Bionomics and distribution of malaria vectors in Kisumu city, Western Kenya: Implications for urban malaria transmission  

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Machani, Shirley A. Onyango, Irene Nzioki, Sylvia Milanoi, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4943539/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 15 Mar, 2025 Read the published version in Malaria Journal → Version 1 posted 10 You are reading this latest preprint version Abstract Background Increasing urbanization in tropical Africa may create new niches for malaria vectors, potentially leading to higher disease transmission rates. Vector control efforts remain largely targeted at ecologically rural bio-complexities with multiple hosts. Understanding mosquito species composition, ecology, host diversity and biting behavior in urban areas is crucial for planning effective control. This study assessed mosquito species diversity, abundance, behavioral patterns, and Plasmodium sporozoite infection rates of Anopheles vectors along an urban-rural transect in Kisumu city, western Kenya. Methods Indoor and outdoor host-seeking and resting adult mosquitoes were collected using Centers for Disease Control and Prevention miniature light traps (CDC-LT) and mechanical aspirators (Prokopack) along an urban-rural transect. Females Anopheles mosquitoes collected were identified using morphological taxonomic keys to species level. Specimens belonging to the Anopheles gambiae complex and Anopheles funestus group were further processed using polymerase chain reaction (PCR) to identify members of each complex/group. Subsequently, sporozoite infection rates of the anopheline mosquitoes were determined using a multiplexed real-time quantitative PCR (qPCR) assay. Result A total of 3,394 female Anopheles mosquitoes were collected and identified. These comprised of An. gambiae s.l. (68%), An. funestus group (19.8%), An. coustani (7.8%), An. pharoensis (2.6%), An. maculipalipis (1.6%), and An. leesoni (0.2%). All six species were found in urban zone, but only three were found in peri-urban and rural sites. Overall, urban collections accounted for the majority of these collections (55.5%) of mosquitoes collected, followed by those from peri-urban (30%) and rural sites (14.5%). Species distribution across the three ecotypes showed Anopheles arabiensis was the dominant species in urban (84.3%) and peri-urban (89%) sites, while An. gambiae s.s. was predominantly found in the rural zone (60.2%) alongside An. arabiensis (39.7%). Anopheles funestus was the predominant species in peri-urban (98.4%) and rural (85.7%) areas, with An. leesoni accounted for 1.6% and 14.3%, respectively. In urban areas, all samples from the An. funestus group were identified as An. funestus s.s.. Majority (55.5%) of Anopheles mosquitoes were collected indoors, while secondary vectors were primarily caught outdoors. Overall, sporozoite rates were higher outdoors 3.5% compared to indoors 1.45% in rural areas. Specifically, sporozoite infectivity rates for An. funestus , An. gambiae s.s and An. arabiensis collected indoors in the rural zone was 2.5%, 1.4% and 1% respectively. Outdoors in rural areas, An. gambiae had a sporozoite rate of 5.3%, while An. arabiensis had a rate of 2.1%. In peri-urban areas An. gambiae had a sporozoite rate of 2.3%. No sporozoites were detected in samples from urban sites. Conclusion The study highlights a shift of diversity of Anopheles species towards urban areas with increased outdoor activity, and significant outdoor malaria transmission in rural and peri-urban areas, emphasizing the need for tools targeting outdoor-biting mosquitoes. The presence of An. funestus in urban settings is of interest and highlights the critical importance of sustained entomological surveillance to inform integrated vector control and prevent future transmission risks. Anopheles malaria Anopheles density species composition sporozoite infection urban city Figures Figure 1 Figure 2 Figure 3 Background The sustained global malaria control campaign has made remarkable progress in reducing malaria morbidity and mortality, primarily by scaling up vector control tools and improving malaria case management ( 1 ). Nevertheless, recent findings from the World Health Organization (WHO) indicate that further reductions in malaria prevalence in Africa are not as significant, with progress stalling in several regions of sub-Saharan Africa where the disease remains widespread ( 2 ). The campaigns have predominantly focused on rural areas, overlooking urban centers where malaria prevalence has traditionally been low. However, malaria is now considered an emerging threat in rapidly urbanizing areas of sub-Saharan Africa ( 3 , 4 ) highlighting the need to monitor vector populations and implement long-term interventions in the neglected urban environments. This oversight has gained significant attention, particularly with the recent establishment and spread of the invasive urban vector Anopheles stephensi , which is likely to alter disease risk landscape in Africa ( 5 – 7 ). In response to these challenges, the WHO introduced a framework supporting the control and elimination of malaria in urban environments, marking the beginning of efforts to address malaria in urban settings ( 8 ). Urbanization, often associated with human development and progress, can also lead to significant inequalities and health problems ( 9 , 10 ). The prevalence of Anopheles mosquitoes and malaria transmission in urban environments can be influenced by various factors, including housing conditions, land use patterns, population density, transportation/migration, and waste generation/pollution, among other anthropogenic practices ( 11 – 14 ). Peri-urban locations, which combine urban and rural characteristics, is likely to experience unique challenges due to changing environmental conditions and socioeconomic factors ( 15 ). Rural areas, with diverse ecological conditions and traditional practices, typically have higher mosquito densities and infection rates ( 16 – 18 ). However, many cities are now experiencing increased urban agriculture, poor drainage systems, broken and open sewers and inadequate housing due to rapid urbanization. These conditions create ideal environments for vector breeding and facilitate their entry into homes, significantly increasing the risk of exposure to malaria vectors ( 18 – 20 ). In addition, changing rainfall patterns may increase the availability and suitability of vector breeding habitats. Therefore, understanding mosquito-borne diseases in cities will require an integrative approach that combines ecological findings with their social context ( 21 ). Although malaria vectors are uncommon in urban settings, they have adapted to human-induced changes, including climate change, which can potentially increase the risk of malaria transmission ( 22 , 23 ). Over half the world’s population (4.2 billion people) now live in urban areas with the number expected to reach 9.7 billion by 2050. The proportion of urban residents in Africa is projected to increase from 36% in 2010 to 50% by 2030 and 60% by 2050 ( 24 ). In developing cities, large populations, particularly the poor, face significant challenges and often turn to activities like urban farming, which create favorable conditions for mosquitoes ( 25 ). High mobility from malaria-endemic rural areas and rural practices in urban regions, along with the recent presence of invasive species such as Anopheles stephensi ( 6 , 26 ) and climate change ( 27 , 28 ) in Kenya and other developing African cities, underscores the need for a robust mosquito surveillance in the urban centers. The main aim of this study was to assess malaria vector diversity, species composition, host-seeking and resting behaviors, and their contributions towards indoor and outdoor malaria transmission across urban, peri-urban and rural settings to provide critical insights for integrated malaria control strategies and targeted mitigation measures in urban areas. Method Description of Study Area The study was conducted in an urban-rural continuum in Kisumu County in Western Kenya. Kisumu (00°06′S 034°45′E) is the third largest urban settlement in Kenya with a population of approximately 610,000 people and is located 10 km south of the equator on Lake Victoria. The city lies on the northeastern shore of Lake Victoria with an elevation of approximately 1,140 m above sea level. Kisumu city experiences a humid climate with an average relative humidity of 70%. Western Kenya has two distinct rainy seasons: a long rainy season from March to May and short rains in September through December. The extended dry season spans from January to March, with a shorter dry period from August to September. Annual rainfall typically ranges between 1,000 and 1,500 mm. Thirteen sites were randomly selected along an urban-rural transect from Kisumu city spanning a distance of 30 km. Among these, five locations: Nyalenda, Gesoko, Migosi, Mamboleo and Bandani were surveyed within the urban Kisumu and are characterized by dense urbanization. These sites all are informal residences located within the city). There were four sites in the peri-urban area: Kotetni, Kandalo, Tiengre and Kisian. The four rural locations sampled included Ojola, Mainga, Chulaimbo and Marera, which are approximately 30 km from the city (Fig. 1 ). Kisumu city is a major regional transportation hub where populations are engaged in formal and informal economic activity( 18 ). Anopheles mosquito species in the peri-urban and rural of western Kenya lowlands include Anopheles arabiensis , An. funestus , and An. gambiae ( 29 , 30 ). Adult Anopheles collection To determine the abundance of indoor and outdoor biting and resting adult female Anopheles mosquitoes in urban, peri-urban, and rural clusters, sampling was conducted from September 2022 to September 2023. CDC light traps (Model 512; John W. Hock Company, Gainesville, FL, USA) and mechanical aspirators (Prokopack) were used for these collections. For indoor and outdoor biting mosquitoes, battery-powered CDC light traps were hung at the foot end of the bed approximately 1.5 meters above the floor with a sleeping person protected under bednet indoors from 18:00 h to 06:00 h. and outdoors within 2 meters of sentinel houses ( 31 ). Collections were conducted in the morning from 6:00 h to 07:00 h. The trapping was done for four consecutive nights in five randomly selected houses in each cluster per zone. Prokopack aspirator (John W Hock, Gainesville, FL, USA) was used to collect indoor and outdoor resting mosquitoes from ten randomly selected houses every morning (06:00 h to 10:00 h) for four days in each cluster per zone. Indoor collections targeted mosquitoes resting on hunged clothes, walls, furniture, under roofs or ceilings, and under beds. Outdoor sampling included open containers, water reservoirs, outdoor kitchens, animal sheds, and outdoor human resting points. Each collection session in a house (both indoors and outdoors) lasted for approximately 20 minutes. Mosquitoes from each house and collection method were sorted, classified according to their gonotrophic status, and morphologically identified as Anopheles species following the recent taxonomic keys ( 32 ). Mosquitoes from each collection method were stored in vials labeled separately and preserved by desiccation. Different houses were visited throughout the study period. Identification of vector species complexes A subset of members of An. gambiae s.l. and An. funestus s.l. groups randomly selected from indoor and outdoor collections from each cluster per zone were identified to species by polymerase chain reaction (PCR), following the protocols developed by Scott et al. for An. gambiae s.l. ( 33 ) and Koekemoer et al. for An. funestus s.l. ( 34 ). Molecular detection of Sporozoite infections The head and thorax of the preserved Anopheles mosquito specimens were carefully separated from the abdomen, and DNA extracted from head/thorax using the alcohol precipitation method ( 35 ). The DNA was analyzed to determine sporozoite infections of Plasmodium species using a multiplexed real-time quantitative PCR (qPCR) assay. The assay was performed using the published species-specific 18 s ribosomal RNA probes and primers for P. falciparum , P. malariae , and P. ovale ( 36 , 37 ). Data management and analysis Vector densities from indoor and outdoor night collections were calculated as the number of female mosquitoes per trap/night for each collection method. Analysis of variance (ANOVA) was used to compare malaria vector density between indoor and outdoor locations. Differences in composition and abundance of mosquitoes between sites and locations were tested using chi-squared tests. The sporozoite rate was calculated as the proportion of Anopheles mosquito samples tested that turned positive for Plasmodium species. Data were stored in Microsoft Excel 2010 datasheets and analysis done using R statistical software (version 4.0.3; R foundation for Statistical Computing, Vienna, Austria). Result Mosquito species composition and abundance During the study period, a total of 27,483 mosquitoes were collected, comprising 14,478 host-seeking and 13,005 resting mosquitoes, across urban, peri-urban, and rural sites. Culex spp . constituted the majority of the samples 87.6% (n = 24,089), while Anopheles spp . accounted for 12.4% (n = 3,394). The highest number of mosquitoes was collected in the urban zone, comprising 49.4% (n = 13,579) of the total captures. This was followed by the peri-urban zone with 37% (n = 10,164) and rural zone with 13.6% (n = 3,740) (Table 1 ). Table 1 Morphologically identified adult mosquitoes samples by zones (urban, peri-urban and rural) based on sampling method and location in Kisumu city. Zone Mosquito species Indoor Outdoor Total LT Aspiration Total LT Aspiration Total Urban An.gambiae s.l. 453 29 482 455 105 560 1042 An.funestus grp 354 24 378 90 12 102 480 An. coustani grp 21 0 21 195 0 195 216 An.maculipalipis 4 2 6 22 25 47 53 An.pretoriensis 13 3 16 37 36 73 89 An.pharoensis 0 0 0 3 0 3 3 Total Anopheles 845 58 903 802 178 980 1883 Culex spp 3663 2182 5845 4389 1462 5851 11696 Peri-urban An.gambiae s.l 227 309 536 151 211 362 898 An.funestus grp 40 23 63 18 5 23 86 An. coustani grp 2 0 2 31 1 32 34 Total Anopheles 269 332 601 200 217 417 1018 Culex spp 2021 3339 5360 1748 2038 3786 9146 Rural An.gambiae s.l. 180 108 288 62 19 81 369 An.funestus grp 54 36 90 13 6 19 109 An. coustani grp 3 0 3 10 0 10 13 An. pharaoensis 0 0 0 2 0 2 2 Total Anopheles 237 144 381 87 25 112 493 Culex spp 740 648 1388 470 1389 1859 3247 Table 2: Sporozoite rates of Anopheles mosquitoes from indoor and outdoor collections in Urban, peri-urban and rural zones in Kisumu, western Kenya Study zone and Anopheles species Parameters Indoor Outdoor Overall LT Aspiration Total LT Aspiration Total Urban An.gambiae s.s No.tested 39 2 41 41 10 51 92 Pf + Ve (%) 0 0 0 0 0 0 0 An.arabiensis No.tested 221 21 242 189 80 269 511 Pf + Ve (%) 0 0 0 0 0 0 0 An.funestus s.s. No.tested 76 15 91 27 0 27 118 Pf + Ve (%) 0 0 0 0 0 0 0 An. coustani No.tested 3 0 3 48 0 48 51 Pf + Ve (%) 0 0 0 0 0 0 0 An.ziemanni No.tested 0 0 0 26 0 26 26 Pf + Ve (%) 0 0 0 0 0 0 0 An.maculipalipis No.tested 1 0 1 22 15 37 38 Pf + Ve (%) 0 0 0 0 0 0 0 An.pretoriensis No.tested 8 0 8 35 31 66 74 Pf + Ve (%) 0 0 0 0 0 0 0 Peri-urban An.gambiae s.s No.tested 35 18 53 20 23 43 96 Pf + Ve (%) 0 0 0 0 1(4.4) 1 (2.3) 1(1.0) An.arabiensis No.tested 223 188 411 152 165 317 728 Pf + Ve (%) 0 0 0 0 0 0 0 An.funestus s.s. No.tested 8 2 10 3 2 5 15 Pf + Ve (%) 0 0 0 0 0 0 0 An. coustani No.tested 0 0 0 21 0 21 21 Pf + Ve (%) 0 0 0 0 0 0 0 Rural An.gambiae s.s No.tested 96 43 139 23 15 38 177 Pf + Ve (%) 0 2(4.7) 2(1.4) 0 2(13.3) 2(5.3) 4(2.3) An.arabiensis No.tested 58 41 99 43 5 48 147 Pf + Ve (%) 1(1.7) 0 1(1.0) 0 1(20) 1(2.1) 2(1.4) An.funestus s.s. No.tested 25 15 40 1 1 2 42 Pf + Ve (%) 0 1(6.7) 1(2.5) 0 0 0 1(2.4) An.leesoni No.tested 1 0 1 4 3 7 8 Pf + Ve (%) 0 0 0 0 0 0 0 Anopheline mosquito species composition and abundance Overall, a total of 3,394 adult female Anopheles mosquitoes, comprising six species, were collected over the study period. Of these, 55.5% (n = 1,883) were from the urban zone, 30% (n = 1,018) from the peri-urban zone, and 14.5% n = 493 from the rural zone (Table 1 ). The difference in the distribution of anopheline mosquito species between the study sites was statistically significant (F 2, 1092 = 14.45, P < 0.001). Overall, Anopheles gambiae s.l. was the predominant species, comprising 68% (n = 2,309) of the total collection. This was followed by An. funestus group (19.8%, n = 675), An. coustani group (7.8%, n = 263), An. pretoriensis (2.6%, n = 89), An. maculipalpis (1.6%, n = 53), and An. pharoensis (0.2%, n = 5). In the urban zone, Anopheles gambiae s.l was the most abundant 55.3% (n = 1042) followed by An. funestus group 25.5% (n = 480), An. coustan i group 11.5% (n = 216), An. pretoriensis 4.7% (n = 89), An. maculipalipis 2.8% (n = 53) and An. pharoensis 0.2% (n = 3). Out of 1,018 Anopheles females collected in peri-urban, 88.2% (n = 898) were An. gambiae s.l, 8.4% (n = 86) An. funestus group and 3.3% (n = 34) An. coustani group. In rural zone, An. gambiae s.l was predominant species 74.8% (n = 396) followed by An. funestus group 22.1% (n = 109), An. coustani group 2.6% (n = 13) and An. pharoensis 0.4% (n = 2). Indoor and outdoor Anopheles mosquito composition Overall, the majority of anophelines (55.5%, n = 1885) were collected indoors across the three zone. In urban, peri-urban, and rural sites, more Anopheles mosquitoes were host-seeking indoors [51.3% (95% CI 48.8–53.7%), 57.3% (95% CI 52.8–61.8%), and 73.1% (95% CI 68.3–78%), respectively] than outdoors [48.7% (95% CI 46.3–51.1%), 42.6% (95% CI 38.2–47.1%), and 26.8% (95% CI 22-31.8%), respectively]. The mean indoor host-seeking density for the An. funestus group in urban zone was significantly higher than the outdoor density ( t 74 = 2.67, p 0.05). The secondary vectors mean outdoor host-seeking densities were marginally significant compared to the indoor densities for An. maculipalipis ( t 9 = 1.96, p < 0.04) and An. coustani group ( t 42 = 2.15, p < 0.02). The proportion of outdoor host seeking An. pretoriensis was higher 74% (95% CI 61.8–86.2%) compared to indoors 26% (95% CI 13.8–38.2%). There was no significant difference in the mean indoor and outdoor host-seeking densities for An. gambiae s.l. and the An. funestus group (p > 0.05) in the peri-urban sites. The mean indoor host-seeking density for the An. gambiae s.l was significantly higher than the outdoor density ( t 94 = 2.3, p 0.05) in the rural zone. Most members of the An. coustani group were host-seeking outdoors in both peri-urban [94% (95% CI 85.7–100%)] and rural areas [76.9% (95% CI 54-99.8%)]. The majority of female Anopheles mosquitoes were caught resting outdoors [75.4% (95% CI 70–81%)] compared to indoors [24.6% (95% CI 19.1–30%)] in the urban zone. Conversely, in the peri-urban and rural sites, most female Anopheles mosquitoes were caught resting indoors [60.5% (95% CI 56.4–64.6%) and 85.2% (95% CI 79.8–90.5%), respectively] than outdoors [39.5% (95% CI 35.4–43.6%) and 14.8% (95% CI 9.4–20.1%), respectively]. The mean outdoor resting density of An. gambiae s.l in urban was significantly higher than indoor density ( t 66 = 2.2, p 0.05) (Fig. 2 A). The majority of An. maculipalipis 93% (95% CI 82.7–100%) and An. pretoriensis 92.3% (95% CI 83.9-100.6%) were resting outdoors. The difference in mean indoor and outdoor resting densities for An. gambiae s.l and An. funestus group in peri-urban were not significant (p > 0.05) (Fig. 2 B). In Rural, the mean indoor resting density of An. gambiae s.l was higher than outdoor ( t 69 = 1.76, p < 0.042) (Fig. 2 C). The proportion of An. funestus group caught resting indoors 85.7% (95% CI 75.1–96.3%) was higher than outdoor 14.3% (95% CI 3.7–24.9%). Anopheles gambiae and Anopheles funestus sibling species composition A total of 2,170 specimens (1,896 An. gambiae s.l. and 274 An. funestus group) were used for molecular assay to discriminate respective sibling species. Anopheles arabiensis was the predominant sibling species in both the urban (84.3%) and peri-urban (89%) sites, while An. gambiae accounted for 15.7% and 11% in these sites, respectively. In contrast, in the rural zone, An. gambiae s.s. (hereafter An. gambiae ) was the most abundant species (60.2%), compared to An. arabiensis (39.7%). All the An. funestus group samples assayed from the urban zone were An. funestus s.s. (hereafter An. funestus ) (Fig. 3 A). In the peri-urban and rural sites, An. funestus was the dominant species (98.4% and 85.7%, respectively), while An. leesoni accounted for 1.6% and 14.3%, respectively (Fig. 3 B&C). Overall, there was a significant difference between indoor and outdoor locations in terms of An. funestus group species composition (χ 2 = 21.34, df = 1, p < 0.001). Sporozoite infectivity rates Sporozoite infectivity rate was used as a proxy for establishing Plasmodium infection rates. Out of the 2,170 mosquitoes tested, 8 specimens turned positive for sporozoites (i.e. 5 An. gambiae , 2 An. arabiensis , and 1 An. funestus ). Of these, one sample was from the peri-urban zone and seven from the rural zone. In the peri-urban zone, 2.3% (1/43) of An. gambiae collected outdoors tested positive for sporozoite. The Sporozoite rate for An. gambiae in the rural zone was 1.4% (2/139) indoors and 5.3% (2/38) outdoors. The sporozoite rate for An. arabiensis was 1% (1/99) indoors and 2.1% (1/48) outdoors. Additionally, 2.5% (1/40) of An. funestus collected indoors tested positive for sporozoites. Overall, the sporozoite rates were higher for samples collected outdoors 3.5% (3/86) than indoors 1.45% (4/278) in rural areas. None of the samples tested from urban zone were positive (Table 2). Discussion With over half of the world’s population now residing in urban areas and projections suggesting this could rise to 75% by 2050 ( 38 ), rapid urbanization, often coupled with economic decline, has the potential to profoundly affect malaria epidemiology and control, thereby raising the disease burden in urban populations ( 9 , 39 ). A major global public health concern is whether the rapid urbanization experienced in most developing African cities will shift malaria from rural to urban areas( 40 ). Gaining insight into mosquito species composition, ecology, and biting behavior in these developing African cities is essential for implementing effective vector control strategies ( 41 ). This study found a surprisingly higher species diversity of anopheline mosquitoes in urban areas which was even higher compared to peri-urban and rural areas. The predominant vector was An. gambiae s.l. with An. arabiensis population being the highest in urban and peri-urban areas, while An. gambiae dominated the rural areas. The higher numbers of An. arabiensis in the city corroborates similar studies in West Africa, which have demonstrated the increased adaptability of this species in urban environments ( 42 , 43 ). This adaptability may be facilitated by urbanization-induced environmental changes, such as higher temperatures and lower humidity, which favor its survival ( 44 ). The abundance of Anopheles gambiae in rural areas can be attributed to its preference for unpolluted waters, which are commonly found in such settings. In contrast, urban environments, characterized by polluted waters, are less conducive to the survival of this species. However, instances of this species adapting to urban environments have been documented in Cameroon, West Africa ( 45 ). The presence of An. funestus , a significant malaria vector in rural sub-Saharan Africa, in urban areas is concerning as it could potentially sustain high levels of malaria transmission within cities. Reports of this species in urban areas of West Africa highlight their expansion to new niches thereby increasing the risk of malaria ( 45 ). In addition to primary vectors, secondary vectors such as An. coustani group, An. pretoriensis , An. maculipalipis and An. pharaonsis were abundant in urban areas, unlike the rural and peri-urban settings where only the An. coustani group and An. pharaonsis were observed. A recent study from rural western Kenya reported an increase in secondary vectors ( 46 ) compared to previous findings ( 47 ). The co-occurrence of primary and secondary vectors in the urban zone is concerning as it may lead to increased risk of malaria transmission. Studies have shown that many secondary vectors prefer outdoor resting and biting, allowing them to sustain transmission even after indoor control measures, like insecticide-treated bed nets, have reduced primary vectors ( 48 , 49 ). Some of the likely factors contributing to their occurrence in urban environments could be due to climate changes and unprecedented land-use contributing to their survival in urban environments ( 28 , 48 ). The adaptation of the secondary vectors to the urban environment highlights the need for additional vector control interventions that target the behavior of these vectors, as well as a better understanding of their biology and role in urban malaria epidemiology to inform targeted interventions. Consistent with previous studies in western Kenya ( 47 , 50 , 51 ), An. arabiensis was found to seek hosts and rest outdoors more frequently than indoors in urban and rural sites but showed no such preference in peri-urban areas. This variability may be influenced by ecological factors and implemented indoor vector control measures ( 52 , 53 ), challenging the traditional indoor-focused interventions. Conversely, An. funestus and An. gambiae consistently exhibited indoor host-seeking and resting behaviors despite the use of LLINs, likely as a result of high insecticide resistance ( 51 , 54 ). Moreover, these behaviors may also be influenced by poor housing conditions, which frequently fail to prevent mosquitoes from entering homes. While urbanization often improves infrastructure and housing quality, providing better mosquito-proof environments and healthcare access, this improvement may not extend to many developing African cities with slum-like conditions, as observed in this study. Thus, effective vector control strategies like house screening and larval source management are necessary to mitigate mosquito entry and outdoor mosquito activities in such settings. Secondary vectors like An. maculipalipis , An. coustani , An. pretoriensis , and An. pharaoensis showed increased outdoor activity, particularly in urban areas, potentially evading primary interventions and sustaining malaria transmission. Their ability to harbor Plasmodium parasites( 46 , 55 ) emphasizes their significant epidemiological impact, highlighting the need for robust entomological surveillance and targeted vector control strategies. Malaria persistence is linked to behavioral changes in anopheline mosquitoes ( 56 ). This study found that most malaria transmission by An. funestus likely occurs indoors in rural areas, confirming its significant role in indoor transmission. Conversely, An. arabiensis and An. gambiae may be more involved in outdoor transmission, with An. gambiae potentially driving outdoor malaria transmission in peri-urban areas. Overall, most transmission occurred outdoors in rural and peri-urban areas, suggesting that indoor vector control methods like LLINs and IRS alone may not be sufficient, as outdoor-biting vectors pose a significant threat to elimination efforts. Despite the high numbers of malaria vectors in urban areas, which could suggest ongoing malaria transmission, no Plasmodium infections were detected in the tested mosquitoes. This absence of detection could be due to the limitations of the CDC LT trap in high-light urban environments. In western Kenya, CDC light traps in areas dominated by An. arabiensis have been found to capture a higher proportion of younger mosquitoes, confirmed by parity dissections( 57 ). Additionally, urban-adapted malaria vectors have been reported to have a shorter lifespan compared to rural counterparts (4.1 days versus 11 days) ( 58 ), potentially limiting their ability to transmit the parasite. Although this parity and survivorship information were not considered in the current analysis, integrating these factors in future research could enhance our understanding of mosquito population dynamics in urban areas. Nonetheless, studies in West Africa have implicated An. arabiensis and An. funes tus to urban malaria transmission, necessitating the need for tailored urban-specific vector control strategies. It is concerning that secondary vectors such as An. coustani , An. pretoriensis , and An. pharoensis , despite their tendency to feed on animals, have been found susceptible to Plasmodium infections ( 46 , 47 , 55 ). The complex behaviors and species diversity of these vectors in urban areas, pose a significant challenge to malaria elimination efforts that rely solely on indoor vector control, underscoring the need for ongoing adoption of integrated control strategies. Conclusion The study revealed a high diversity of Anopheles species in urban areas, with significant outdoor activity. The detection of An. funestus in urban environments is concerning due to its established role in malaria transmission in rural areas, where malaria is high. Notably, outdoor malaria transmission was prevalent in rural and peri-urban regions, emphasizing the need to adapt and diversify interventions targeting outdoor-biting and resting mosquitoes. These findings highlight the importance of increased routine entomological surveillance in urban areas. Implementing integrated vector control measures, including larval source management, house modifications such as screening windows and eaves, and improved urban planning, is crucial for effective urban vector control. Declarations Ethics approval and consent to participate: The study was approved by the Maseno University Ethics Review Committee (MUERC Protocol No. 00456) and the University of California, Irvine Institutional Review Board (UCI IRB) and received authorization from the Ministry of Health, Kenya. Written informed consent was sought from household heads before data were collected from the households. All experiments and methods were carried out in accordance with the relevant guidelines and regulations of MUERC and UCI-IRB. Availability of data and materials The dataset supporting the conclusions of this article is included within the article and its supplementary information files. Competing interest The authors have declared that no competing interest. Authors’ contribution MGM, EO, YAA and GY conceived and designed the study. MGM, SAO, IN, SM, GN participated in the field work and laboratory analysis, MGM did data analysis and drafted the manuscript. MCL determined the study site demarcations, MGM, SAO, GN, HA, JG and CW supervised data collection and edited the draft manuscript writing. The final manuscript was edited by GZ, AG, EO, YAA and GY. All authors read and approved the final version of the manuscript. Acknowledgments The authors wish to thank the volunteers for their participation in this study and the leadership of Kisumu County for allowing us to conduct the study in the area. We acknowledge the Entomology Laboratory at Kenya Medical Research Institute, Kisumu, the field assistants in urban, peri-urban and rural areas for providing technical support. Funding This study was supported by grants from the National Institute of Health (R01 AI123074, U19 AI129326, R01 AI050243, D43 TW001505). There was no additional external funding received for this study. References Bhatt S, Weiss D, Cameron E, Bisanzio D, Mappin B, Dalrymple U, et al. The effect of malaria control on Plasmodium falciparum in Africa between 2000 and 2015. Nature. 2015;526(7572):207–11. WHO. World Malaria Report 2022. Geneva: World Health Organisation; 2023. Lohnert B. Migration and the rural-urban transition in Sub-Saharan Africa. Humboldt-Universität zu Berlin; 2017. 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Mwangangi JM, Midega J, Kahindi S, Njoroge L, Nzovu J, Githure J, et al. Mosquito species abundance and diversity in Malindi, Kenya and their potential implication in pathogen transmission. Parasitol Res. 2012;110:61–71. Hay SI, Shanks GD, Stern DI, Snow RW, Randolph SE, Rogers DJ. Climate variability and malaria epidemics in the highlands of East Africa. Trends Parasitol. 2005;21(2):52–3. Mzilahowa T, Luka-Banda M, Uzalili V, Mathanga DP, Campbell CH Jr, Mukaka M, Gimnig JE. Risk factors for Anopheles mosquitoes in rural and urban areas of Blantyre District, southern Malawi. Malawi Med J. 2016;28(4):154–8. Keating J, Macintyre K, Mbogo C, Githeko A, Regens JL, Swalm C, et al. A geographic sampling strategy for studying relationships between human activity and malaria vectors in urban Africa. Am J Trop Med Hyg. 2003;68(3):357–65. Yadouléton A, N'guessan R, Allagbé H, Asidi A, Boko M, Osse R, et al. The impact of the expansion of urban vegetable farming on malaria transmission in major cities of Benin. Parasites Vectors. 2010;3:1–7. De Silva PM, Marshall JM. Factors contributing to urban malaria transmission in sub-saharan Africa: A systematic review. J Trop Med. 2012;2012(1):819563. Evans MV, Bhatnagar S, Drake JM, Murdock CC, Mukherjee S. Socio-ecological dynamics in urban systems: an integrative approach to mosquito‐borne disease in Bengaluru, India. People Nat. 2022;4(3):730–43. Doumbe-Belisse P, Kopya E, Ngadjeu CS, Sonhafouo-Chiana N, Talipouo A, Djamouko-Djonkam L et al. Urban malaria in sub-Saharan Africa: dynamic of the vectorial system and the entomological inoculation rate. 2021;20(1):364. De Silva PM, Marshall JM. Factors contributing to urban malaria transmission in sub-Saharan Africa: a systematic review. Journal of tropical medicine. 2012;2012. Dorling D. World population prospects at the UN: our numbers are not our problem? The struggle for social sustainability. Policy; 2021. pp. 129–54. Yadouléton A, N'guessan R, Allagbé H, Asidi A, Boko M, Osse R, et al. The impact of the expansion of urban vegetable farming on malaria transmission in major cities of Benin. Parasites Vectors. 2010;3(1):1–7. Ochomo EO, Milanoi S, Abong’o B, Onyango B, Muchoki M, Omoke D, et al. Detection of Anopheles stephensi mosquitoes by molecular surveillance, Kenya. Emerg Infect Dis. 2023;29(12):2498. Giesen C, Roche J, Redondo-Bravo L, Ruiz-Huerta C, Gomez-Barroso D, Benito A, Herrador Z. The impact of climate change on mosquito-borne diseases in Africa. Pathogens Global Health. 2020;114(6):287–301. Nosrat C, Altamirano J, Anyamba A, Caldwell JM, Damoah R, Mutuku F, et al. Impact of recent climate extremes on mosquito-borne disease transmission in Kenya. PLoS Negl Trop Dis. 2021;15(3):e0009182. Imbahale SS, Mukabana WR, Orindi B, Githeko AK, Takken W. Variation in malaria transmission dynamics in three different sites in Western kenya. J Trop Med. 2012;2012:912408. Wanjala CL, Mbugi JP, Ototo E, Gesuge M, Afrane Y, Atieli HE et al. Pyrethroid and DDT resistance and organophosphate susceptibility among Anopheles spp. mosquitoes from Western Kenya. Emerg Infect Dis. 2015;21. Lines J, Curtis C, Wilkes T, Njunwa K. Monitoring human-biting mosquitoes (Diptera: Culicidae) in Tanzania with light-traps hung beside mosquito nets. Bull Entomol Res. 1991;81(1):77–84. Coetzee M. Key to the females of Afrotropical Anopheles mosquitoes (Diptera: Culicidae). Malar J. 2020;19(1):1–20. Scott JA, Brogdon WG, Collins FH. Identification of single specimens of the Anopheles gambiae complex by the polymerase chain reaction. Am J Trop Med Hyg. 1993;49(4):520–9. Koekemoer LL, Kamau L, Hunt RH, Coetzee M. A cocktail polymerase chain reaction assay to identify members of the Anopheles funestus (Diptera: Culicidae) group. Am J Trop Med Hyg. 2002;66(6):804–11. Collins FH, Mendez MA, Rasmussen MO, Mehaffey PC, Besansky NJ, Finnerty V. A ribosomal RNA gene probe differentiates member species of the Anopheles gambiae complex. Am J Trop Med Hyg. 1987;37(1):37–41. Shokoples SE, Ndao M, Kowalewska-Grochowska K, Yanow SK. Multiplexed real-time PCR assay for discrimination of Plasmodium species with improved sensitivity for mixed infections. J Clin Microbiol. 2009;47(4):975–80. Veron V, Simon S, Carme B. Multiplex real-time PCR detection of P. falciparum, P. vivax and P. malariae in human blood samples. Exp Parasitol. 2009;121(4):346–51. Desa U. World urbanization prospects, the 2011 revision. Population Division, department of economic and social affairs. United Nations Secretariat. 2014. Obame-Nkoghe J, Makanga BK, Zongo SB, Koumba AA, Komba P, Longo-Pendy N-M, et al. Urban green spaces and vector-borne disease risk in Africa: the case of an unclean forested park in libreville (Gabon, Central Africa). Int J Environ Res Public Health. 2023;20(10):5774. WHO. Global framework for the response to malaria in urban areas. Geneva: World Health Organization; 2022. Salomé G, Riddin M, Braack L. Species composition, seasonal abundance, and biting behavior of malaria vectors in rural Conhane village, Southern Mozambique. Int J Environ Res Public Health. 2023;20(4):3597. Dia AK, Guèye OK, Niang EA, Diédhiou SM, Sy MD, Konaté A, et al. Insecticide resistance in Anopheles arabiensis populations from Dakar and its suburbs: role of target site and metabolic resistance mechanisms. Malar J. 2018;17:1–9. Konaté L, Faye O, Diallo M, Dia I. Vector bionomics and malaria transmission in an area of sympatry of An. arabiensis, An. coluzzii and An. gambiae. Acta Trop. 2019;189:129–36. Ndiaye F, Diop A, Chabi J, Sturm-Ramirez K, Senghor M, Diouf EH, et al. Distribution and dynamics of Anopheles gambiae sl larval habitats in three Senegalese cities with high urban malaria incidence. PLoS ONE. 2024;19(5):e0303473. Djamouko-Djonkam L, Nkahe DL, Kopya E, Talipouo A, Ngadjeu CS, Doumbe-Belisse P et al. Implication of Anopheles funestus in malaria transmission in the city of Yaoundé. Cameroon Parasite. 2020;27. Mustapha AM, Musembi S, Nyamache AK, Machani MG, Kosgei J, Wamuyu L, et al. Secondary malaria vectors in western Kenya include novel species with unexpectedly high densities and parasite infection rates. Parasites Vectors. 2021;14(1):252. Degefa T, Yewhalaw D, Zhou G, Lee M-c, Atieli H, Githeko AK, Yan G. Indoor and outdoor malaria vector surveillance in western Kenya: implications for better understanding of residual transmission. Malar J. 2017;16(1):443. Afrane YA, Bonizzoni M, Yan G. Secondary malaria vectors of sub-Saharan Africa: threat to malaria elimination on the continent? IntechOpen; 2016. Antonio-Nkondjio C, Kerah CH, Simard F, Awono-Ambene P, Chouaibou M, Tchuinkam T, Fontenille D. Complexity of the malaria vectorial system in Cameroon: contribution of secondary vectors to malaria transmission. J Med Entomol. 2006;43(6):1215–21. Githeko AK, Adungo NI, Karanja DM, Hawley WA, Vulule JM, Seroney IK et al. Some observations on the biting behaviour of Anopheles gambiae s.s., Anopheles arabiensis, and Anopheles funestus and their implications for malaria control. Exp Parasitol. 1996;82. Machani MG, Ochomo E, Amimo F, Kosgei J, Munga S, Zhou G, et al. Resting behaviour of malaria vectors in highland and lowland sites of western Kenya: Implication on malaria vector control measures. PLoS ONE. 2020;15(2):e0224718. Bayoh MN, Mathias Dk, Odiere MR, Mutuku FM, Kamau L, Gimnig JE, et al. Anopheles gambiae: historical population decline associated with regional distribution of insecticide-treated bed nets in western Nyanza Province. Kenya Malar J. 2010;9:62. Musiime AK, Smith DL, Kilama M, Rek J, Arinaitwe E, Nankabirwa JI, et al. Impact of vector control interventions on malaria transmission intensity, outdoor vector biting rates and Anopheles mosquito species composition in Tororo, Uganda. Malar J. 2019;18:1–9. Owuor KO, Machani MG, Mukabana WR, Munga SO, Yan G, Ochomo E, Afrane YA. Insecticide resistance status of indoor and outdoor resting malaria vectors in a highland and lowland site in Western Kenya. PLoS ONE. 2021;16(3):e0240771. Lobo NF, Laurent BS, Sikaala CH, Hamainza B, Chanda J, Chinula D, et al. Unexpected diversity of Anopheles species in Eastern Zambia: implications for evaluating vector behavior and interventions using molecular tools. Sci Rep. 2015;5(1):17952. Gatton ML, Chitnis N, Churcher T, Donnelly MJ, Ghani AC, Godfray HC et al. The importance of mosquito behavioural adaptations to malaria control in Africa. Evolution. 2013;67. Githeko A, Mbogo C, Atieli F, Juma F. Sampling Anopheles arabiensis, A. gambiae sensu lato and A. funestus (Diptera: Culicidae) with CDC light-traps near a rice irrigation area and a sugarcane belt in western Kenya. Bull Entomol Res. 1994;84(3):319–24. Coene J. Malaria in urban and rural Kinshasa: the entomological input. Med Vet Entomol. 1993;7(2):127–37. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 15 Mar, 2025 Read the published version in Malaria Journal → Version 1 posted Editorial decision: Revision requested 06 Jan, 2025 Reviews received at journal 03 Dec, 2024 Reviewers agreed at journal 11 Nov, 2024 Reviewers agreed at journal 05 Nov, 2024 Reviews received at journal 05 Nov, 2024 Reviewers agreed at journal 05 Nov, 2024 Reviewers invited by journal 04 Nov, 2024 Editor assigned by journal 21 Aug, 2024 Submission checks completed at journal 21 Aug, 2024 First submitted to journal 20 Aug, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Nevertheless, recent findings from the World Health Organization (WHO) indicate that further reductions in malaria prevalence in Africa are not as significant, with progress stalling in several regions of sub-Saharan Africa where the disease remains widespread (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). The campaigns have predominantly focused on rural areas, overlooking urban centers where malaria prevalence has traditionally been low. However, malaria is now considered an emerging threat in rapidly urbanizing areas of sub-Saharan Africa (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) highlighting the need to monitor vector populations and implement long-term interventions in the neglected urban environments. This oversight has gained significant attention, particularly with the recent establishment and spread of the invasive urban vector \u003cem\u003eAnopheles stephensi\u003c/em\u003e, which is likely to alter disease risk landscape in Africa (\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). In response to these challenges, the WHO introduced a framework supporting the control and elimination of malaria in urban environments, marking the beginning of efforts to address malaria in urban settings (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eUrbanization, often associated with human development and progress, can also lead to significant inequalities and health problems (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). The prevalence of \u003cem\u003eAnopheles\u003c/em\u003e mosquitoes and malaria transmission in urban environments can be influenced by various factors, including housing conditions, land use patterns, population density, transportation/migration, and waste generation/pollution, among other anthropogenic practices (\u003cspan additionalcitationids=\"CR12 CR13\" citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Peri-urban locations, which combine urban and rural characteristics, is likely to experience unique challenges due to changing environmental conditions and socioeconomic factors (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Rural areas, with diverse ecological conditions and traditional practices, typically have higher mosquito densities and infection rates (\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). However, many cities are now experiencing increased urban agriculture, poor drainage systems, broken and open sewers and inadequate housing due to rapid urbanization. These conditions create ideal environments for vector breeding and facilitate their entry into homes, significantly increasing the risk of exposure to malaria vectors (\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). In addition, changing rainfall patterns may increase the availability and suitability of vector breeding habitats. Therefore, understanding mosquito-borne diseases in cities will require an integrative approach that combines ecological findings with their social context (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAlthough malaria vectors are uncommon in urban settings, they have adapted to human-induced changes, including climate change, which can potentially increase the risk of malaria transmission (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). Over half the world\u0026rsquo;s population (4.2\u0026nbsp;billion people) now live in urban areas with the number expected to reach 9.7\u0026nbsp;billion by 2050. The proportion of urban residents in Africa is projected to increase from 36% in 2010 to 50% by 2030 and 60% by 2050 (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). In developing cities, large populations, particularly the poor, face significant challenges and often turn to activities like urban farming, which create favorable conditions for mosquitoes (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). High mobility from malaria-endemic rural areas and rural practices in urban regions, along with the recent presence of invasive species such as \u003cem\u003eAnopheles stephensi\u003c/em\u003e (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e) and climate change (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e) in Kenya and other developing African cities, underscores the need for a robust mosquito surveillance in the urban centers. The main aim of this study was to assess malaria vector diversity, species composition, host-seeking and resting behaviors, and their contributions towards indoor and outdoor malaria transmission across urban, peri-urban and rural settings to provide critical insights for integrated malaria control strategies and targeted mitigation measures in urban areas.\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eDescription of Study Area\u003c/h2\u003e \u003cp\u003eThe study was conducted in an urban-rural continuum in Kisumu County in Western Kenya. Kisumu (00\u0026deg;06\u0026prime;S 034\u0026deg;45\u0026prime;E) is the third largest urban settlement in Kenya with a population of approximately 610,000 people and is located 10 km south of the equator on Lake Victoria. The city lies on the northeastern shore of Lake Victoria with an elevation of approximately 1,140 m above sea level. Kisumu city experiences a humid climate with an average relative humidity of 70%. Western Kenya has two distinct rainy seasons: a long rainy season from March to May and short rains in September through December. The extended dry season spans from January to March, with a shorter dry period from August to September. Annual rainfall typically ranges between 1,000 and 1,500 mm. Thirteen sites were randomly selected along an urban-rural transect from Kisumu city spanning a distance of 30 km. Among these, five locations: Nyalenda, Gesoko, Migosi, Mamboleo and Bandani were surveyed within the urban Kisumu and are characterized by dense urbanization. These sites all are informal residences located within the city). There were four sites in the peri-urban area: Kotetni, Kandalo, Tiengre and Kisian. The four rural locations sampled included Ojola, Mainga, Chulaimbo and Marera, which are approximately 30 km from the city (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Kisumu city is a major regional transportation hub where populations are engaged in formal and informal economic activity(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). \u003cem\u003eAnopheles\u003c/em\u003e mosquito species in the peri-urban and rural of western Kenya lowlands include \u003cem\u003eAnopheles arabiensis\u003c/em\u003e, \u003cem\u003eAn. funestus\u003c/em\u003e, and \u003cem\u003eAn. gambiae\u003c/em\u003e (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eAdult\u003c/b\u003e \u003cb\u003eAnopheles\u003c/b\u003e \u003cb\u003ecollection\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo determine the abundance of indoor and outdoor biting and resting adult female \u003cem\u003eAnopheles\u003c/em\u003e mosquitoes in urban, peri-urban, and rural clusters, sampling was conducted from September 2022 to September 2023. CDC light traps (Model 512; John W. Hock Company, Gainesville, FL, USA) and mechanical aspirators (Prokopack) were used for these collections. For indoor and outdoor biting mosquitoes, battery-powered CDC light traps were hung at the foot end of the bed approximately 1.5 meters above the floor with a sleeping person protected under bednet indoors from 18:00 h to 06:00 h. and outdoors within 2 meters of sentinel houses (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). Collections were conducted in the morning from 6:00 h to 07:00 h. The trapping was done for four consecutive nights in five randomly selected houses in each cluster per zone. Prokopack aspirator (John W Hock, Gainesville, FL, USA) was used to collect indoor and outdoor resting mosquitoes from ten randomly selected houses every morning (06:00 h to 10:00 h) for four days in each cluster per zone. Indoor collections targeted mosquitoes resting on hunged clothes, walls, furniture, under roofs or ceilings, and under beds. Outdoor sampling included open containers, water reservoirs, outdoor kitchens, animal sheds, and outdoor human resting points. Each collection session in a house (both indoors and outdoors) lasted for approximately 20 minutes. Mosquitoes from each house and collection method were sorted, classified according to their gonotrophic status, and morphologically identified as \u003cem\u003eAnopheles\u003c/em\u003e species following the recent taxonomic keys (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). Mosquitoes from each collection method were stored in vials labeled separately and preserved by desiccation. Different houses were visited throughout the study period.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eIdentification of vector species complexes\u003c/h2\u003e \u003cp\u003eA subset of members of \u003cem\u003eAn. gambiae\u003c/em\u003e s.l. and \u003cem\u003eAn. funestus\u003c/em\u003e s.l. groups randomly selected from indoor and outdoor collections from each cluster per zone were identified to species by polymerase chain reaction (PCR), following the protocols developed by Scott et al. for \u003cem\u003eAn. gambiae\u003c/em\u003e s.l. (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e) and Koekemoer et al. for \u003cem\u003eAn. funestus\u003c/em\u003e s.l. (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eMolecular detection of Sporozoite infections\u003c/h2\u003e \u003cp\u003eThe head and thorax of the preserved \u003cem\u003eAnopheles\u003c/em\u003e mosquito specimens were carefully separated from the abdomen, and DNA extracted from head/thorax using the alcohol precipitation method (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). The DNA was analyzed to determine sporozoite infections of \u003cem\u003ePlasmodium\u003c/em\u003e species using a multiplexed real-time quantitative PCR (qPCR) assay. The assay was performed using the published species-specific 18 s ribosomal RNA probes and primers for \u003cem\u003eP. falciparum\u003c/em\u003e, \u003cem\u003eP. malariae\u003c/em\u003e, and \u003cem\u003eP. ovale\u003c/em\u003e (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eData management and analysis\u003c/h2\u003e \u003cp\u003eVector densities from indoor and outdoor night collections were calculated as the number of female mosquitoes per trap/night for each collection method. Analysis of variance (ANOVA) was used to compare malaria vector density between indoor and outdoor locations. Differences in composition and abundance of mosquitoes between sites and locations were tested using chi-squared tests. The sporozoite rate was calculated as the proportion of \u003cem\u003eAnopheles\u003c/em\u003e mosquito samples tested that turned positive for \u003cem\u003ePlasmodium\u003c/em\u003e species. Data were stored in Microsoft Excel 2010 datasheets and analysis done using R statistical software (version 4.0.3; R foundation for Statistical Computing, Vienna, Austria).\u003c/p\u003e \u003c/div\u003e"},{"header":"Result","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eMosquito species composition and abundance\u003c/h2\u003e \u003cp\u003eDuring the study period, a total of 27,483 mosquitoes were collected, comprising 14,478 host-seeking and 13,005 resting mosquitoes, across urban, peri-urban, and rural sites. \u003cem\u003eCulex spp\u003c/em\u003e. constituted the majority of the samples 87.6% (n\u0026thinsp;=\u0026thinsp;24,089), while \u003cem\u003eAnopheles spp\u003c/em\u003e. accounted for 12.4% (n\u0026thinsp;=\u0026thinsp;3,394). The highest number of mosquitoes was collected in the urban zone, comprising 49.4% (n\u0026thinsp;=\u0026thinsp;13,579) of the total captures. This was followed by the peri-urban zone with 37% (n\u0026thinsp;=\u0026thinsp;10,164) and rural zone with 13.6% (n\u0026thinsp;=\u0026thinsp;3,740) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\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\u003eMorphologically identified adult mosquitoes samples by zones (urban, peri-urban and rural) based on sampling method and location in Kisumu city.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\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=\"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 \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eZone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMosquito species\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eIndoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e \u003cp\u003eOutdoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAspiration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAspiration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"7\" rowspan=\"8\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAn.gambiae\u003c/em\u003e s.l.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e453\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e482\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e455\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e105\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e560\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1042\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAn.funestus\u003c/em\u003e grp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e354\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e378\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e480\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAn. coustani\u003c/em\u003e grp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21\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\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e195\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\u003e195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e216\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAn.maculipalipis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4\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\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e47\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAn.pretoriensis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\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\u003e16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e73\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAn.pharoensis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3\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\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eTotal Anopheles\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e845\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e903\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e802\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e980\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1883\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCulex spp\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3663\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2182\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5845\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e4389\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1462\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5851\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e11696\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003ePeri-urban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAn.gambiae s.l\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e309\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e536\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e211\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e362\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e898\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAn.funestus\u003c/em\u003e grp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAn. coustani\u003c/em\u003e grp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e31\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\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eTotal Anopheles\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e332\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e601\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e217\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e417\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1018\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCulex spp\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3339\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5360\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1748\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3786\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e9146\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAn.gambiae\u003c/em\u003e s.l.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e180\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e369\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAn.funestus\u003c/em\u003e grp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e109\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAn. coustani\u003c/em\u003e grp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\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\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e10\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\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eAn. pharaoensis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\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\u0026nbsp;\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\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal \u003cem\u003eAnopheles\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e237\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e381\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e493\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cem\u003eCulex spp\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e740\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e648\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1388\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e470\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1389\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1859\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e3247\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\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"No\" id=\"Taba\" border=\"1\"\u003e \u003ccolgroup cols=\"10\"\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 \u003cp\u003e\u003cstrong\u003eTable 2:\u0026nbsp;\u003c/strong\u003eSporozoite rates of \u003cem\u003eAnopheles\u003c/em\u003e mosquitoes from indoor and outdoor collections in Urban, peri-urban and rural zones in Kisumu, western Kenya\u003c/p\u003e\n\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=\"char\" char=\".\" 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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStudy zone and \u003cem\u003eAnopheles\u003c/em\u003e species\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eParameters\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eIndoor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c9\" namest=\"c7\"\u003e \u003cp\u003eOutdoor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAspiration\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eLT\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eAspiration\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003eTotal\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eAn.gambiae\u003c/em\u003e s.s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo.tested\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39\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\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePf\u0026thinsp;+\u0026thinsp;Ve (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" 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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eAn.arabiensis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo.tested\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e242\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e189\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e511\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePf\u0026thinsp;+\u0026thinsp;Ve (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" 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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eAn.funestus s.s.\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo.tested\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e27\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\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e118\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePf\u0026thinsp;+\u0026thinsp;Ve (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" 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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eAn. coustani\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo.tested\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\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\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e48\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\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePf\u0026thinsp;+\u0026thinsp;Ve (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" 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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eAn.ziemanni\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo.tested\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e26\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\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePf\u0026thinsp;+\u0026thinsp;Ve (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" 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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eAn.maculipalipis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo.tested\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePf\u0026thinsp;+\u0026thinsp;Ve (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" 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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eAn.pretoriensis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo.tested\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\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\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePf\u0026thinsp;+\u0026thinsp;Ve (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" 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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePeri-urban\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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eAn.gambiae\u003c/em\u003e s.s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo.tested\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePf\u0026thinsp;+\u0026thinsp;Ve (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1(4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e1(1.0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eAn.arabiensis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo.tested\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e223\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e188\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e411\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e165\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e317\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e728\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePf\u0026thinsp;+\u0026thinsp;Ve (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" 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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eAn.funestus\u003c/em\u003e s.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo.tested\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\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\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePf\u0026thinsp;+\u0026thinsp;Ve (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" 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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eAn. coustani\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo.tested\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e21\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\u003e21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePf\u0026thinsp;+\u0026thinsp;Ve (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" 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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\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 \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eAn.gambiae\u003c/em\u003e s.s\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo.tested\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e177\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePf\u0026thinsp;+\u0026thinsp;Ve (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2(4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2(1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2(13.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2(5.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e4(2.3)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eAn.arabiensis\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo.tested\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e147\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePf\u0026thinsp;+\u0026thinsp;Ve (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(1.7)\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(1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1(20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1(2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e2(1.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eAn.funestus\u003c/em\u003e s.s.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo.tested\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" 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\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePf\u0026thinsp;+\u0026thinsp;Ve (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1(6.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1(2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" 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(2.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eAn.leesoni\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo.tested\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePf\u0026thinsp;+\u0026thinsp;Ve (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\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\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" 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 \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eAnopheline mosquito species composition and abundance\u003c/h2\u003e \u003cp\u003eOverall, a total of 3,394 adult female \u003cem\u003eAnopheles\u003c/em\u003e mosquitoes, comprising six species, were collected over the study period. Of these, 55.5% (n\u0026thinsp;=\u0026thinsp;1,883) were from the urban zone, 30% (n\u0026thinsp;=\u0026thinsp;1,018) from the peri-urban zone, and 14.5% n\u0026thinsp;=\u0026thinsp;493 from the rural zone (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The difference in the distribution of anopheline mosquito species between the study sites was statistically significant (F\u003csub\u003e2, 1092\u003c/sub\u003e = 14.45, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Overall, \u003cem\u003eAnopheles gambiae\u003c/em\u003e s.l. was the predominant species, comprising 68% (n\u0026thinsp;=\u0026thinsp;2,309) of the total collection. This was followed by \u003cem\u003eAn. funestus\u003c/em\u003e group (19.8%, n\u0026thinsp;=\u0026thinsp;675), \u003cem\u003eAn. coustani\u003c/em\u003e group (7.8%, n\u0026thinsp;=\u0026thinsp;263), \u003cem\u003eAn. pretoriensis\u003c/em\u003e (2.6%, n\u0026thinsp;=\u0026thinsp;89), \u003cem\u003eAn. maculipalpis\u003c/em\u003e (1.6%, n\u0026thinsp;=\u0026thinsp;53), and \u003cem\u003eAn. pharoensis\u003c/em\u003e (0.2%, n\u0026thinsp;=\u0026thinsp;5). In the urban zone, \u003cem\u003eAnopheles gambiae\u003c/em\u003e s.l was the most abundant 55.3% (n\u0026thinsp;=\u0026thinsp;1042) followed by \u003cem\u003eAn. funestus\u003c/em\u003e group 25.5% (n\u0026thinsp;=\u0026thinsp;480), \u003cem\u003eAn. coustan\u003c/em\u003ei group 11.5% (n\u0026thinsp;=\u0026thinsp;216), \u003cem\u003eAn. pretoriensis\u003c/em\u003e 4.7% (n\u0026thinsp;=\u0026thinsp;89), \u003cem\u003eAn. maculipalipis\u003c/em\u003e 2.8% (n\u0026thinsp;=\u0026thinsp;53) and \u003cem\u003eAn. pharoensis\u003c/em\u003e 0.2% (n\u0026thinsp;=\u0026thinsp;3). Out of 1,018 \u003cem\u003eAnopheles\u003c/em\u003e females collected in peri-urban, 88.2% (n\u0026thinsp;=\u0026thinsp;898) were \u003cem\u003eAn. gambiae\u003c/em\u003e s.l, 8.4% (n\u0026thinsp;=\u0026thinsp;86) \u003cem\u003eAn. funestus\u003c/em\u003e group and 3.3% (n\u0026thinsp;=\u0026thinsp;34) \u003cem\u003eAn. coustani\u003c/em\u003e group. In rural zone, \u003cem\u003eAn. gambiae\u003c/em\u003e s.l was predominant species 74.8% (n\u0026thinsp;=\u0026thinsp;396) followed by \u003cem\u003eAn. funestus\u003c/em\u003e group 22.1% (n\u0026thinsp;=\u0026thinsp;109), \u003cem\u003eAn. coustani\u003c/em\u003e group 2.6% (n\u0026thinsp;=\u0026thinsp;13) and \u003cem\u003eAn. pharoensis\u003c/em\u003e 0.4% (n\u0026thinsp;=\u0026thinsp;2).\u003c/p\u003e \u003cp\u003e \u003cb\u003eIndoor and outdoor\u003c/b\u003e \u003cb\u003eAnopheles\u003c/b\u003e \u003cb\u003emosquito composition\u003c/b\u003e\u003c/p\u003e \u003cp\u003eOverall, the majority of anophelines (55.5%, n\u0026thinsp;=\u0026thinsp;1885) were collected indoors across the three zone. In urban, peri-urban, and rural sites, more \u003cem\u003eAnopheles\u003c/em\u003e mosquitoes were host-seeking indoors [51.3% (95% CI 48.8\u0026ndash;53.7%), 57.3% (95% CI 52.8\u0026ndash;61.8%), and 73.1% (95% CI 68.3\u0026ndash;78%), respectively] than outdoors [48.7% (95% CI 46.3\u0026ndash;51.1%), 42.6% (95% CI 38.2\u0026ndash;47.1%), and 26.8% (95% CI 22-31.8%), respectively]. The mean indoor host-seeking density for the \u003cem\u003eAn. funestus\u003c/em\u003e group in urban zone was significantly higher than the outdoor density (\u003cem\u003et\u003c/em\u003e \u003csub\u003e74\u003c/sub\u003e = 2.67, p\u0026thinsp;\u0026lt;\u0026thinsp;0.004) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). In contrast, there was no significant difference in the mean indoor and outdoor host-seeking densities for \u003cem\u003eAn. gambiae\u003c/em\u003e s.l. in urban zone (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The secondary vectors mean outdoor host-seeking densities were marginally significant compared to the indoor densities for \u003cem\u003eAn. maculipalipis\u003c/em\u003e (\u003cem\u003et\u003c/em\u003e \u003csub\u003e9\u003c/sub\u003e = 1.96, p\u0026thinsp;\u0026lt;\u0026thinsp;0.04) and \u003cem\u003eAn. coustani\u003c/em\u003e group (\u003cem\u003et\u003c/em\u003e \u003csub\u003e42\u003c/sub\u003e = 2.15, p\u0026thinsp;\u0026lt;\u0026thinsp;0.02). The proportion of outdoor host seeking \u003cem\u003eAn. pretoriensis\u003c/em\u003e was higher 74% (95% CI 61.8\u0026ndash;86.2%) compared to indoors 26% (95% CI 13.8\u0026ndash;38.2%).\u003c/p\u003e \u003cp\u003eThere was no significant difference in the mean indoor and outdoor host-seeking densities for \u003cem\u003eAn. gambiae\u003c/em\u003e s.l. and the \u003cem\u003eAn. funestus\u003c/em\u003e group (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) in the peri-urban sites. The mean indoor host-seeking density for the \u003cem\u003eAn. gambiae\u003c/em\u003e s.l was significantly higher than the outdoor density (\u003cem\u003et\u003c/em\u003e \u003csub\u003e94\u003c/sub\u003e = 2.3, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01), whereas the difference in the mean indoor and outdoor host-seeking densities for the An. \u003cem\u003efunestus\u003c/em\u003e group was not significant (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) in the rural zone. Most members of the \u003cem\u003eAn. coustani\u003c/em\u003e group were host-seeking outdoors in both peri-urban [94% (95% CI 85.7\u0026ndash;100%)] and rural areas [76.9% (95% CI 54-99.8%)].\u003c/p\u003e \u003cp\u003eThe majority of female \u003cem\u003eAnopheles\u003c/em\u003e mosquitoes were caught resting outdoors [75.4% (95% CI 70\u0026ndash;81%)] compared to indoors [24.6% (95% CI 19.1\u0026ndash;30%)] in the urban zone. Conversely, in the peri-urban and rural sites, most female \u003cem\u003eAnopheles\u003c/em\u003e mosquitoes were caught resting indoors [60.5% (95% CI 56.4\u0026ndash;64.6%) and 85.2% (95% CI 79.8\u0026ndash;90.5%), respectively] than outdoors [39.5% (95% CI 35.4\u0026ndash;43.6%) and 14.8% (95% CI 9.4\u0026ndash;20.1%), respectively]. The mean outdoor resting density of \u003cem\u003eAn. gambiae\u003c/em\u003e s.l in urban was significantly higher than indoor density (\u003cem\u003et\u003c/em\u003e \u003csub\u003e66\u003c/sub\u003e = 2.2, p\u0026thinsp;\u0026lt;\u0026thinsp;0.016) whereas, the difference in the mean indoor and outdoor resting density for \u003cem\u003eAn. funestus\u003c/em\u003e group was not significant (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). The majority of \u003cem\u003eAn. maculipalipis\u003c/em\u003e 93% (95% CI 82.7\u0026ndash;100%) and \u003cem\u003eAn. pretoriensis\u003c/em\u003e 92.3% (95% CI 83.9-100.6%) were resting outdoors. The difference in mean indoor and outdoor resting densities for \u003cem\u003eAn. gambiae\u003c/em\u003e s.l and \u003cem\u003eAn. funestus\u003c/em\u003e group in peri-urban were not significant (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). In Rural, the mean indoor resting density of \u003cem\u003eAn. gambiae\u003c/em\u003e s.l was higher than outdoor (\u003cem\u003et\u003c/em\u003e \u003csub\u003e69\u003c/sub\u003e = 1.76, p\u0026thinsp;\u0026lt;\u0026thinsp;0.042) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). The proportion of \u003cem\u003eAn. funestus\u003c/em\u003e group caught resting indoors 85.7% (95% CI 75.1\u0026ndash;96.3%) was higher than outdoor 14.3% (95% CI 3.7\u0026ndash;24.9%).\u003c/p\u003e \u003cp\u003e \u003cb\u003eAnopheles gambiae\u003c/b\u003e \u003cb\u003eand\u003c/b\u003e \u003cb\u003eAnopheles funestus\u003c/b\u003e \u003cb\u003esibling species composition\u003c/b\u003e\u003c/p\u003e \u003cp\u003eA total of 2,170 specimens (1,896 \u003cem\u003eAn. gambiae\u003c/em\u003e s.l. and 274 \u003cem\u003eAn. funestus\u003c/em\u003e group) were used for molecular assay to discriminate respective sibling species. \u003cem\u003eAnopheles arabiensis\u003c/em\u003e was the predominant sibling species in both the urban (84.3%) and peri-urban (89%) sites, while \u003cem\u003eAn. gambiae\u003c/em\u003e accounted for 15.7% and 11% in these sites, respectively. In contrast, in the rural zone, \u003cem\u003eAn. gambiae\u003c/em\u003e s.s. (hereafter \u003cem\u003eAn. gambiae\u003c/em\u003e) was the most abundant species (60.2%), compared to \u003cem\u003eAn. arabiensis\u003c/em\u003e (39.7%). All the \u003cem\u003eAn. funestus\u003c/em\u003e group samples assayed from the urban zone were \u003cem\u003eAn. funestus\u003c/em\u003e s.s. (hereafter \u003cem\u003eAn. funestus\u003c/em\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). In the peri-urban and rural sites, \u003cem\u003eAn. funestus\u003c/em\u003e was the dominant species (98.4% and 85.7%, respectively), while \u003cem\u003eAn. leesoni\u003c/em\u003e accounted for 1.6% and 14.3%, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB\u0026amp;C). Overall, there was a significant difference between indoor and outdoor locations in terms of \u003cem\u003eAn. funestus\u003c/em\u003e group species composition (χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;21.34, \u003cem\u003edf\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003eSporozoite infectivity rates\u003c/h2\u003e \u003cp\u003eSporozoite infectivity rate was used as a proxy for establishing \u003cem\u003ePlasmodium\u003c/em\u003e infection rates. Out of the 2,170 mosquitoes tested, 8 specimens turned positive for sporozoites (i.e. 5 \u003cem\u003eAn. gambiae\u003c/em\u003e, 2 \u003cem\u003eAn. arabiensis\u003c/em\u003e, and 1 \u003cem\u003eAn. funestus\u003c/em\u003e). Of these, one sample was from the peri-urban zone and seven from the rural zone. In the peri-urban zone, 2.3% (1/43) of \u003cem\u003eAn. gambiae\u003c/em\u003e collected outdoors tested positive for sporozoite. The Sporozoite rate for \u003cem\u003eAn. gambiae\u003c/em\u003e in the rural zone was 1.4% (2/139) indoors and 5.3% (2/38) outdoors. The sporozoite rate for \u003cem\u003eAn. arabiensis\u003c/em\u003e was 1% (1/99) indoors and 2.1% (1/48) outdoors. Additionally, 2.5% (1/40) of \u003cem\u003eAn. funestus\u003c/em\u003e collected indoors tested positive for sporozoites. Overall, the sporozoite rates were higher for samples collected outdoors 3.5% (3/86) than indoors 1.45% (4/278) in rural areas. None of the samples tested from urban zone were positive (Table\u0026nbsp;2).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eWith over half of the world\u0026rsquo;s population now residing in urban areas and projections suggesting this could rise to 75% by 2050 (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e), rapid urbanization, often coupled with economic decline, has the potential to profoundly affect malaria epidemiology and control, thereby raising the disease burden in urban populations (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). A major global public health concern is whether the rapid urbanization experienced in most developing African cities will shift malaria from rural to urban areas(\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Gaining insight into mosquito species composition, ecology, and biting behavior in these developing African cities is essential for implementing effective vector control strategies (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). This study found a surprisingly higher species diversity of anopheline mosquitoes in urban areas which was even higher compared to peri-urban and rural areas. The predominant vector was \u003cem\u003eAn. gambiae\u003c/em\u003e s.l. with \u003cem\u003eAn. arabiensis\u003c/em\u003e population being the highest in urban and peri-urban areas, while \u003cem\u003eAn. gambiae\u003c/em\u003e dominated the rural areas.\u003c/p\u003e \u003cp\u003eThe higher numbers of \u003cem\u003eAn. arabiensis\u003c/em\u003e in the city corroborates similar studies in West Africa, which have demonstrated the increased adaptability of this species in urban environments (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). This adaptability may be facilitated by urbanization-induced environmental changes, such as higher temperatures and lower humidity, which favor its survival (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e). The abundance of \u003cem\u003eAnopheles gambiae\u003c/em\u003e in rural areas can be attributed to its preference for unpolluted waters, which are commonly found in such settings. In contrast, urban environments, characterized by polluted waters, are less conducive to the survival of this species. However, instances of this species adapting to urban environments have been documented in Cameroon, West Africa (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e). The presence of \u003cem\u003eAn. funestus\u003c/em\u003e, a significant malaria vector in rural sub-Saharan Africa, in urban areas is concerning as it could potentially sustain high levels of malaria transmission within cities. Reports of this species in urban areas of West Africa highlight their expansion to new niches thereby increasing the risk of malaria (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn addition to primary vectors, secondary vectors such as \u003cem\u003eAn. coustani\u003c/em\u003e group, \u003cem\u003eAn. pretoriensis\u003c/em\u003e, \u003cem\u003eAn. maculipalipis\u003c/em\u003e and \u003cem\u003eAn. pharaonsis\u003c/em\u003e were abundant in urban areas, unlike the rural and peri-urban settings where only the \u003cem\u003eAn. coustani\u003c/em\u003e group and \u003cem\u003eAn. pharaonsis\u003c/em\u003e were observed. A recent study from rural western Kenya reported an increase in secondary vectors (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e) compared to previous findings (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). The co-occurrence of primary and secondary vectors in the urban zone is concerning as it may lead to increased risk of malaria transmission. Studies have shown that many secondary vectors prefer outdoor resting and biting, allowing them to sustain transmission even after indoor control measures, like insecticide-treated bed nets, have reduced primary vectors (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e). Some of the likely factors contributing to their occurrence in urban environments could be due to climate changes and unprecedented land-use contributing to their survival in urban environments (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e). The adaptation of the secondary vectors to the urban environment highlights the need for additional vector control interventions that target the behavior of these vectors, as well as a better understanding of their biology and role in urban malaria epidemiology to inform targeted interventions.\u003c/p\u003e \u003cp\u003eConsistent with previous studies in western Kenya (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e), \u003cem\u003eAn. arabiensis\u003c/em\u003e was found to seek hosts and rest outdoors more frequently than indoors in urban and rural sites but showed no such preference in peri-urban areas. This variability may be influenced by ecological factors and implemented indoor vector control measures (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e), challenging the traditional indoor-focused interventions. Conversely, \u003cem\u003eAn. funestus\u003c/em\u003e and \u003cem\u003eAn. gambiae\u003c/em\u003e consistently exhibited indoor host-seeking and resting behaviors despite the use of LLINs, likely as a result of high insecticide resistance (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e). Moreover, these behaviors may also be influenced by poor housing conditions, which frequently fail to prevent mosquitoes from entering homes. While urbanization often improves infrastructure and housing quality, providing better mosquito-proof environments and healthcare access, this improvement may not extend to many developing African cities with slum-like conditions, as observed in this study. Thus, effective vector control strategies like house screening and larval source management are necessary to mitigate mosquito entry and outdoor mosquito activities in such settings. Secondary vectors like \u003cem\u003eAn. maculipalipis\u003c/em\u003e, \u003cem\u003eAn. coustani\u003c/em\u003e, \u003cem\u003eAn. pretoriensis\u003c/em\u003e, and \u003cem\u003eAn. pharaoensis\u003c/em\u003e showed increased outdoor activity, particularly in urban areas, potentially evading primary interventions and sustaining malaria transmission. Their ability to harbor \u003cem\u003ePlasmodium\u003c/em\u003e parasites(\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e) emphasizes their significant epidemiological impact, highlighting the need for robust entomological surveillance and targeted vector control strategies.\u003c/p\u003e \u003cp\u003eMalaria persistence is linked to behavioral changes in anopheline mosquitoes (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e). This study found that most malaria transmission by \u003cem\u003eAn. funestus\u003c/em\u003e likely occurs indoors in rural areas, confirming its significant role in indoor transmission. Conversely, \u003cem\u003eAn. arabiensis\u003c/em\u003e and \u003cem\u003eAn. gambiae\u003c/em\u003e may be more involved in outdoor transmission, with \u003cem\u003eAn. gambiae\u003c/em\u003e potentially driving outdoor malaria transmission in peri-urban areas. Overall, most transmission occurred outdoors in rural and peri-urban areas, suggesting that indoor vector control methods like LLINs and IRS alone may not be sufficient, as outdoor-biting vectors pose a significant threat to elimination efforts. Despite the high numbers of malaria vectors in urban areas, which could suggest ongoing malaria transmission, no \u003cem\u003ePlasmodium\u003c/em\u003e infections were detected in the tested mosquitoes. This absence of detection could be due to the limitations of the CDC LT trap in high-light urban environments. In western Kenya, CDC light traps in areas dominated by \u003cem\u003eAn. arabiensis\u003c/em\u003e have been found to capture a higher proportion of younger mosquitoes, confirmed by parity dissections(\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e). Additionally, urban-adapted malaria vectors have been reported to have a shorter lifespan compared to rural counterparts (4.1 days versus 11 days) (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e), potentially limiting their ability to transmit the parasite. Although this parity and survivorship information were not considered in the current analysis, integrating these factors in future research could enhance our understanding of mosquito population dynamics in urban areas. Nonetheless, studies in West Africa have implicated \u003cem\u003eAn. arabiensis\u003c/em\u003e and \u003cem\u003eAn. funes\u003c/em\u003etus to urban malaria transmission, necessitating the need for tailored urban-specific vector control strategies. It is concerning that secondary vectors such as \u003cem\u003eAn. coustani\u003c/em\u003e, \u003cem\u003eAn. pretoriensis\u003c/em\u003e, and \u003cem\u003eAn. pharoensis\u003c/em\u003e, despite their tendency to feed on animals, have been found susceptible to \u003cem\u003ePlasmodium\u003c/em\u003e infections (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e). The complex behaviors and species diversity of these vectors in urban areas, pose a significant challenge to malaria elimination efforts that rely solely on indoor vector control, underscoring the need for ongoing adoption of integrated control strategies.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe study revealed a high diversity of \u003cem\u003eAnopheles\u003c/em\u003e species in urban areas, with significant outdoor activity. The detection of \u003cem\u003eAn. funestus\u003c/em\u003e in urban environments is concerning due to its established role in malaria transmission in rural areas, where malaria is high. Notably, outdoor malaria transmission was prevalent in rural and peri-urban regions, emphasizing the need to adapt and diversify interventions targeting outdoor-biting and resting mosquitoes. These findings highlight the importance of increased routine entomological surveillance in urban areas. Implementing integrated vector control measures, including larval source management, house modifications such as screening windows and eaves, and improved urban planning, is crucial for effective urban vector control.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Maseno University Ethics Review Committee (MUERC Protocol No. 00456) and the University of California, Irvine Institutional Review Board (UCI IRB) and received authorization from the Ministry of Health, Kenya. Written informed consent was sought from household heads before data were collected from the households. All experiments and methods were carried out in accordance with the relevant guidelines and regulations of MUERC and UCI-IRB.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dataset supporting the conclusions of this article is included within the article and its supplementary information files.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have declared that no competing interest.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contribution\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMGM, EO, YAA and GY conceived and designed the study. MGM, SAO, IN, SM, GN participated in the field work and laboratory analysis, MGM did data analysis and drafted the manuscript. MCL determined the study site demarcations, MGM, SAO, GN, HA, JG and CW supervised data collection and edited the draft manuscript writing. \u0026nbsp;The final manuscript was edited by GZ, AG, EO, YAA and GY. All authors read and approved the final version of the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors wish to thank the volunteers for their participation in this study and the leadership of Kisumu County for allowing us to conduct the study in the area. We acknowledge the Entomology Laboratory at Kenya Medical Research Institute, Kisumu, the field assistants in urban, peri-urban and rural areas for providing technical support.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by grants from the National Institute of Health (R01 AI123074, U19 AI129326, R01 AI050243, D43 TW001505). There was no additional external funding received for this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBhatt S, Weiss D, Cameron E, Bisanzio D, Mappin B, Dalrymple U, et al. The effect of malaria control on Plasmodium falciparum in Africa between 2000 and 2015. Nature. 2015;526(7572):207\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWHO. World Malaria Report 2022. Geneva: World Health Organisation; 2023.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLohnert B. 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Am J Trop Med Hyg. 2002;66(6):804\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCollins FH, Mendez MA, Rasmussen MO, Mehaffey PC, Besansky NJ, Finnerty V. A ribosomal RNA gene probe differentiates member species of the Anopheles gambiae complex. Am J Trop Med Hyg. 1987;37(1):37\u0026ndash;41.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShokoples SE, Ndao M, Kowalewska-Grochowska K, Yanow SK. Multiplexed real-time PCR assay for discrimination of Plasmodium species with improved sensitivity for mixed infections. J Clin Microbiol. 2009;47(4):975\u0026ndash;80.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVeron V, Simon S, Carme B. Multiplex real-time PCR detection of P. falciparum, P. vivax and P. malariae in human blood samples. Exp Parasitol. 2009;121(4):346\u0026ndash;51.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDesa U. World urbanization prospects, the 2011 revision. Population Division, department of economic and social affairs. United Nations Secretariat. 2014.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eObame-Nkoghe J, Makanga BK, Zongo SB, Koumba AA, Komba P, Longo-Pendy N-M, et al. Urban green spaces and vector-borne disease risk in Africa: the case of an unclean forested park in libreville (Gabon, Central Africa). Int J Environ Res Public Health. 2023;20(10):5774.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWHO. Global framework for the response to malaria in urban areas. Geneva: World Health Organization; 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSalom\u0026eacute; G, Riddin M, Braack L. Species composition, seasonal abundance, and biting behavior of malaria vectors in rural Conhane village, Southern Mozambique. Int J Environ Res Public Health. 2023;20(4):3597.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDia AK, Gu\u0026egrave;ye OK, Niang EA, Di\u0026eacute;dhiou SM, Sy MD, Konat\u0026eacute; A, et al. Insecticide resistance in Anopheles arabiensis populations from Dakar and its suburbs: role of target site and metabolic resistance mechanisms. Malar J. 2018;17:1\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKonat\u0026eacute; L, Faye O, Diallo M, Dia I. Vector bionomics and malaria transmission in an area of sympatry of An. arabiensis, An. coluzzii and An. gambiae. Acta Trop. 2019;189:129\u0026ndash;36.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNdiaye F, Diop A, Chabi J, Sturm-Ramirez K, Senghor M, Diouf EH, et al. Distribution and dynamics of Anopheles gambiae sl larval habitats in three Senegalese cities with high urban malaria incidence. PLoS ONE. 2024;19(5):e0303473.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDjamouko-Djonkam L, Nkahe DL, Kopya E, Talipouo A, Ngadjeu CS, Doumbe-Belisse P et al. Implication of Anopheles funestus in malaria transmission in the city of Yaound\u0026eacute;. Cameroon Parasite. 2020;27.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMustapha AM, Musembi S, Nyamache AK, Machani MG, Kosgei J, Wamuyu L, et al. Secondary malaria vectors in western Kenya include novel species with unexpectedly high densities and parasite infection rates. Parasites Vectors. 2021;14(1):252.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDegefa T, Yewhalaw D, Zhou G, Lee M-c, Atieli H, Githeko AK, Yan G. Indoor and outdoor malaria vector surveillance in western Kenya: implications for better understanding of residual transmission. Malar J. 2017;16(1):443.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAfrane YA, Bonizzoni M, Yan G. Secondary malaria vectors of sub-Saharan Africa: threat to malaria elimination on the continent? IntechOpen; 2016.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAntonio-Nkondjio C, Kerah CH, Simard F, Awono-Ambene P, Chouaibou M, Tchuinkam T, Fontenille D. Complexity of the malaria vectorial system in Cameroon: contribution of secondary vectors to malaria transmission. J Med Entomol. 2006;43(6):1215\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGitheko AK, Adungo NI, Karanja DM, Hawley WA, Vulule JM, Seroney IK et al. Some observations on the biting behaviour of Anopheles gambiae s.s., Anopheles arabiensis, and Anopheles funestus and their implications for malaria control. Exp Parasitol. 1996;82.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMachani MG, Ochomo E, Amimo F, Kosgei J, Munga S, Zhou G, et al. 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Insecticide resistance status of indoor and outdoor resting malaria vectors in a highland and lowland site in Western Kenya. PLoS ONE. 2021;16(3):e0240771.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLobo NF, Laurent BS, Sikaala CH, Hamainza B, Chanda J, Chinula D, et al. Unexpected diversity of Anopheles species in Eastern Zambia: implications for evaluating vector behavior and interventions using molecular tools. Sci Rep. 2015;5(1):17952.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGatton ML, Chitnis N, Churcher T, Donnelly MJ, Ghani AC, Godfray HC et al. The importance of mosquito behavioural adaptations to malaria control in Africa. Evolution. 2013;67.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGitheko A, Mbogo C, Atieli F, Juma F. Sampling Anopheles arabiensis, A. gambiae sensu lato and A. funestus (Diptera: Culicidae) with CDC light-traps near a rice irrigation area and a sugarcane belt in western Kenya. Bull Entomol Res. 1994;84(3):319\u0026ndash;24.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCoene J. Malaria in urban and rural Kinshasa: the entomological input. Med Vet Entomol. 1993;7(2):127\u0026ndash;37.\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":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"malaria-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"malj","sideBox":"Learn more about [Malaria Journal](http://malariajournal.biomedcentral.com/)","snPcode":"12936","submissionUrl":"https://submission.nature.com/new-submission/12936/3","title":"Malaria Journal","twitterHandle":"@malariajournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Anopheles, malaria, Anopheles density, species composition, sporozoite infection, urban city","lastPublishedDoi":"10.21203/rs.3.rs-4943539/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4943539/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eIncreasing urbanization in tropical Africa may create new niches for malaria vectors, potentially leading to higher disease transmission rates. Vector control efforts remain largely targeted at ecologically rural bio-complexities with multiple hosts. Understanding mosquito species composition, ecology, host diversity and biting behavior in urban areas is crucial for planning effective control. This study assessed mosquito species diversity, abundance, behavioral patterns, and \u003cem\u003ePlasmodium\u003c/em\u003e sporozoite infection rates of \u003cem\u003eAnopheles\u003c/em\u003e vectors along an urban-rural transect in Kisumu city, western Kenya.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIndoor and outdoor host-seeking and resting adult mosquitoes were collected using Centers for Disease Control and Prevention miniature light traps (CDC-LT) and mechanical aspirators (Prokopack) along an urban-rural transect. Females \u003cem\u003eAnopheles\u003c/em\u003e mosquitoes collected were identified using morphological taxonomic keys to species level. Specimens belonging to the \u003cem\u003eAnopheles gambiae\u003c/em\u003e complex and \u003cem\u003eAnopheles funestus\u003c/em\u003e group were further processed using polymerase chain reaction (PCR) to identify members of each complex/group. Subsequently, sporozoite infection rates of the anopheline mosquitoes were determined using a multiplexed real-time quantitative PCR (qPCR) assay.\u003c/p\u003e\u003ch2\u003eResult\u003c/h2\u003e \u003cp\u003eA total of 3,394 female \u003cem\u003eAnopheles\u003c/em\u003e mosquitoes were collected and identified. These comprised of \u003cem\u003eAn. gambiae\u003c/em\u003e s.l. (68%), \u003cem\u003eAn. funestus\u003c/em\u003e group (19.8%), \u003cem\u003eAn. coustani\u003c/em\u003e (7.8%), \u003cem\u003eAn. pharoensis\u003c/em\u003e (2.6%), \u003cem\u003eAn. maculipalipis\u003c/em\u003e (1.6%), and \u003cem\u003eAn. leesoni\u003c/em\u003e (0.2%). All six species were found in urban zone, but only three were found in peri-urban and rural sites. Overall, urban collections accounted for the majority of these collections (55.5%) of mosquitoes collected, followed by those from peri-urban (30%) and rural sites (14.5%). Species distribution across the three ecotypes showed \u003cem\u003eAnopheles arabiensis\u003c/em\u003e was the dominant species in urban (84.3%) and peri-urban (89%) sites, while \u003cem\u003eAn. gambiae\u003c/em\u003e s.s. was predominantly found in the rural zone (60.2%) alongside \u003cem\u003eAn. arabiensis\u003c/em\u003e (39.7%). \u003cem\u003eAnopheles funestus\u003c/em\u003e was the predominant species in peri-urban (98.4%) and rural (85.7%) areas, with \u003cem\u003eAn. leesoni\u003c/em\u003e accounted for 1.6% and 14.3%, respectively. In urban areas, all samples from the \u003cem\u003eAn. funestus\u003c/em\u003e group were identified as \u003cem\u003eAn. funestus\u003c/em\u003e s.s.. Majority (55.5%) of \u003cem\u003eAnopheles\u003c/em\u003e mosquitoes were collected indoors, while secondary vectors were primarily caught outdoors. Overall, sporozoite rates were higher outdoors 3.5% compared to indoors 1.45% in rural areas. Specifically, sporozoite infectivity rates for \u003cem\u003eAn. funestus\u003c/em\u003e, \u003cem\u003eAn. gambiae\u003c/em\u003e s.s and \u003cem\u003eAn. arabiensis\u003c/em\u003e collected indoors in the rural zone was 2.5%, 1.4% and 1% respectively. Outdoors in rural areas, \u003cem\u003eAn. gambiae\u003c/em\u003e had a sporozoite rate of 5.3%, while \u003cem\u003eAn. arabiensis\u003c/em\u003e had a rate of 2.1%. In peri-urban areas \u003cem\u003eAn. gambiae\u003c/em\u003e had a sporozoite rate of 2.3%. No sporozoites were detected in samples from urban sites.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe study highlights a shift of diversity of \u003cem\u003eAnopheles\u003c/em\u003e species towards urban areas with increased outdoor activity, and significant outdoor malaria transmission in rural and peri-urban areas, emphasizing the need for tools targeting outdoor-biting mosquitoes. The presence of \u003cem\u003eAn. funestus\u003c/em\u003e in urban settings is of interest and highlights the critical importance of sustained entomological surveillance to inform integrated vector control and prevent future transmission risks.\u003c/p\u003e","manuscriptTitle":"Bionomics and distribution of malaria vectors in Kisumu city, Western Kenya: Implications for urban malaria transmission ","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-19 13:19:22","doi":"10.21203/rs.3.rs-4943539/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-01-06T21:00:06+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-12-03T14:03:42+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"159431445157783047534277692870811791977","date":"2024-11-11T12:56:57+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"65075996860145867368913413441294987840","date":"2024-11-05T09:33:31+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-11-05T08:50:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"282053980169470559653843237942421830769","date":"2024-11-05T06:17:42+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-11-05T02:29:40+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-08-21T07:52:43+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-08-21T07:51:19+00:00","index":"","fulltext":""},{"type":"submitted","content":"Malaria Journal","date":"2024-08-20T08:57:55+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"malaria-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"malj","sideBox":"Learn more about [Malaria Journal](http://malariajournal.biomedcentral.com/)","snPcode":"12936","submissionUrl":"https://submission.nature.com/new-submission/12936/3","title":"Malaria Journal","twitterHandle":"@malariajournal","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e826b47c-a6b4-4a23-8021-c59481684814","owner":[],"postedDate":"September 19th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-03-17T16:06:09+00:00","versionOfRecord":{"articleIdentity":"rs-4943539","link":"https://doi.org/10.1186/s12936-025-05332-7","journal":{"identity":"malaria-journal","isVorOnly":false,"title":"Malaria Journal"},"publishedOn":"2025-03-15 15:58:54","publishedOnDateReadable":"March 15th, 2025"},"versionCreatedAt":"2024-09-19 13:19:22","video":"","vorDoi":"10.1186/s12936-025-05332-7","vorDoiUrl":"https://doi.org/10.1186/s12936-025-05332-7","workflowStages":[]},"version":"v1","identity":"rs-4943539","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4943539","identity":"rs-4943539","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}