Our blood-meal data show that Mn. africana in Kajiado also fed on humans, raising the possibility that this mosquito species bridges livestock and human populations in settings where Ca. Neoehrlichia mikurensis circulates. While this does not constitute evidence of transmission, it highlights the One Health relevance of these findings and underscores the need for targeted screening of at-risk human populations in areas of documented pathogen circulation. However, important knowledge gaps remain. Capacity of Ca. Neoehrlichia mikurensis to survive or replicate within mosquito tissues has not been assessed, and the potential for mechanical transmission has not been evaluated. Additionally, the contribution of wildlife or rodent reservoirs in Kenyan agro-pastoral landscapes remains unknown. Future research should therefore focus on (i) tracing Ca. Neoehrlichia mikurensis in livestock, rodents, and ticks around sampling sites, (ii) experimentally testing bacterial viability and persistence in mosquito tissues, including salivary glands, and (iii) determining whether mosquito-derived detections reflect genuine exposure or incidental carriage. However, we did not detect Rickettsia , Theileria , or Babesia DNA in any mosquito pool, despite screening all 303 pools with validated primer sets. The absence of Rickettsia is consistent with the low prevalence of rickettsial agents reported in livestock in the study region. The failure to detect Theileria and Babesia , despite their documented prevalence in cattle in the same study area [ 7 ], may reflect inherent limitations of xenosurveillance for intracellular parasites that sequester in erythrocytes and maintain relatively low circulating DNA loads in peripheral blood. This observation suggests that mosquito-based xenosurveillance may be better suited for detecting bacterial pathogens with higher bacteraemia levels than for apicomplexan haemoparasites and highlights the need to consider pathogen biology when evaluating the sensitivity of this approach. Our findings support the growing recognition of mosquitoes as “flying syringes” or biological samplers capable of capturing vertebrate pathogen profiles without implying vector competence. Previous studies have reported presence of pathogen nucleic acid in mosquito midgut days after feeding [ 15 , 67 ], highlighting the possibility of exploiting this retention period for molecular detection of pathogens. Our findings are consistent with xenosurveillance approaches using other hematophagous insects that have revealed cryptic infection reservoirs across wildlife and livestock populations [ 9 , 11 , 15 , 20 , 68 , 69 ]. Therefore, our data reflect environmental circulation rather than biological transmission, demonstrating that mosquitoes can function as scalable, cost-efficient biosamplers, particularly where direct host sampling is difficult, ethically constrained, or expensive. Future laboratory studies should quantify factors affecting detection, such as the decay kinetics of pathogen nucleic acids in the mosquito gut, the time interval between feeding and sample processing, and the pathogen load in the host at the time of feeding, to refine detection probabilities and optimize sampling designs. However, several limitations should be considered when interpreting these findings. Detection of bacterial DNA in mosquitoes reflects recent blood feeding on infected hosts and does not indicate pathogen viability, replication, or transmission potential. Therefore, results from this study should be interpreted strictly within a xenosurveillance framework. The use of pooled samples and variability in the interval between blood feeding, mosquito capture, and processing may have influenced detection sensitivity due to dilution effects or nucleic acid degradation. Additionally, because mosquitoes were collected near cattle enclosures and specimens were not surface-sterilised prior to homogenization, the possibility that external contamination with environmental pathogen DNA cannot be entirely excluded. However, the strong concordance between pathogen identity and expected vertebrate host in individually processed blood-fed specimens argues against non-specific environmental contamination as a primary explanation. Specifically, A. marginale was detected exclusively in cattle-fed mosquitoes and Anaplasma sp. in goat-fed mosquitoes, and surface-derived DNA would not be expected to correlate with blood-meal host identity. Furthermore, pathogen detection rates for some species, particularly Ae. hirsutus (n = 11 pools), were based on small sample sizes and should not be directly compared with rates from more extensively sampled species. Finally, the cross-sectional design precludes assessment of temporal dynamics in pathogen circulation. Future studies incorporating individual mosquito analyses, longitudinal sampling, and controlled laboratory experiments will be important for refining interpretation and strengthening mosquito-based xenosurveillance approaches. Conclusions Our results demonstrate that mosquito-based xenosurveillance is a feasible and practical approach for monitoring livestock-associated bacterial pathogens in Kenya. By revealing both veterinary and zoonotic pathogens circulating at the livestock-human interface, mosquito-derived sampling can complement existing surveillance tools and help detect emerging threats earlier than traditional methods alone. As One Health challenges continue to intensify across East Africa, cost-effective surveillance strategies that use blood-feeding insects as biological samplers may strengthen disease monitoring, support targeted control efforts, and enhance preparedness for vector-borne and zoonotic diseases. Future studies should focus on factors that influence pathogen detection in mosquito-derived samples, including the time between blood feeding and sample processing, the persistence of pathogen nucleic acids in the mosquito midgut, and pathogen levels in the host at the time of feeding. Carefully designed laboratory studies addressing these factors are essential to improve data interpretation and optimize the use of mosquito-based xenosurveillance in complex agro-pastoral systems. Declarations Acknowledgements The authors would like to express their sincere gratitude to Joel L. Bargul of Jomo Kenyatta University of Agriculture and Technology (JKUAT) and Daniel K. Masiga of icipe for their invaluable guidance and mentorship throughout the study. We are grateful to Emily Kimathi of IGAD Climate Prediction and Application Centre (ICPAC) for help in generating the study area maps, David Wainana of icipe for the assistance during field sample collection and John Gachoya for mosquito identification. Special thanks are extended to the homeowners and cattle farmers for their co-operation and for granting us access to their property for mosquito sampling. Funding The authors gratefully acknowledge the financial support for this research by the following organizations and agencies: the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 101000365 (PREPARE4VBD); the Swedish International Development Cooperation Agency (Sida); the Swiss Agency for Development and Cooperation (SDC); the Australian Centre for International Agricultural Research (ACIAR); the Government of Norway; the German Federal Ministry for Economic Cooperation and Development (BMZ); and the Government of the Republic of Kenya. The views expressed herein do not necessarily reflect the official opinion of the donors. Availability of data and materials The sequences generated and analyzed during the current study have been deposited at the NCBI GenBank database under accession PZ069361–PZ069368. Authors’ contributions DG : Conceptualization, Investigation, Methodology, Data curation, Formal analysis, Software, Validation, Writing – original draft. SM : Supervision, Validation, Writing – review & editing. OE : Investigation, Data curation, Formal analysis, Software, Writing – review & editing. EY : Formal analysis, Software, Writing – review & editing. JK : Formal analysis, Writing – review & editing. RK : Formal analysis, Software, Writing – review & editing. JV : Conceptualization, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Software, Validation, Writing – review & editing. All authors read and approved the final manuscript. Ethics approval and consent to participate This study was approved by Pwani University Ethics Review Committee (Ref: ERC/EXT/002/2020E) and National Commission for Science, Technology & Innovation (NACOSTI) (Ref: NACOSTI/P/24/38943). Mosquitoes were sampled using CDC light traps placed in the vicinity of cattle enclosures; no animals or humans were handled during the study. Prior to trap placement, livestock owners were briefed about the study and informed oral consent was obtained from the household heads before proceeding with trapping of mosquitoes on their property. Consent for publication Not applicable. Competing interests The authors declare no conflict of interests. References Vieira CJSP, Gyawali N, Onn MB, Shivas MA, Shearman D, Darbro JM, et al. Mosquito bloodmeals can be used to determine vertebrate diversity, host preference, and pathogen exposure in humans and wildlife. Sci Rep. 2024;14:23203. https://doi.org/10.1038/s41598-024-73820-y Daszak P, Cunningham AA, Hyatt AD. 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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-9010968","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":605882810,"identity":"038375ec-0fa9-402d-a863-20c9ad200088","order_by":0,"name":"Dennis Getange","email":"","orcid":"","institution":"International Centre of Insect Physiology and Ecology","correspondingAuthor":false,"prefix":"","firstName":"Dennis","middleName":"","lastName":"Getange","suffix":""},{"id":605882813,"identity":"2c9c3631-f2b6-4fce-9efa-dadd580a6c24","order_by":1,"name":"Samson Mukaratirwa","email":"","orcid":"","institution":"University of KwaZulu-Natal","correspondingAuthor":false,"prefix":"","firstName":"Samson","middleName":"","lastName":"Mukaratirwa","suffix":""},{"id":605882816,"identity":"c475f931-0ac0-41d3-9309-e327661e1323","order_by":2,"name":"Oscar Esibi","email":"","orcid":"","institution":"International Centre of Insect Physiology and Ecology","correspondingAuthor":false,"prefix":"","firstName":"Oscar","middleName":"","lastName":"Esibi","suffix":""},{"id":605882819,"identity":"55fc56c9-5afe-4e52-b070-7bd3406689f4","order_by":3,"name":"Epaphrus Yuko","email":"","orcid":"","institution":"International Centre of Insect Physiology and Ecology","correspondingAuthor":false,"prefix":"","firstName":"Epaphrus","middleName":"","lastName":"Yuko","suffix":""},{"id":605882822,"identity":"99c9481e-381c-4299-9023-7e4b37bfb6e8","order_by":4,"name":"James Kabii","email":"","orcid":"","institution":"International Centre of Insect Physiology and Ecology","correspondingAuthor":false,"prefix":"","firstName":"James","middleName":"","lastName":"Kabii","suffix":""},{"id":605882825,"identity":"46fb3871-eba5-4265-8c44-4e53cecd690f","order_by":5,"name":"Rua Khogali","email":"","orcid":"","institution":"International Centre of Insect Physiology and Ecology","correspondingAuthor":false,"prefix":"","firstName":"Rua","middleName":"","lastName":"Khogali","suffix":""},{"id":605882827,"identity":"236a0ef6-9288-452f-947e-a1480ee88a0f","order_by":6,"name":"Jandouwe Villinger","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0klEQVRIiWNgGAWjYBACxgYGBgkQg5+ZgeEAaVokm4nVAgJgLQZEq2duP3vwxse2w3LGx5kfHi6oYJAz719AwGE9ecmWM9sOG5sdZjM4POMMg7HMjQcEtDTkmEnztt1O3HaYh+EwbxtD4gwJAk5k7H8D1lK/uRmk5R8xWmZAbEkwYAZpaQBq4W8gpOWNseWMc/8NZ4D9ckzCWEICvw4Gw/4cwxsfytLk+fsPP/5cUGMjJ8FPwGGGyK5gBseRRAJ+LfLIHGYwSciWUTAKRsEoGHEAAMV+QsM2OTN3AAAAAElFTkSuQmCC","orcid":"","institution":"International Centre of Insect Physiology and Ecology","correspondingAuthor":true,"prefix":"","firstName":"Jandouwe","middleName":"","lastName":"Villinger","suffix":""}],"badges":[],"createdAt":"2026-03-02 13:54:26","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9010968/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9010968/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104736583,"identity":"b0136de5-51a5-4629-8159-2c4119974cbf","added_by":"auto","created_at":"2026-03-16 15:28:08","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":599053,"visible":true,"origin":"","legend":"\u003cp\u003eMap of the study area in the livestock-wildlife interface of Kajiado and Nakuru County, Kenya, showing mosquito sampling sites around cattle enclosures. The maps were created using the open-source software, QGIS v. 3.40.14\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-9010968/v1/20a9d5c66ed73e8f7b342cea.png"},{"id":104736621,"identity":"357c9cac-d6cd-4338-8b93-8ef787ccc516","added_by":"auto","created_at":"2026-03-16 15:28:24","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1012298,"visible":true,"origin":"","legend":"\u003cp\u003eAlluvial diagram showing mosquito blood-feeding patterns and vertebrate host associations, visualized using the \u003cem\u003ebipartite\u003c/em\u003e R package.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-9010968/v1/74587a911393d0df60a2aa37.png"},{"id":104736659,"identity":"1b306cde-e891-4c69-8253-32b49e3af009","added_by":"auto","created_at":"2026-03-16 15:28:30","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":441784,"visible":true,"origin":"","legend":"\u003cp\u003eMaximum likelihood phylogenetic tree of \u003cem\u003eAnaplasma\u003c/em\u003e and \u003cem\u003eCandidatus\u003c/em\u003eNeoehrlichia mikurensis 16S rRNA gene (1030bp) gene sequences (some identical sequences are represented by a single entry). GenBank accession numbers, species identifications, and country of origin in brackets. Sequences from this study are bolded. Bootstrap values at the major nodes are of percentage agreement among 1000 replicates.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-9010968/v1/7ed95fbfe952252bfe8b884c.png"},{"id":104736688,"identity":"6858fb6d-8986-4436-acd0-361b17c2761e","added_by":"auto","created_at":"2026-03-16 15:28:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3539325,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9010968/v1/e5b88302-6abf-4a9f-872b-c7b63514a105.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Mosquito-based xenosurveillance reveals circulation of Anaplasma and Neoehrlichia in livestock at a human–wildlife interface in Kenya","fulltext":[{"header":"Background","content":"\u003cp\u003eOver the recent years, the emergence and re-emergence of vector-borne infectious diseases have increased significantly resulting in substantial global economic and public health burdens [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. This trend is driven largely by ecological, demographic, and climatic shifts that increase interactions among humans, livestock, and wildlife [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. An estimated 60% of emerging infectious diseases are zoonotic, and more than two-thirds of these originate in wildlife reservoirs [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Although viral pathogens constitute a major proportion of these threats, bacterial and protozoan zoonoses, particularly those transmitted by arthropod vectors, remain critically important to both veterinary and human health [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Species within the \u003cem\u003eAnaplasma\u003c/em\u003e, \u003cem\u003eEhrlichia\u003c/em\u003e, \u003cem\u003eRickettsia\u003c/em\u003e, \u003cem\u003eBabesia\u003c/em\u003e, and \u003cem\u003eTheileria\u003c/em\u003e genera circulate in complex enzootic cycles involving domestic animals, wildlife, and hematophagous arthropods [\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. These pathogens can cause debilitating diseases such as anaplasmosis, ehrlichiosis, and theileriosis, leading to significant livestock morbidity and economic losses across tropical and subtropical regions [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Therefore, the development of innovative surveillance tools capable of detecting diverse vector-borne pathogens is essential for strengthening early warning systems and improving integrated disease control.\u003c/p\u003e \u003cp\u003eWhile ticks remain the primary vectors of many bacterial pathogens affecting livestock, growing evidence indicates that non-tick hematophagous arthropods, including mosquitoes, Hippoboscids, biting midges, and stable flies, can occasionally harbour pathogen DNA acquired through blood-meals from infected hosts [\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. This has renewed interest in their potential roles in mechanical transmission and in xenosurveillance-based pathogen monitoring. Notably, recent experimental work demonstrated that the camel-specific ked \u003cem\u003eHippobosca camelina\u003c/em\u003e can transmit \u003cem\u003eCandidatus\u003c/em\u003e Anaplasma camelii to laboratory mice, indicating the potential role of non-tick blood-feeding flies in the ecology of \u003cem\u003eAnaplasma\u003c/em\u003e spp. transmission [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Although mosquitoes are not biological vectors for these bacteria, their ability to carry detectable pathogen DNA offers opportunities for pathogen monitoring through molecular surveillance approaches. Moreover, mosquitoes already serve as major vectors of diverse protozoan, viral, and filarial pathogens affecting humans, livestock, and wildlife [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], highlighting their global epidemiological importance. Understanding cross-vector interactions at livestock\u0026ndash;vector interfaces is therefore essential for unravelling the complex ecological networks that shape pathogen transmission in agro-ecological systems.\u003c/p\u003e \u003cp\u003eUse of blood-feeding arthropods as \"biological syringes\" for detecting vertebrate pathogens, termed xenosurveillance or invertebrate-derived DNA (iDNA) screening, has achieved considerable momentum in recent years [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. This non-invasive method is based on the analysis of host selection and host preferences of hematophagous arthropods, achieved through the molecular identification of their blood-meals [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. By capitalising on the broad feeding ranges of mosquitoes and other hematophagous taxa, xenosurveillance enables these insects to serve as natural samplers of vertebrate communities, particularly in regions where conventional wildlife or livestock sampling is logistically difficult [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The approach has been successfully applied to detect a wide range of pathogens, including arboviruses, malaria parasites, filarial nematodes, and non\u0026ndash;vector-borne agents such as influenza virus and Epstein\u0026ndash;Barr virus from mosquito blood meals [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e], demonstrating its versatility for broad-scale pathogen surveillance across human, livestock, and wildlife interfaces. Insights derived from these vector-host-pathogen profiles are critical for guiding disease-control strategies [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] and position xenosurveillance as a powerful component of integrated One Health surveillance systems.\u003c/p\u003e \u003cp\u003eAlthough most research on mosquito-associated pathogens has focused on arboviruses and protozoa such as \u003cem\u003ePlasmodium\u003c/em\u003e spp., increasing attention is being directed toward the detection of tick-borne bacterial pathogens in mosquitoes as part of integrated biosurveillance efforts [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Recent molecular studies have identified \u003cem\u003eRickettsia\u003c/em\u003e DNA in blood-fed mosquitoes, suggesting that these insects may acquire tick-borne bacteria incidentally during blood feeding and could potentially act as mechanical carriers [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. While these detections do not imply biological transmission, they highlight the value of mosquitoes as passive sentinels for identifying areas of elevated pathogen circulation in livestock systems. In this study, we collected mosquitoes around cattle enclosures at night to investigate their potential role in the epidemiology and surveillance of tick-borne pathogens. Specifically, we evaluated whether mosquito-derived blood-meals can reveal the presence and distribution of Anaplasmataceae in livestock-dominated environments.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy area and mosquito collection\u003c/h2\u003e \u003cp\u003eThe study was conducted in two livestock-wildlife interface regions of Kenya as part of a study by Getange et al. [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]: Amboseli in Kajiado County and Naivasha in Nakuru County (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Amboseli is an arid to semi-arid ecosystem characterized by open savannah, seasonal wetlands, and dispersed Maasai pastoralist settlements. It supports high densities of domestic livestock, primarily cattle (\u003cem\u003eBos indicus\u003c/em\u003e), goats (\u003cem\u003eCapra hircus\u003c/em\u003e), and sheep (\u003cem\u003eOvis aries\u003c/em\u003e), alongside free-ranging wildlife such as African buffalo (\u003cem\u003eSyncerus caffer\u003c/em\u003e), elephants (\u003cem\u003eLoxodonta africana\u003c/em\u003e), zebra (\u003cem\u003eEquus quagga\u003c/em\u003e), giraffe (\u003cem\u003eGiraffa\u003c/em\u003e spp.), and multiple antelope species. The close spatial overlap of these host communities facilitates the circulation of diverse vector-borne pathogens [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Naivasha, in contrast, is a sub-humid agro-ecological zone with mixed livestock production, horticultural farming, and abundant wildlife associated with the Lake Naivasha ecosystem [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Both sites experience bimodal rainfall patterns, with mosquito populations typically increasing during the long and short rainy seasons.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eMosquitoes were collected around cattle enclosures overnight (6:00pm\u0026thinsp;\u0026minus;\u0026thinsp;6:00am) using Centres for Disease Control and Prevention (CDC) miniature light traps (Model 512, John Hock Co., Gainesville, Florida, USA) baited with carbonated dry ice (CO\u003csub\u003e2\u003c/sub\u003e) during the long rainy season in April 2024, a period associated with increased vector activity. Traps were suspended approximately 1.5 m above ground level and positioned 5 m from cattle enclosures to maximize the capture of host-seeking mosquitoes. Traps operated continuously overnight and were retrieved the following morning. Mosquito samples were linked to the collection sites by geo-coding using a GPS. Captured mosquitoes were temporarily immobilized using triethylamine and transported in liquid nitrogen to International Centre of Insect Physiology and Ecology (\u003cem\u003eicipe\u003c/em\u003e) Martin L\u0026uuml;scher Emerging Infectious Diseases (ML-EID) Laboratory in Nairobi for identification and further molecular analysis.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMosquito morphological identification\u003c/h3\u003e\n\u003cp\u003eMosquitoes were identified morphologically to species level under a stereomicroscope using established taxonomic keys, including Edwards [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], Harbach [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e], and Huang and Ward [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Following identification, specimens were pooled into groups of 1\u0026ndash;25 individuals based on species, sex, collection site, and collection date. Blood-fed mosquitoes were processed individually and treated as pools of size 1, a deliberate decision consistent with the study\u0026rsquo;s primary objective of detecting and characterizing tick-borne bacterial pathogens from bloodmeal-derived DNA. Mosquitoes of the same species were placed in sterile 1.5 mL microcentrifuge tubes (303 pools in total) and stored at -80\u0026deg;C until further molecular processing.\u003c/p\u003e\n\u003ch3\u003eDNA extraction of mosquito pools and individuals\u003c/h3\u003e\n\u003cp\u003eMosquito pools and individual mosquitoes were homogenized prior to DNA extraction to ensure thorough disruption of tissues. Specimens were not surface-sterilised prior to homogenization, as the primary objective was to detect pathogen DNA acquired through blood feeding rather than to establish vector competence. Each pool was placed in a 1.5-mL microcentrifuge tube containing five 2.0-mm zirconia/yttria-stabilized beads (BioSpec, USA) and mechanically disrupted using a Mini Bead Beater 16 (BioSpec, Bartlesville, USA) for approximately 30 seconds at ~\u0026thinsp;3,450 rpm. Following homogenization, genomic DNA was extracted using the Isolate II Genomic DNA Kit (Bioline, UK) according to the manufacturer\u0026rsquo;s instructions. Extracted DNA from each pool was stored at -20\u0026deg;C until PCR screening.\u003c/p\u003e\n\u003ch3\u003eMosquito blood-meal source identification\u003c/h3\u003e\n\u003cp\u003eAll blood-fed mosquito samples were individually analysed to determine the vertebrate host origin of the blood. Host identification was performed using PCR amplification of vertebrate mitochondrial markers, specifically cytochrome \u003cem\u003eb\u003c/em\u003e (cyt \u003cem\u003eb\u003c/em\u003e) and 16S rRNA (vert16S), which have been shown to reliably differentiate a wide range of vertebrate taxa [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. For each specimen, 1 \u0026micro;L of extracted nucleic acid served as template in a 10 \u0026micro;L reaction mixture containing 2 \u0026micro;L of 5\u0026times; HOT FIREPol\u0026reg; EvaGreen\u0026reg; qPCR Mix (Solis BioDyne, Estonia) and 10 pmol of each primer. PCR amplification and high-resolution melting (HRM) analysis were conducted on a MIC PCR Cycler (BioMolecular Systems, Upper Coomera, Queensland, Australia) following previously optimized protocols [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. DNA from known vertebrate hosts, including human, cattle, sheep, goat, elephant, and chicken, was included in each run as positive controls to support interpretation of melting profiles. Nuclease-free water was included as a non-template control in each assay to monitor for potential reagent contamination. Representative amplicons exhibiting distinct HRM profiles consistent with our positive controls were purified using an Exo-rSAP enzymatic cleanup (New England Biolabs, UK), and outsourced to Macrogen Europe (The Netherlands) for Sanger sequencing to confirm host identity.\u003c/p\u003e \u003cp\u003e \u003cb\u003eScreening of mosquito pools for\u003c/b\u003e \u003cb\u003eAnaplasma\u003c/b\u003e, \u003cb\u003eEhrlichia, Rickettsia\u003c/b\u003e, \u003cb\u003eTheileria\u003c/b\u003e \u003cb\u003eand\u003c/b\u003e \u003cb\u003eBabesia\u003c/b\u003e\u003c/p\u003e \u003cp\u003eAll mosquito DNA samples were screened for \u003cem\u003eAnaplasma\u003c/em\u003e, \u003cem\u003eEhrlichia\u003c/em\u003e, \u003cem\u003eRickettsia\u003c/em\u003e, \u003cem\u003eTheileria\u003c/em\u003e, and \u003cem\u003eBabesia\u003c/em\u003e using PCR-high-resolution melting (HRM) analysis performed on a Mic PCR Cycler (BioMolecular Systems, Upper Coomera, Queensland, Australia). Screening was conducted using previously published primer sets (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), following the PCR-HRM protocol described by Mwamuye et al. [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] and Getange et al. [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Primer pairs included those amplifying fragments of the 16S rRNA gene for \u003cem\u003eAnaplasma\u003c/em\u003e spp. (AnaplasmaJVF/JVR) and \u003cem\u003eEhrlichia\u003c/em\u003e spp. (Ehrlichia16S F/R), and the \u003cem\u003eRickettsia\u003c/em\u003e spp. 16S rRNA gene (Rick16SF/R). In addition, the 18S rRNA gene of \u003cem\u003eTheileria\u003c/em\u003e and \u003cem\u003eBabesia\u003c/em\u003e spp. was amplified using RLB F/R primers. Each 10-\u0026micro;L HRM reaction consisted of 0.5 \u0026micro;L of each primer (10 pmol/\u0026micro;L), 2 \u0026micro;L of FIREPol\u0026reg; EvaGreen\u0026reg; HRM Master Mix (Solis BioDyne, Tartu, Estonia), 1 \u0026micro;L genomic DNA, and nuclease-free water to final volume. PCR cycling and HRM conditions followed previously described protocol [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePrimers used for blood-meal analysis and molecular detection of TBPs in mosquito pools\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimer name\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGene target\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTarget size (bp)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSequence (5\u0026rsquo;\u0026ndash;3\u0026rsquo;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eReference\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCytb F\u003c/p\u003e \u003cp\u003eCytb R\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVertebrate cyt \u003cem\u003eb\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCCCCTCAGAATGATATTTGTCCTCA\u003c/p\u003e \u003cp\u003eCATCCAACATCTCAGCATGATGAAA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVert16S F\u003c/p\u003e \u003cp\u003eVert16S R\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eVertebrate 16S\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e250\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGAGAAGACCCTRTGGARCTT\u003c/p\u003e \u003cp\u003eCGCTGTTATCCCTAGGGTA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRick-F\u003c/p\u003e \u003cp\u003eRick-R\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eRickettsia\u003c/em\u003e 16S rRNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e364\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGAACGCTATCGGTATGCTTAACACA\u003c/p\u003e \u003cp\u003eCATCACTCACTCGGTATTGCTGGA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e120\u0026ndash;2788\u003c/p\u003e \u003cp\u003e120\u0026ndash;3599\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eRickettsia\u003c/em\u003e ompB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e856\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAAACAATAATCAAGGTACTGT\u003c/p\u003e \u003cp\u003eTACTTCCGGTTACAGCAAAGT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eEhrlichia\u003c/em\u003e16S F\u003c/p\u003e \u003cp\u003e\u003cem\u003eEhrlichia\u003c/em\u003e16SR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eEhrlichia\u003c/em\u003e 16S rRNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCGTAAAGGGCACGTAGGTGGACTA\u003c/p\u003e \u003cp\u003eCACCTCAGTGTCAGTATCGAACCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePER1\u003c/p\u003e \u003cp\u003ePER2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eEhrlichia\u003c/em\u003e 16S rRNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e451\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eTTTATCGCTATTAGATGAGCCTATG\u003c/p\u003e \u003cp\u003eCTCTACACTAGGAATTCCGCTAT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEHR16SD\u003c/p\u003e \u003cp\u003e1492R\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAnaplasma\u003c/em\u003e/\u003cem\u003eEhrlichia\u003c/em\u003e 16S rRNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGGTACCYACAGAAGAAGTCC\u003c/p\u003e \u003cp\u003eGGTTACCTTGTTACGACTT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAnaplasma\u003c/em\u003eJF\u003c/p\u003e \u003cp\u003e\u003cem\u003eAnaplasma\u003c/em\u003eJR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAnaplasma\u003c/em\u003e 16S rRNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCGGTGGAGCATGTGGTTTAATTC\u003c/p\u003e \u003cp\u003eCGRCGTTGCAACCTATTGTAGTC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRLB F\u003c/p\u003e \u003cp\u003eRLB R\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eTheileria\u003c/em\u003e/\u003cem\u003eBabesia\u003c/em\u003e 18S rRNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e460\u0026ndash;520\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGAGGTAGTGACAAGAAATAACAATA\u003c/p\u003e \u003cp\u003eTCTTCGATCCCCTAACTTTC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSamples with distinct HRM profiles were subjected to confirmatory PCR assays using EHR16SD\u0026ndash;1492R primer pair for \u003cem\u003eAnaplasma\u003c/em\u003e spp., and PER1\u0026ndash;PER2 primers for \u003cem\u003eEhrlichia\u003c/em\u003e spp. (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). These reactions were performed on a ProFlex PCR System (Applied Biosystems, Foster City, CA, USA) in a total volume of 15 \u0026micro;L, comprising 3 \u0026micro;L of 5\u0026times; HOT FIREPol\u0026reg; Blend Master Mix (Solis BioDyne, Tartu, Estonia), 1.5 \u0026micro;L of template DNA, and 0.75 \u0026micro;L each of forward and reverse primers (10 pmol/\u0026micro;L). Thermocycling conditions followed previously published protocols [\u003cspan additionalcitationids=\"CR38\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Amplification success was assessed by electrophoresing 5 \u0026micro;L of PCR products on a 2% agarose gel pre-stained with ethidium bromide, followed by visualization under UV illumination. Remaining PCR products were purified using ExoSAP (New England Biolabs, UK) according to the manufacturer\u0026rsquo;s guidelines. Purified amplicons were then submitted to Macrogen Europe (The Netherlands) for Sanger sequencing.\u003c/p\u003e\n\u003ch3\u003ePhylogenetic and bioinformatic analyses\u003c/h3\u003e\n\u003cp\u003eForward and reverse sequence chromatograms obtained through Sanger sequencing were inspected, edited, and assembled into high-quality consensus sequences using Geneious Prime v2024.0.7 [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Consensus sequences were compared against publicly available reference sequences in the NCBI database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.ncbi.nlm.nih.gov\u003c/span\u003e\u003cspan address=\"http://www.ncbi.nlm.nih.gov\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) through BLASTn searches [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e] to verify taxonomic identities and assess similarity to known pathogen reference sequences. For evolutionary inference, multiple sequence alignments were generated using MAFFT, after which maximum-likelihood phylogenetic trees were reconstructed in PhyML v3.0 [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. The optimal nucleotide substitution model for each dataset was selected automatically using the Akaike Information Criterion [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Resulting phylogenies were visualized and annotated in FigTree v1.4.4 [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]. Pathogen detection frequencies were expressed as the proportion of positive mosquito pools relative to the total number of pools screened for each pathogen group. In addition, minimum infection rates (MIR) were calculated as the number of positive pools divided by the total number of individual mosquitoes tested per species, multiplied by 1,000, to enable standardised comparison across species with different pool sizes.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eMorphological identification of mosquitoes\u003c/h2\u003e \u003cp\u003eA total of 4,673 mosquitoes (303 pools) representing five genera (\u003cem\u003eAedes\u003c/em\u003e, \u003cem\u003eAnopheles\u003c/em\u003e, \u003cem\u003eCulex\u003c/em\u003e, \u003cem\u003eMansonia\u003c/em\u003e, and \u003cem\u003eCoquillettidia\u003c/em\u003e), were collected in Amboseli (n\u0026thinsp;=\u0026thinsp;546) and Naivasha (n\u0026thinsp;=\u0026thinsp;4,127) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Overall, \u003cem\u003eCulex\u003c/em\u003e was the dominant genus, accounting for 74.3% (n\u0026thinsp;=\u0026thinsp;3,473) of all collected mosquitoes, followed by \u003cem\u003eMansonia\u003c/em\u003e at 23.5% (n\u0026thinsp;=\u0026thinsp;1,100). In contrast, \u003cem\u003eAedes\u003c/em\u003e and \u003cem\u003eAnopheles\u003c/em\u003e were comparatively less abundant, contributing 1.5% (n\u0026thinsp;=\u0026thinsp;70) and 0.4% (n\u0026thinsp;=\u0026thinsp;19) of the total catch, respectively, while \u003cem\u003eCoquillettidia aurites\u003c/em\u003e represented 0.24% (n\u0026thinsp;=\u0026thinsp;11). At the species level, the most abundant mosquitoes were \u003cem\u003eCulex pipiens\u003c/em\u003e (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3,220; 68.9%), followed by \u003cem\u003eMansonia africana\u003c/em\u003e (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;976; 19.6%), and \u003cem\u003eCulex vansomereni\u003c/em\u003e (\u003cem\u003en\u003c/em\u003e\u0026thinsp;=\u0026thinsp;126; 2.7%). These three species collectively constituted over 92.5% of the entire mosquito collection. Naivasha collections were dominated by \u003cem\u003eCulex pipiens\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;2,837; 68.7%), followed by \u003cem\u003eMn. africana\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;942; 22.8%) and \u003cem\u003eCx. vansomereni\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;126; 3.1%). In contrast, Amboseli was dominated by \u003cem\u003eCx. pipiens\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;383; 70.1%), followed by \u003cem\u003eCx. univittatus\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;90; 16.5%) and \u003cem\u003eMn. africana\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;34; 6.2%).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSummary of mosquito species trapped at the sampling sites in Kajiado and Naivasha counties of Kenya\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGenus\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eAmboseli\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c7\" namest=\"c6\"\u003e \u003cp\u003eNaivasha\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eSpecies\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003ePools\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eF\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eM\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003eF\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003eM\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAedes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAe. aegypti\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAe. hirsutus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e47\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAe. mcintoshi\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e15\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAe. tarsalis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAe. tricholabis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAnopheles\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAn. coustani\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAn. funestus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAn. gambiae\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAn. pharoensis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e12\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCoquillettidia\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCq. aurites\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e11\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCulex\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCx. annulirostris\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCx. bitaeniorhynchus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCx. cinereus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCx. pipiens\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e366\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2827\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e3220\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCx. poicilipes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCx. tigripes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCx. univittatus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e105\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCx. vansomereni\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e126\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCx. zombaensis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e12\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMansonia\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eMn. africana\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e877\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e976\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eMn. uniformis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e124\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e303\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e527\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e19\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e4011\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e116\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e4673\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eMosquito blood-meal analysis\u003c/h3\u003e\n\u003cp\u003eFifty-six mosquitoes that were visibly blood-fed representing eight species across four genera (\u003cem\u003eCulex, Aedes, Anopheles\u003c/em\u003e and \u003cem\u003eMansonia\u003c/em\u003e) were analysed for vertebrate blood-meal sources using cytochrome \u003cem\u003eb\u003c/em\u003e sequencing. Vertebrate host DNA was successfully identified in 43 mosquitoes, representing a 76.8% success rate (n\u0026thinsp;=\u0026thinsp;56). The detected vertebrate hosts included humans (\u003cem\u003eHomo sapiens\u003c/em\u003e), cattle (\u003cem\u003eBos taurus\u003c/em\u003e), goats (\u003cem\u003eCapra hircus\u003c/em\u003e), sheep (\u003cem\u003eOvis aries\u003c/em\u003e), hippopotamus (\u003cem\u003eHippopotamus amphibius\u003c/em\u003e), dog (\u003cem\u003eCanis familiaris\u003c/em\u003e), and wildebeest (\u003cem\u003eConnochaetes taurinus\u003c/em\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e), while the remaining 13 samples failed to amplify with any of the vertebrate primers used, likely due to advanced blood-meal digestion, low DNA quantity, or host species falling outside the primer amplification range. Overall, human (23.2%, n\u0026thinsp;=\u0026thinsp;13) was the most frequently detected vertebrate blood-meal source, followed closely by cattle (19.6%, n\u0026thinsp;=\u0026thinsp;11), goats (17.9%, n\u0026thinsp;=\u0026thinsp;10), and sheep (7.1%, n\u0026thinsp;=\u0026thinsp;4). Wildlife-derived blood-meals were less common and included \u003cem\u003eHippopotamus\u003c/em\u003e (5.4%, n\u0026thinsp;=\u0026thinsp;3) and wildebeest (1.9%, n\u0026thinsp;=\u0026thinsp;1), while dog blood was detected in a single sample (1.9%, n\u0026thinsp;=\u0026thinsp;1). \u003cem\u003eCulex\u003c/em\u003e species, particularly \u003cem\u003eCx. pipiens\u003c/em\u003e and \u003cem\u003eCx. univittatus\u003c/em\u003e, showed the greatest diversity of host use and accounted for most livestock- and human-derived blood-meals, whereas \u003cem\u003eMansonia\u003c/em\u003e and \u003cem\u003eAedes\u003c/em\u003e species contributed mainly to wildlife- and mixed-interface feeding patterns. In Nakuru, goats were the primary host (n\u0026thinsp;=\u0026thinsp;9), while in Kajiado, cattle were the most frequent source of blood-meals (n\u0026thinsp;=\u0026thinsp;9) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDistribution of vertebrate blood-meal sources among blood-fed mosquito species collected in Nakuru and Kajiado counties of Kenya\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCounty\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMosquito Species\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHuman\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCattle\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eGoat\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSheep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eHippo\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eWildebeest\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eDog\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c11\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNakuru\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAedes hirsutus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAedes mcintoshi\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAedes tricholabis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAedes trisatus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAnopheles funestus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAnopheles pharoensis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCulex annulirostris\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCulex pipiens\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCulex poicilipes\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCulex univittatus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCulex vansomereni\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eMansonia uniformis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e6\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eNakuru Total\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e34\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e8 (23.5%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e2 (5.9%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e9 (26.5%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e3 (8.8%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e3 (8.8%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0 (0%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e0 (0%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e9 (26.5%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKajiado\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAedes hirsutus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCulex cinereus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCulex pipiens\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCulex univittatus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eMansonia africana\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eKajiado Total\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e22\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e5 (22.7%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e9 (40.9%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e1 (4.5%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e1 (4.5%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e0 (0%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e1 (4.5%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e1 (4.5%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cb\u003e4 (18.2%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003ePathogen detection in mosquito pools\u003c/h2\u003e \u003cp\u003eScreening of mosquito pools for tick-borne pathogens revealed low but notable detection of \u003cem\u003eAnaplasma\u003c/em\u003e and \u003cem\u003eNeoehrlichia\u003c/em\u003e spp. in mosquito species from Kajiado County, and none from Naivasha County. \u003cem\u003eCulex pipiens\u003c/em\u003e had the highest diversity of detections, with \u003cem\u003eAnaplasma marginale\u003c/em\u003e identified in 1/150 pools (0.7%; MIR\u0026thinsp;=\u0026thinsp;0.31) and an unclassified \u003cem\u003eAnaplasma\u003c/em\u003e sp. (2/150; 1.4%; MIR\u0026thinsp;=\u0026thinsp;0.62). In contrast, \u003cem\u003eAedes hirsutus\u003c/em\u003e showed comparatively higher pool positivity rates, with \u003cem\u003eA. marginale\u003c/em\u003e (2/11; 18.2%; MIR\u0026thinsp;=\u0026thinsp;42.55) and \u003cem\u003eAnaplasma\u003c/em\u003e sp. (1/11; 9.1%; MIR\u0026thinsp;=\u0026thinsp;21.28). Phylogenetic analysis based on partial 16S rRNA gene sequences showed that \u003cem\u003eA. marginale\u003c/em\u003e sequences generated in this study clustered closely with reference sequences from Kenya (PV133719; 99.89%) and Uganda (KU686780; 99.79%). Similarly, \u003cem\u003eAnaplasma\u003c/em\u003e sp. sequences aligned with reference sequences from South Africa (OQ909493; 99.44%) and Zambia (LC558313; 99.55%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eNotably, \u003cem\u003eMn. africana\u003c/em\u003e was exclusively positive for \u003cem\u003eCandidatus\u003c/em\u003e Neoehrlichia mikurensis (2/50; 4%), marking the only occurrence of this emerging pathogen within the mosquito collection (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). Sequences identified as \u003cem\u003eCa.\u003c/em\u003e Neoehrlichia mikurensis clustered with reference sequences from China (GU227699; 98.1% and JQ359050; 98.1%), supporting their taxonomic assignment (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). We did not detect any \u003cem\u003eRickettsia\u003c/em\u003e, \u003cem\u003eTheileria\u003c/em\u003e, or \u003cem\u003eBabesia\u003c/em\u003e DNA in this study.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePooled positivity rates and minimum infection rates (MIR) of pathogens detected in mosquito pools from Naivasha and Kajiado counties of Kenya\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePathogen detected (No. of pools)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePositive pools\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePool positivity (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e95% CI (Lower - Upper)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMIR (per 1,000)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCulex pipiens\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;150)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAnaplasma marginale\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.67%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.017% \u0026ndash; 3.66%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAnaplasma sp.\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.33%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.16% \u0026ndash; 4.73%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.62\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAedes hirsutus\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAnaplasma marginale\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18.18%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.28% \u0026ndash; 51.78%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e42.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eAnaplasma sp.\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.09%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.23% \u0026ndash; 41.28%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e21.28\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eMansonia africana\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eCandidatus\u003c/em\u003e Neoehrlichia mikurensis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.00%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.49% \u0026ndash; 13.71%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTick-borne pathogen\u0026ndash;positive mosquito pools were identified in three mosquito species, and their associated blood-meal sources were determined by cytochrome \u003cem\u003eb\u003c/em\u003e analysis (Tables\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and \u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). \u003cem\u003eAnaplasma marginale\u003c/em\u003e and \u003cem\u003eAnaplasma\u003c/em\u003e sp. were detected in \u003cem\u003eCx. pipiens\u003c/em\u003e and \u003cem\u003eAe. hirsutus\u003c/em\u003e, whereas \u003cem\u003eCa.\u003c/em\u003e Neoehrlichia mikurensis was detected in \u003cem\u003eMn. africana\u003c/em\u003e. In \u003cem\u003eCx. pipiens\u003c/em\u003e, \u003cem\u003eAnaplasma\u003c/em\u003e sp. was identified in two pools that had fed on goats, and \u003cem\u003eA. marginale\u003c/em\u003e was detected in one pool with an undetermined blood-meal source, with sequence identities of 99.7\u0026ndash;99.9% and amplicon lengths ranging from 660 to 952 bp. In \u003cem\u003eAe. hirsutus\u003c/em\u003e, \u003cem\u003eA. marginale\u003c/em\u003e was detected in two pools that had fed on cattle, while \u003cem\u003eAnaplasma\u003c/em\u003e sp. was detected in one pool with a goat-derived blood-meal, with sequence identities of 99.4\u0026ndash;100% and fragment lengths of 391\u0026ndash;917 bp. \u003cem\u003eCandidatus\u003c/em\u003e Neoehrlichia mikurensis was detected in two \u003cem\u003eMn. africana\u003c/em\u003e pools, one associated with a cattle blood-meal and one with an unidentified host, showing 98.1% sequence identity over 372\u0026ndash;377 bp. Overall, the detected tick-borne pathogens (TBPs) were associated primarily with livestock-derived blood-meals, particularly cattle and goats, with sequence identity values\u0026thinsp;\u0026ge;\u0026thinsp;98.1%, confirming the presence of Anaplasmataceae DNA in mosquito blood-meals.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDescription of tick-borne pathogen-positive mosquito samples from Kajiado County, Kenya\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSample ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMosquito species\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBloodmeal source\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePathogen\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eidentity (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eSequence Length(bp)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eGenBank accession\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMSQ278\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCulex pipiens\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eAnaplasma marginale\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e99.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e660\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePZ069361\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMSQ137\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAedes hirsutus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCattle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eAnaplasma\u003c/em\u003e marginale.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e99.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e952\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePZ069362\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMSQ297\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAedes hirsutus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCattle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eAnaplasma\u003c/em\u003e marginale.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e99.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e947\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePZ069363\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMSQ120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCulex pipiens\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGoat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eAnaplasma sp.\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e99.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e917\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePZ069364\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMSQ163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCulex pipiens\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGoat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eAnaplasma\u003c/em\u003e sp.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e99.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e910\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePZ069365\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMSQ273\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAedes hirsutus\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGoat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eAnaplasma\u003c/em\u003e sp.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e391\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePZ069366\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMSQ201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eMansonia africana\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCattle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eCandidatus\u003c/em\u003e Neoehrlichia mikurensis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e98.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e377\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePZ069367\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMSQ207\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eMansonia africana\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eUnknown\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eCa.\u003c/em\u003e Neoehrlichia mikurensis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e98.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e372\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePZ069368\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eHere, we investigated the feasibility of using blood-feeding mosquitoes, for the surveillance of pathogens in livestock at a human\u0026ndash;wildlife interface. We detected \u003cem\u003eA. marginale\u003c/em\u003e, an unclassified \u003cem\u003eAnaplasma\u003c/em\u003e sp., and to our knowledge for the first time, \u003cem\u003eCa.\u003c/em\u003e Neoehrlichia mikurensis in mosquito pools collected around cattle enclosures in Kajiado and Naivasha counties of Kenya. The findings provide evidence that mosquitoes in livestock-dense ecosystems may acquire and indirectly reflect the circulation of bacterial pathogens traditionally associated with tick vectors. Although mosquitoes are not recognized as biological vectors of these bacteria, our results are consistent with previous field studies demonstrating the presence of tick-borne bacterial DNA in field-collected mosquitoes [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. Collectively, these observations support the concept that mosquitoes can function as ecological sentinels of vertebrate infections in pastoral landscapes. Our findings add to a growing body of literature indicating that blood-feeding arthropods, including mosquitoes and other hematophagous insects, may serve as valuable, non-invasive tools for monitoring pathogen circulation in animal populations [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eInterestingly, all pathogen detections in this study originated exclusively from Kajiado County, despite Naivasha contributing 88% of the total mosquito collection (4,127 of 4,673 specimens). Possible explanations include mosquito species composition differed between sites, with livestock-feeding species potentially more abundant in Kajiado's pastoral landscape, increasing the probability of bloodmeal acquisition from tick-infested hosts. Given that tick-borne pathogen DNA in mosquitoes represents bloodmeal content rather than vector infection, variation in livestock management practices that may influence tick burdens and pathogen exposure may also contribute [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. Additionally, the distinct agro-ecological characteristics of Naivasha, a sub-humid zone with mixed farming [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], versus the arid pastoral landscape of Amboseli [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] may influence vector\u0026ndash;host\u0026ndash;pathogen dynamics. Future studies with balanced sampling designs across sites would help clarify whether this pattern reflects genuine spatial variation in pathogen circulation.\u003c/p\u003e \u003cp\u003eOur study detected \u003cem\u003eA. marginale\u003c/em\u003e in \u003cem\u003eCx. pipiens\u003c/em\u003e that fed on unknown host and \u003cem\u003eAe. hirsutus\u003c/em\u003e that fed on cattle, suggesting exposure of livestock to this pathogen, and that mosquito blood-meals can reflect host infection patterns. Circulation of \u003cem\u003eA. marginale\u003c/em\u003e in the region was further supported by parallel findings from a complementary study that molecularly confirmed presence of the pathogen in cattle blood samples collected from same cattle enclosures as mosquitoes in this study using direct host-based diagnostics [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], though the infection rates were higher in blood (24.6%) than mosquitoes (1.9%). All \u003cem\u003eA. marginale\u003c/em\u003e positive mosquitoes were detected in enclosures that contained \u003cem\u003eA. marginale\u003c/em\u003e-positive cattle. The agreement between pathogen detection in mosquito blood-meals and cattle blood [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] provides clear empirical evidence that mosquito-based xenosurveillance can reliably reflect livestock infection status. This finding is noteworthy given the pathogen\u0026rsquo;s well-established role in bovine anaplasmosis and its economic impact across sub-Saharan Africa [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Transmission of \u003cem\u003eA. marginale\u003c/em\u003e is primarily attributed to ixodid ticks and, secondarily, to mechanical transfer by biting flies [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]; however, previous studies have demonstrated that various hematophagous insects may transiently harbour \u003cem\u003eAnaplasma\u003c/em\u003e DNA following blood feeding [\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Experimental studies using mosquito cell lines have shown that \u003cem\u003eAnaplasma\u003c/em\u003e and \u003cem\u003eRickettsia\u003c/em\u003e species can be maintained under laboratory conditions; however, this does not imply biological transmission by mosquitoes in nature [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]. Furthermore, the detection of \u003cem\u003eAnaplasma\u003c/em\u003e DNA in the midguts of field-collected \u003cem\u003eAnopheles\u003c/em\u003e in China, as well as in diverse mosquito species across multiple provinces, reinforces the role of these insects as effective ecological sentinels rather than biological vectors [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. Similarly, the discovery of unclassified \u003cem\u003eAnaplasma\u003c/em\u003e sp. in a mosquito that fed on goat mirrors previous findings of un-characterized \u003cem\u003eAnaplasma\u003c/em\u003e diversity in livestock in Kenya [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e], expanding the scope of known circulation and suggesting broad ecological reservoirs. Host\u0026ndash;pathogen associations observed in this study were highly consistent: \u003cem\u003eA. marginale\u003c/em\u003e detections in \u003cem\u003eAe. hirsutus\u003c/em\u003e were from cattle-fed individuals, while \u003cem\u003eAnaplasma\u003c/em\u003e sp. was exclusively associated with goat-derived blood-meals in both \u003cem\u003eCx. pipiens\u003c/em\u003e and \u003cem\u003eAe. hirsutus\u003c/em\u003e. This concordance between pathogen identity and expected vertebrate host strengthens the biological plausibility of the xenosurveillance detections and suggests that mosquito blood-meals accurately capture host-specific infection patterns.\u003c/p\u003e \u003cp\u003eWe detected \u003cem\u003eCa.\u003c/em\u003e Neoehrlichia mikurensis, a bacterium first described as a human pathogen in Sweden in 2010 [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e], exclusively in \u003cem\u003eMn. africana\u003c/em\u003e that fed on cattle and unknown host, representing the first report of this pathogen in mosquitoes in Africa. While \u003cem\u003eCa.\u003c/em\u003e Neoehrlichia mikurensis is traditionally considered a tick-borne pathogen transmitted primarily by \u003cem\u003eIxodes\u003c/em\u003e species in Europe and Asia, detection in mosquitoes has been previously reported. Guo et al. [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e] identified \u003cem\u003eCa.\u003c/em\u003e Neoehrlichia mikurensis DNA in multiple mosquito species across all life stages, eggs, larvae, pupae, and adults, in China, suggesting that mosquitoes may acquire this bacterium through environmental exposure or bloodmeals from infected vertebrate hosts. Previous studies have documented \u003cem\u003eCa.\u003c/em\u003e Neoehrlichia mikurensis in rodents [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e, \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e], bovine blood [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e], ticks in Africa [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e] and Europe [\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e], and humans across multiple European countries [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan additionalcitationids=\"CR62 CR63 CR64 CR65\" citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]. Given that \u003cem\u003eMn. africana\u003c/em\u003e readily feeds on both livestock and humans in peri-agricultural settings, our detection suggests that mosquitoes may serve as environmental sentinels, providing a non-invasive reflection of local pathogen circulation. Our blood-meal data show that \u003cem\u003eMn. africana\u003c/em\u003e in Kajiado also fed on humans, raising the possibility that this mosquito species bridges livestock and human populations in settings where \u003cem\u003eCa.\u003c/em\u003e Neoehrlichia mikurensis circulates. While this does not constitute evidence of transmission, it highlights the One Health relevance of these findings and underscores the need for targeted screening of at-risk human populations in areas of documented pathogen circulation. However, important knowledge gaps remain. Capacity of \u003cem\u003eCa.\u003c/em\u003e Neoehrlichia mikurensis to survive or replicate within mosquito tissues has not been assessed, and the potential for mechanical transmission has not been evaluated. Additionally, the contribution of wildlife or rodent reservoirs in Kenyan agro-pastoral landscapes remains unknown. Future research should therefore focus on (i) tracing \u003cem\u003eCa.\u003c/em\u003e Neoehrlichia mikurensis in livestock, rodents, and ticks around sampling sites, (ii) experimentally testing bacterial viability and persistence in mosquito tissues, including salivary glands, and (iii) determining whether mosquito-derived detections reflect genuine exposure or incidental carriage.\u003c/p\u003e \u003cp\u003eHowever, we did not detect \u003cem\u003eRickettsia\u003c/em\u003e, \u003cem\u003eTheileria\u003c/em\u003e, or \u003cem\u003eBabesia\u003c/em\u003e DNA in any mosquito pool, despite screening all 303 pools with validated primer sets. The absence of \u003cem\u003eRickettsia\u003c/em\u003e is consistent with the low prevalence of rickettsial agents reported in livestock in the study region. The failure to detect \u003cem\u003eTheileria\u003c/em\u003e and \u003cem\u003eBabesia\u003c/em\u003e, despite their documented prevalence in cattle in the same study area [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], may reflect inherent limitations of xenosurveillance for intracellular parasites that sequester in erythrocytes and maintain relatively low circulating DNA loads in peripheral blood. This observation suggests that mosquito-based xenosurveillance may be better suited for detecting bacterial pathogens with higher bacteraemia levels than for apicomplexan haemoparasites and highlights the need to consider pathogen biology when evaluating the sensitivity of this approach.\u003c/p\u003e \u003cp\u003eOur findings support the growing recognition of mosquitoes as \u0026ldquo;flying syringes\u0026rdquo; or biological samplers capable of capturing vertebrate pathogen profiles without implying vector competence. Previous studies have reported presence of pathogen nucleic acid in mosquito midgut days after feeding [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e], highlighting the possibility of exploiting this retention period for molecular detection of pathogens. Our findings are consistent with xenosurveillance approaches using other hematophagous insects that have revealed cryptic infection reservoirs across wildlife and livestock populations [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e, \u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e]. Therefore, our data reflect environmental circulation rather than biological transmission, demonstrating that mosquitoes can function as scalable, cost-efficient biosamplers, particularly where direct host sampling is difficult, ethically constrained, or expensive. Future laboratory studies should quantify factors affecting detection, such as the decay kinetics of pathogen nucleic acids in the mosquito gut, the time interval between feeding and sample processing, and the pathogen load in the host at the time of feeding, to refine detection probabilities and optimize sampling designs.\u003c/p\u003e \u003cp\u003eHowever, several limitations should be considered when interpreting these findings. Detection of bacterial DNA in mosquitoes reflects recent blood feeding on infected hosts and does not indicate pathogen viability, replication, or transmission potential. Therefore, results from this study should be interpreted strictly within a xenosurveillance framework. The use of pooled samples and variability in the interval between blood feeding, mosquito capture, and processing may have influenced detection sensitivity due to dilution effects or nucleic acid degradation. Additionally, because mosquitoes were collected near cattle enclosures and specimens were not surface-sterilised prior to homogenization, the possibility that external contamination with environmental pathogen DNA cannot be entirely excluded. However, the strong concordance between pathogen identity and expected vertebrate host in individually processed blood-fed specimens argues against non-specific environmental contamination as a primary explanation. Specifically, \u003cem\u003eA. marginale\u003c/em\u003e was detected exclusively in cattle-fed mosquitoes and \u003cem\u003eAnaplasma\u003c/em\u003e sp. in goat-fed mosquitoes, and surface-derived DNA would not be expected to correlate with blood-meal host identity. Furthermore, pathogen detection rates for some species, particularly \u003cem\u003eAe. hirsutus\u003c/em\u003e (n\u0026thinsp;=\u0026thinsp;11 pools), were based on small sample sizes and should not be directly compared with rates from more extensively sampled species. Finally, the cross-sectional design precludes assessment of temporal dynamics in pathogen circulation. Future studies incorporating individual mosquito analyses, longitudinal sampling, and controlled laboratory experiments will be important for refining interpretation and strengthening mosquito-based xenosurveillance approaches.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eOur results demonstrate that mosquito-based xenosurveillance is a feasible and practical approach for monitoring livestock-associated bacterial pathogens in Kenya. By revealing both veterinary and zoonotic pathogens circulating at the livestock-human interface, mosquito-derived sampling can complement existing surveillance tools and help detect emerging threats earlier than traditional methods alone. As One Health challenges continue to intensify across East Africa, cost-effective surveillance strategies that use blood-feeding insects as biological samplers may strengthen disease monitoring, support targeted control efforts, and enhance preparedness for vector-borne and zoonotic diseases. Future studies should focus on factors that influence pathogen detection in mosquito-derived samples, including the time between blood feeding and sample processing, the persistence of pathogen nucleic acids in the mosquito midgut, and pathogen levels in the host at the time of feeding. Carefully designed laboratory studies addressing these factors are essential to improve data interpretation and optimize the use of mosquito-based xenosurveillance in complex agro-pastoral systems.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcknowledgements\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to express their sincere gratitude to Joel L. Bargul of Jomo Kenyatta University of Agriculture and Technology (JKUAT) and Daniel K. Masiga of \u003cem\u003eicipe\u003c/em\u003e for their invaluable guidance and mentorship throughout the study. We are grateful to Emily Kimathi of IGAD Climate Prediction and Application Centre (ICPAC) for help in generating the study area maps, David Wainana of \u003cem\u003eicipe\u003c/em\u003e for the assistance during field sample collection and John Gachoya for mosquito identification. Special thanks are extended to the homeowners and cattle farmers for their co-operation and for granting us access to their property for mosquito sampling.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors gratefully acknowledge the financial support for this research by the following organizations and agencies: the European Union\u0026rsquo;s Horizon 2020 research and innovation programme under grant agreement No. 101000365 (PREPARE4VBD); the Swedish International Development Cooperation Agency (Sida); the Swiss Agency for Development and Cooperation (SDC); the Australian Centre for International Agricultural Research (ACIAR); the Government of Norway; the German Federal Ministry for Economic Cooperation and Development (BMZ); and the Government of the Republic of Kenya. The views expressed herein do not necessarily reflect the official opinion of the donors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAvailability of data and materials\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe sequences generated and analyzed during the current study have been deposited at the NCBI GenBank database under accession PZ069361\u0026ndash;PZ069368.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthors\u0026rsquo; contributions\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDG\u003c/strong\u003e: Conceptualization, Investigation, Methodology, Data curation, Formal analysis, Software, Validation, Writing \u0026ndash; original draft. \u003cstrong\u003eSM\u003c/strong\u003e: Supervision, Validation, Writing \u0026ndash; review \u0026amp; editing. \u003cstrong\u003eOE\u003c/strong\u003e: Investigation, Data curation, Formal analysis, Software, Writing \u0026ndash; review \u0026amp; editing. \u003cstrong\u003eEY\u003c/strong\u003e: Formal analysis, Software, Writing \u0026ndash; review \u0026amp; editing. \u003cstrong\u003eJK\u003c/strong\u003e: Formal analysis, Writing \u0026ndash; review \u0026amp; editing. \u003cstrong\u003eRK\u003c/strong\u003e: Formal analysis, Software, Writing \u0026ndash; review \u0026amp; editing. \u003cstrong\u003eJV\u003c/strong\u003e: Conceptualization, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Software, Validation, Writing \u0026ndash; review \u0026amp; editing. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by Pwani University Ethics Review Committee (Ref: ERC/EXT/002/2020E) and National Commission for Science, Technology \u0026amp; Innovation (NACOSTI) (Ref: NACOSTI/P/24/38943). Mosquitoes were sampled using CDC light traps placed in the vicinity of cattle enclosures; no animals or humans were handled during the study. Prior to trap placement, livestock owners were briefed about the study and informed oral consent was obtained from the household heads before proceeding with trapping of mosquitoes on their property.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eVieira CJSP, Gyawali N, Onn MB, Shivas MA, Shearman D, Darbro JM, et al. Mosquito bloodmeals can be used to determine vertebrate diversity, host preference, and pathogen exposure in humans and wildlife. 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Using haematophagous fly blood meals to study the diversity of blood-borne pathogens infecting wild mammals. Mol Ecol Resour. 2022;22:2915\u0026ndash;27. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/1755-0998.13670\u003c/span\u003e\u003cspan address=\"10.1111/1755-0998.13670\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\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":"parasites-and-vectors","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"parv","sideBox":"Learn more about [Parasites \u0026 Vectors](http://parasitesandvectors.biomedcentral.com/)","snPcode":"13071","submissionUrl":"https://submission.nature.com/new-submission/13071/3","title":"Parasites \u0026 Vectors","twitterHandle":"@bugbittentweets","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Xenosurveillance, mosquitoes, tick-borne pathogens, vector-borne pathogens, Anaplasma spp., Neoehrlichia, Candidatus Neoehrlichia mikurensis","lastPublishedDoi":"10.21203/rs.3.rs-9010968/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9010968/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eHematophagous flies can serve as sentinels for detecting vertebrate pathogens or host antibodies present in the blood they ingest. Xenosurveillance, which uses blood-feeding insects as biological samplers, is emerging as a sensitive and minimally invasive approach for monitoring pathogens circulating among humans, livestock, and wildlife. However, despite its growing application in human health, the use of xenosurveillance for detecting pathogens in livestock systems, particularly within complex human\u0026ndash;animal\u0026ndash;wildlife interfaces, remains underexplored. To date, few studies have assessed whether mosquito blood-meals can reliably capture livestock-associated bacterial pathogens. Our study investigated whether blood-meals from mosquitoes could be used to detect infectious agents circulating in livestock in Kenya.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe collected a total of 4,673 mosquitoes, belonging to \u003cem\u003eCulex\u003c/em\u003e, \u003cem\u003eAnopheles\u003c/em\u003e, \u003cem\u003eAedes\u003c/em\u003e, \u003cem\u003eMansonia\u003c/em\u003e, and \u003cem\u003eCoquillettidia\u003c/em\u003e genera around livestock enclosures in Kajiado and Naivasha counties, Kenya. Blood-fed mosquitoes were examined for the presence of \u003cem\u003eAnaplasma\u003c/em\u003e, \u003cem\u003eEhrlichia\u003c/em\u003e, \u003cem\u003eRickettsia, Theileria\u003c/em\u003e, and \u003cem\u003eBabesia\u003c/em\u003e pathogens using molecular tools and gene sequencing.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOverall, we detected \u003cem\u003eAnaplasma marginale\u003c/em\u003e in \u003cem\u003eCulex pipiens\u003c/em\u003e (1/150; 0.7%) and \u003cem\u003eAedes hirsutus\u003c/em\u003e (2/11; 18.2%), \u003cem\u003eAnaplasma\u003c/em\u003e sp. in \u003cem\u003eCx. pipiens\u003c/em\u003e (2/150; 1.4%) and \u003cem\u003eAe. hirsutus\u003c/em\u003e (1/11; 9.1%), and \u003cem\u003eCandidatus\u003c/em\u003e Neoehrlichia mikurensis was found only in \u003cem\u003eMansonia africana\u003c/em\u003e (2/50; 4%). Pathogen detections showed strong host concordance where \u003cem\u003eA. marginale\u003c/em\u003e was associated with cattle-derived blood-meals and \u003cem\u003eAnaplasma\u003c/em\u003e sp. with goat-derived blood-meals, while \u003cem\u003eCandidatus\u003c/em\u003e Neoehrlichia mikurensis was detected in \u003cem\u003eMansonia africana\u003c/em\u003e that had fed on cattle and on a host that could not be determined due to amplification failure.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003e \u003cem\u003eCandidatus\u003c/em\u003e Neoehrlichia mikurensis is a recognized zoonotic pathogen, and detection represents the first report of its presence in mosquitoes in Africa. Although mosquitoes are not biological vectors of these pathogens, the presence of pathogen DNA in their blood-meals reveals circulation of the pathogens in livestock in Kenya. Our findings demonstrate that mosquito-based xenosurveillance offers a simple, scalable, and non-invasive method for detecting circulating vector-borne pathogens in livestock-human-wildlife ecosystems, supporting its value as an emerging tool for integrated biosurveillance.\u003c/p\u003e","manuscriptTitle":"Mosquito-based xenosurveillance reveals circulation of Anaplasma and Neoehrlichia in livestock at a human–wildlife interface in Kenya","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-16 15:26:43","doi":"10.21203/rs.3.rs-9010968/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-26T11:05:12+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-24T13:21:42+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-17T14:49:21+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"308987417957461407240127544191110030055","date":"2026-03-16T13:03:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"263874990753044055999745112535060126900","date":"2026-03-13T15:03:32+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-13T11:49:37+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-08T06:11:41+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-06T10:17:03+00:00","index":"","fulltext":""},{"type":"submitted","content":"Parasites \u0026 Vectors","date":"2026-03-02T13:48:59+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"parasites-and-vectors","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"parv","sideBox":"Learn more about [Parasites \u0026 Vectors](http://parasitesandvectors.biomedcentral.com/)","snPcode":"13071","submissionUrl":"https://submission.nature.com/new-submission/13071/3","title":"Parasites \u0026 Vectors","twitterHandle":"@bugbittentweets","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3cbdda46-ae89-4db6-92a3-7ca5e6d28f05","owner":[],"postedDate":"March 16th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-05-18T17:23:31+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-16 15:26:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9010968","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9010968","identity":"rs-9010968","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}