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

Malaria Journal volume 24, Article number: 85 (2025) Cite this article

Abstract

Background

Increasing unplanned urbanization in tropical Africa may create new niches for malaria vectors, raising transmission risk, yet control efforts focus on rural ecosystems. Understanding mosquito diversity, ecology and biting behaviour in urban areas is crucial for effective control. This study assessed Anopheles diversity, abundance, behaviour, and Plasmodium infection rates in Kisumu city, Kenya.

Methods

Indoor and outdoor host-seeking and resting adult mosquitoes were collected using CDC miniature light traps (CDC-LT) and Prokopack aspirators along an urban–rural transect. Anophelines were identified morphologically, with Anopheles gambiae sensu lato (s.l.) and Anopheles funestus group further distinguished to siblings using polymerase chain reaction (PCR). Sporozoite infection rates were determined using a multiplexed real-time quantitative PCR (qPCR) assay.

Results

A total of 3,394 female Anopheles mosquitoes were collected: An. gambiae s.l. (68%), An. funestus s.l. (19.8%), Anopheles coustani (7.8%), Anopheles pharoensis (2.6%), Anopheles maculipalipis (1.6%), and Anopheles leesoni (0.2%). All six species were found in urban zone, but only three were in peri-urban and rural sites. Overall, urban collection accounted for 55.5% of mosquitoes, followed by peri-urban (30%) and rural sites (14.5%). Anopheles arabiensis dominated urban (84.3%) and peri-urban (89%) sites, while An. gambiae sensu stricto (s.s.) was predominant in rural zone (60.2%) alongside An. arabiensis (39.7%). Anopheles funestus was predominant in peri-urban (98.4%) and rural (85.7%) areas, while An. leesoni accounted for 1.6% and 14.3%, respectively. In urban areas, all An. funestus s.l. samples were An. funestus s.s.. Most (55.5%) of Anopheles mosquitoes were collected indoors, while secondary vectors were mainly outdoors. Overall, sporozoite rates were higher outdoors (3.5%) than indoors (1.45%) in rural areas. Indoor rates were 2.5% (An. funestus), 1.4% (An. gambiae s.s.), and 1% (An. arabiensis). Outdoors, An. gambiae had 5.3%, and An. arabiensis 2.1%. In peri-urban areas, An. gambiae had 2.3%. No sporozoites were found in urban samples.

Conclusion

The study highlights a shift in Anopheles diversity towards urban areas with increased outdoor activity and outdoor malaria transmission in rural and peri-urban areas, underscoring the need for tools targeting outdoor-biting mosquitoes. The presence of An. funestus in urban settings emphasizes the need for sustained entomological surveillance to inform integrated vector control.

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 centres 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 [5,6,7]. 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 construction activities, housing conditions, land use patterns, population density, transportation/migration, and waste generation/pollution, among other anthropogenic practices [11,12,13,14,15]. Peri-urban locations, which combine urban and rural characteristics, is likely to experience unique challenges due to changing environmental conditions and socioeconomic factors [16]. Rural areas, with diverse ecological conditions and traditional practices, typically have higher mosquito densities and infection rates [17,18,19]. 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 [19,20,21]. 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 [22].

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 [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 [9]. 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 creates favourable conditions for mosquitoes [20]. 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, 25] and climate change [26, 27] in Kenya and other developing African cities, underscores the need for robust mosquito surveillance in the urban centres. The main aim of this study was to assess malaria vector diversity, species composition, host-seeking and resting behaviours, 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.

Methods

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 [19]. Anopheles mosquito species in the peri-urban and rural of western Kenya lowlands include An. arabiensis, An. funestus, and An. gambiae [28, 29].

Fig. 1
figure 1

Map of Kenya (right corner) and Kisumu County (in expanded view) showing mosquito collection sites (circles) in the three sites (urban, peri-urban and rural areas in western Kenya

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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 m above the floor with a sleeping person protected under bed net indoors from 18:00 h to 06:00 h. and outdoors within 2 m of sentinel houses [30]. Collections were conducted in the morning from 6:00 h to 07:00 h. The trapping was conducted over four consecutive nights in five randomly selected houses per site within each of the three zones (urban, peri-urban, and rural) during each sampling period. 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 min. 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 [31]. Mosquitoes from each collection method were stored in vials labelled 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. 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. [34] for An. gambiae s.l., and Koekemoer et al. for An. funestus s.l. [32].

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 [33]. The DNA was analysed 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 Plasmodium falciparum, Plasmodium malariae, and Plasmodium ovale [34, 35].

Data management and analysis

Mosquito data were entered into Microsoft Excel spreadsheets for cleaning and visualization. Statistical analyses were performed using R software (version 4.0.3; R Foundation for Statistical Computing, Vienna, Austria). Before analysis, non-normalized data were transformed using the formula log10(x + 1). Vector densities from indoor and outdoor night collections were calculated as the number of female mosquitoes per trap per night for each collection method. Differences in mosquito composition and abundance (total counts) between sites and locations were tested using chi-squared tests. A t-test was used to compare the mean mosquito density between indoor and outdoor locations. Variations in mean densities between species and among sites were analysed using one-way analysis of variance (ANOVA). The sporozoite rate was calculated as the proportion of Anopheles mosquito samples that tested positive for Plasmodium species. A p-value of < 0.05 was considered statistically significant in all analyses.

Results

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
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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 (F2, 1092 = 14.45, P < 0.001). Overall, An. gambiae s.l. was the predominant species, comprising 68% (n = 2,309) of the total collection. This was followed by An. funestus s.l. (19.8%, n = 675), An. coustani s.l. (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, An. gambiae s.l. was the most abundant 55.3% (n = 1042) followed by An. funestus s.l. 25.5% (n = 480), An. coustani s.l. 11.5% (n = 216), An. pretoriensis 4.7% (n = 89), An. maculipalpis 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 s.l. and 3.3% (n = 34) An. coustani s.l.. In rural zone, An. gambiae s.l. was predominant species 74.8% (n = 396) followed by An. funestus s.l. 22.1% (n = 109), An. coustani s.l. 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 s.l. in urban zone was significantly higher than the outdoor density (t 74 = 2.67, p < 0.004) (Fig. 2A). In contrast, there was no significant difference in the mean indoor and outdoor host-seeking densities for An. gambiae s.l. in urban zone (p > 0.05). The secondary vectors mean outdoor host-seeking densities were marginally significant compared to the indoor densities for An. maculipalpis (t 9 = 1.96, p < 0.04) and An. coustani s.l. (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%).

Fig. 2
figure 2

Indoor and outdoor resting density of female Anopheles mosquitoes collected per trapping method A: Urban and B: Peri-urban and C: Rural sites in Kisumu, western Kenya

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There was no significant difference in the mean indoor and outdoor host-seeking densities for An. gambiae s.l. and the An. funestus s.l. (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 < 0.01), whereas the difference in the mean indoor and outdoor host-seeking densities for the An. funestus s.l. was not significant (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 areas was significantly higher than indoor density (t 66 = 2.2, p < 0.016) whereas, the difference in the mean indoor and outdoor resting density for An. funestus s.l. was not significant (p > 0.05) (Fig. 2A). The majority of An. maculipalpis 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 s.l. in peri-urban were not significant (p > 0.05) (Fig. 2B). In rural zones, the mean indoor resting density of An. gambiae s.l. was higher than outdoor (t 69 = 1.76, p < 0.042) (Fig. 2C). The proportion of An. funestus s.l. 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 s.l.) 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 s.l. samples assayed from the urban zone were An. funestus s.s. (hereafter An. funestus) (Fig. 3A). 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. 3B, C). Overall, there was a significant difference between indoor and outdoor locations in terms of An. funestus group species composition (χ2 = 21.34, df = 1, p < 0.001).

Fig. 3
figure 3

Anopheles gambiae s.l and An. funestus s.l sibling species composition, host-seeking and resting indoors and outdoors in A urban and B peri-urban and C Rural sites Kisumu, western Kenya

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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).

Table 2 Sporozoite rates of Anopheles mosquitoes from indoor and outdoor collections in Urban, peri-urban and rural zones in Kisumu, western Kenya
Full size table

Discussion

With over half of the world’s population now residing in urban areas and projections suggesting this could rise to 75% by 2050 [9], 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, 36]. 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 [8]. Gaining insight into mosquito species composition, ecology, and biting behavior in these developing African cities is essential for implementing effective vector control strategies [37]. 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 [38, 39]. This adaptability may be facilitated by urbanization-induced environmental changes, such as higher temperatures and lower humidity, which favor its survival [40]. The abundance of An. gambiae in rural areas can be attributed to its preference for unpolluted waters, 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, Central Africa [41]. 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 [41].

In addition to primary vectors, secondary vectors such as An. coustani group, An. pretoriensis, An. maculipalpis and An. pharoensis were abundant in urban areas, unlike the rural and peri-urban settings where only the An. coustani group and An. pharoensis were observed. A recent study from rural western Kenya reported an increase in secondary vectors [42] compared to previous findings [43]. The co-occurrence of primary and secondary vectors in the urban zone is concerning as it may lead to increased risk of malaria transmission. This increased vector presence could potentially amplify transmission risk if factors such as an increase in asymptomatic human reservoirs or enhanced vector survival create conditions favourable for Plasmodium development. 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 [44, 45]. Some of the factors likely contributing to vector occurrence in urban environments can be linked to climate change and anthropogenic influences. For instance, urban heat islands caused by human activities and the built environment creates localized temperature that differ significantly from surrounding rural areas. These altered microclimates provide favorable conditions for organisms, such as mosquitoes, that adapt well to warmer and more stable environments [27, 44, 46, 47]. 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 [43, 48, 49], 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 [50, 51], challenging the traditional indoor-focused interventions. Conversely, An. funestus and An. gambiae consistently exhibited indoor host-seeking and resting behaviours despite the use of LLINs, likely as a result of high insecticide resistance [49, 52]. 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. maculipalpis, An. coustani, An. pretoriensis, and An. pharoensis showed increased outdoor activity, particularly in urban areas, potentially evading primary interventions and sustaining malaria transmission. Their ability to harbour Plasmodium parasites [42, 53] emphasizes their significant epidemiological impact, highlighting the need for robust entomological surveillance and targeted vector control strategies.

Malaria persistence is linked to behavioural changes in anopheline mosquitoes [54]. 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. The higher abundance of vectors in urban areas, despite the absence of detectable sporozoite infections, suggests a complex interplay of factors influencing malaria transmission. 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 [55]. Moreover, urban-adapted malaria vectors have been reported to have a shorter lifespan compared to rural counterparts (4.1 days versus 11 days) [56], 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. Additionally, studies have reported variations in the prevalence of asymptomatic malaria cases across different ecotypes, with rural areas exhibiting a higher prevalence compared to urban areas [57]. Asymptomatic cases are known to serve as source of infection, contributing to sustained malaria transmission, particularly in rural malaria endemic regions [58]. This pattern has also been observed in the rural areas sampled in this study [59], which may explain the high sporozoite rates recorded at the rural site. Nonetheless, studies in West Africa have implicated An. arabiensis and An. funestus 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 [42, 43, 53]. 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.

Availability of data and materials

The dataset supporting the conclusions of this article is included within the article and its supplementary information files.

References

  1. 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;526:207–11.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. WHO. World malaria report 2022. Geneva: World Health Organization; 2023.

    Google Scholar 

  3. Lohnert B. Migration and the rural-urban transition in sub-Saharan Africa: Thesis; Humboldt-Universität zu Berlin; 2017.

  4. Doumbe-Belisse P, Kopya E, Ngadjeu C, 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. Malar J. 2021;20:1–18.

    Article  Google Scholar 

  5. Samarasekera U. A missed opportunity? Anopheles stephensi in Africa. Lancet. 2022;400:1914–5.

    Article  PubMed  Google Scholar 

  6. WHO. Vector alert: Anopheles stephensi invasion and spread: Horn of Africa, the Republic of the Sudan and surrounding geographical areas, and Sri Lanka: information note. Geneva: World Health Organization; 2019.

    Google Scholar 

  7. Takken W, Lindsay S. Increased threat of urban malaria from Anopheles stephensi mosquitoes. Africa Emerg Infect Dis. 2019;25:1431.

    Article  PubMed  Google Scholar 

  8. WHO. Global framework for the response to malaria in urban areas. Geneva: World Health Organization; 2022.

    Google Scholar 

  9. Kuddus MA, Tynan E, McBryde E. Urbanization: a problem for the rich and the poor? Public Health Rev. 2020;41:1.

    Article  PubMed  PubMed Central  Google Scholar 

  10. Yadouleton AWM, Asidi A, Djouaka RF, Braïma J, Agossou CD, Akogbeto MC. Development of vegetable farming: a cause of the emergence of insecticide resistance in populations of Anopheles gambiae in urban areas of Benin. Malar J. 2009;8:103.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Mathanga DP, Tembo AK, Mzilahowa T, Bauleni A, Mtimaukenena K, Taylor TE, et al. Patterns and determinants of malaria risk in urban and peri-urban areas of Blantyre, Malawi. Malar J. 2016;15:590.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Matthys B, N’Goran EK, Koné M, Koudou BG, Vounatsou P, Cissé G, et al. Urban agricultural land use and characterization of mosquito larval habitats in a medium-sized town of Côte d’Ivoire. J Vector Ecol. 2006;31:319–33.

    Article  PubMed  Google Scholar 

  13. Siri JG, Wilson ML, Murray S, Rosen DH, Vulule JM, Slutsker L, Lindblade KA. Significance of travel to rural areas as a risk factor for malarial anemia in an urban setting. Am J Trop Med Hyg. 2010;82:391–7.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Stoler J, Weeks JR, Getis A, Hill AG. Distance threshold for the effect of urban agriculture on elevated self-reported malaria prevalence in Accra, Ghana. Am J Trop Med Hyg. 2009;80:547–54.

    Article  PubMed  Google Scholar 

  15. Wilke AB, Caban-Martinez AJ, Ajelli M, Vasquez C, Petrie W, Beier JC. Mosquito adaptation to the extreme habitats of urban construction sites. Trends Parasitol. 2019;35:607–14.

    Article  PubMed  Google Scholar 

  16. 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.

    Article  PubMed  Google Scholar 

  17. 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;21:52–3.

    Article  PubMed  PubMed Central  Google Scholar 

  18. 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;28:154–8.

    Article  PubMed  PubMed Central  Google Scholar 

  19. 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;68:357–65.

    Article  PubMed  Google Scholar 

  20. 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. Parasit Vectors. 2010;3:118.

    Article  PubMed  PubMed Central  Google Scholar 

  21. De Silva PM, Marshall JM. Factors contributing to urban malaria transmission in sub-saharan Africa: a systematic review. J Trop Med. 2012;2012:819563.

    Article  PubMed  PubMed Central  Google Scholar 

  22. 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;4:730–43.

    Article  Google Scholar 

  23. 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. Malar J. 2021;20:364.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Dorling D. World population prospects at the UN: our numbers are not our problem? In: Deeming C, editor. The struggle for social sustainability: moral conflicts in global social policy. Bristol: Policy Press; 2021. p. 129–54.

    Google Scholar 

  25. Ochomo EO, Milanoi S, Abongo B, Onyango B, Muchoki M, Omoke D, et al. Detection of Anopheles stephensi mosquitoes by molecular surveillance, Kenya. Emerg Infect Dis. 2023;29:2498.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. 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. Pathog Glob Health. 2020;114:287–301.

    Article  PubMed  PubMed Central  Google Scholar 

  27. 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:e0009182.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. 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.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. 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;21:2178–81.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Lines J, Curtis C, Wilkes T, Njunwa K. Monitoring human-biting mosquitoes (Diptera: Culicidae) in Tanzania with light-traps hung beside mosquito nets. Bull Entomolo Res. 1991;81:77–84.

    Article  Google Scholar 

  31. Coetzee M. Key to the females of Afrotropical Anopheles mosquitoes (Diptera: Culicidae). Malar J. 2020;19:1–20.

    Article  Google Scholar 

  32. 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;66:804–11.

    Article  CAS  PubMed  Google Scholar 

  33. 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;37:37–41.

    Article  CAS  PubMed  Google Scholar 

  34. 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;47:975–80.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. 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;121:346–51.

    Article  CAS  PubMed  Google Scholar 

  36. 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;20:5774.

    Article  PubMed  PubMed Central  Google Scholar 

  37. 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;20:3597.

    Article  PubMed  PubMed Central  Google Scholar 

  38. 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.

    Article  Google Scholar 

  39. 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.

    Article  PubMed  Google Scholar 

  40. Ndiaye F, Diop A, Chabi J, Sturm-Ramirez K, Senghor M, Diouf EH, et al. Distribution and dynamics of Anopheles gambiae s.l. larval habitats in three Senegalese cities with high urban malaria incidence. PLoS ONE. 2024;19:e0303473.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. 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;27:10.

    Article  PubMed  PubMed Central  Google Scholar 

  42. 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. Parasit Vectors. 2021;14:252.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. 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;16:443.

    Article  PubMed  PubMed Central  Google Scholar 

  44. Afrane YA, Bonizzoni M, Yan G. Secondary malaria vectors of sub-Saharan Africa: threat to malaria elimination on the continent. In: Rodriguez-Morales AJ, editor. Current topics in malaria. London: IntechOpen; 2016.

    Google Scholar 

  45. Antonio-Nkondjio C, Kerah CH, Simard F, Awono-Ambene P, Chouaibou M, Tchuinkam T, et al. Complexity of the malaria vectorial system in Cameroon: contribution of secondary vectors to malaria transmission. J Med Entomol. 2006;43:1215–21.

    Article  PubMed  Google Scholar 

  46. Arnfield AJ. Two decades of urban climate research: a review of turbulence, exchanges of energy and water, and the urban heat island. Int J Climatol. 2003;23:1–26.

    Article  Google Scholar 

  47. LaDeau SL, Allan BF, Leisnham PT, Levy MZ. The ecological foundations of transmission potential and vector-borne disease in urban landscapes. Funct Ecol. 2015;29:889–901.

    Article  PubMed  PubMed Central  Google Scholar 

  48. 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;82:306–15.

    Article  CAS  PubMed  Google Scholar 

  49. 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:e0224718.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. 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.

    Article  PubMed  PubMed Central  Google Scholar 

  51. 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;18:445.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. 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:e0240771.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. 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;5:17952.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. 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;67:1218.

    Article  PubMed  PubMed Central  Google Scholar 

  55. 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;84:319–24.

    Article  Google Scholar 

  56. Coene J. Malaria in urban and rural Kinshasa: the entomological input. Med Vet Entomol. 1993;7:127–37.

    Article  CAS  PubMed  Google Scholar 

  57. Mbah CE, Ambe LA, Ngwewondo A, Kidzeru EB, Akwah L, Mountchissi C, et al. A comparative study of asymptomatic malaria in a forest rural and depleted forest urban setting during a low malaria transmission and COVID-19 pandemic period. BioMed Res Int. 2022;2022:2545830.

    Article  PubMed  PubMed Central  Google Scholar 

  58. Debash H, Tesfaw G, Ebrahim H, Shibabaw A, Melese Y, Tilahun M, et al. Symptomatic and asymptomatic malaria prevalence and its determinant factors in pastoral communities of Waghemira Zone, Northeast Ethiopia: a community-based cross-sectional study. Health Sci Rep. 2023;6:e1336.

    Article  PubMed  PubMed Central  Google Scholar 

  59. Oduma CO, Ogolla S, Atieli H, Ondigo BN, Lee M-C, Githeko AK, et al. Increased investment in gametocytes in asymptomatic Plasmodium falciparum infections in the wet season. BMC Infect Dis. 2021;21:44.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

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.

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Authors and Affiliations

  1. Centre for Global Health Research, Kenya Medical Research Institute, Kisumu, Kenya

    Maxwell G. Machani, Irene Nzioki, Sylvia Milanoi, Godfrey Nattoh, Andrew K. Githeko & Eric Ochomo

  2. School of Zoological Sciences, Kenyatta University, Nairobi, Kenya

    Shirley A. Onyango

  3. Kaimosi Friends University, Kaimosi, Kenya

    Godfrey Nattoh

  4. International Center of Excellence for Malaria Research, Tom Mboya University, Homa Bay, Kenya

    John Githure & Harrysone Atieli

  5. Department of Medical Microbiology, College of Health Sciences, University of Ghana Medical School, University of Ghana, Accra, Ghana

    Yaw A. Afrane

  6. Program in Public Health, College of Health Sciences, University of California, Irvine, CA, 92697, USA

    Chloe Wang, Ming-Chieh Lee, Goufa Zhou & Guiyun Yan

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  1. Maxwell G. Machani
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  2. Shirley A. Onyango
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Contributions

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.

Corresponding author

Correspondence to Maxwell G. Machani.

Ethics 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.

Competing interests

The authors declare no competing interests.

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Machani, M.G., Onyango, S.A., Nzioki, I. et al. Bionomics and distribution of malaria vectors in Kisumu city, Western Kenya: implications for urban malaria transmission. Malar J 24, 85 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12936-025-05332-7

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Keywords

Malaria Journal

ISSN: 1475-2875

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