Over the past 20 years, numerous studies have investigated the ecology and behaviour of malaria vectors and Plasmodium falciparum malaria transmission on the coast of Kenya. Substantial progress has been made to control vector populations and reduce high malaria prevalence and severe disease. The goal of this paper was to examine trends over the past 20 years in Anopheles species composition, density, blood-feeding behaviour, and P. falciparum sporozoite transmission along the coast of Kenya.

The scaling up of malaria vector control efforts in Africa has resulted in changing the malaria vectorial systems across different ecological settings. In view of the ongoing trends in vector population dynamics, abundance, species composition and parasite infectiousness, there is a need to understand vector distribution and their contribution to malaria transmission to facilitate future planning of control strategies. We studied indoor and outdoor malaria transmission dynamics and vector population variability of Anopheles mosquitoes in Taveta district along the Kenyan Coast.

Insecticide resistance has emerged as one of the major challenges facing National Malaria Control Programmes in Africa. A well-coordinated national database on insecticide resistance (IRBase) can facilitate the development of effective strategies for managing insecticide resistance and sustaining the effectiveness of chemical-based vector control measures. The aim of this study was to assemble a database on the current status of insecticide resistance among malaria vectors in Kenya. Data was obtained from published literature through PubMed, HINARI and Google Scholar searches and unpublished literature from government reports, research institutions reports and malaria control programme reports. Each data source was assigned a unique identification code and entered into Microsoft Excel 2010 datasheets. Base maps on the distribution of insecticide resistance and resistance mechanisms among malaria vectors in Kenya were generated using ArcGIS Desktop 10.1 (ESRI, Redlands, CA, USA). Insecticide resistance status among the major malaria vectors in Kenya was reported in all the four classes of insecticides including pyrethroids, carbamates, organochlorines and organophosphates. Resistance to pyrethroids has been detected in Anopheles gambiae (s.s.), An. arabiensis and An. funestus (s.s.) while resistance to carbamates was limited to An. gambiae (s.s.) and An. arabiensis. Resistance to the organochlorine was reported in An. gambiae (s.s.) and An. funestus (s.s.) while resistance to organophosphates was reported in An. gambiae (s.l.) only. The mechanisms of insecticide resistance among malaria vectors reported include the kdr mutations (L 1014S and L 1014F) and elevated activity in carboxylesterase, glutathione S-transferases (GST) and monooxygenases. The kdr mutations L 1014S and L 1014F were detected in An. gambiae (s.s.) and An. arabiensis populations. Elevated activity of monooxygenases has been detected in both An. arabiensis and An. gambiae (s.s.) populations while the elevated activity of carboxylesterase and GST has been detected only in An. arabiensis populations. The geographical maps show the distribution of insecticide resistance and resistance mechanisms among malaria vectors in Kenya. The database generated will provide a guide to intervention policies and programmes in the fight against malaria.

Increased use of long-lasting insecticidal nets (LLINs) over the last decade has considerably improved the control of malaria in sub-Saharan Africa. However, there is still a paucity of data on the influence of LLIN use and other factors on mosquito bionomics in different epidemiological foci. The objective of this study was to provide updated data on the evolution of vector bionomics and malaria transmission patterns in the equatorial forest region of Cameroon over the period 2000–2017, during which LLIN coverage has increased substantially. The study was conducted in Olama and Nyabessan, two villages situated in the equatorial forest region. Mosquito collections from 2016–2017 were compared to those of 2000–2001. Mosquitoes were sampled using both human landing catches and indoor sprays, and were identified using morphological taxonomic keys. Specimens belonging to the An. gambiae complex were further identified using molecular tools. Insecticide resistance bioassays were undertaken on An. gambiae to assess the susceptibility levels to both permethrin and deltamethrin. Mosquitoes were screened for Plasmodium falciparum infection and blood-feeding preference using the ELISA technique. Parasitological surveys in the population were conducted to determine the prevalence of Plasmodium infection using rapid diagnostic tests. A change in the species composition of sampled mosquitoes was recorded between the 2000–2001 collections and those of 2016–2017. A drop in the density of the local primary vectors An. nili and An. moucheti in the forest region was recorded, whereas there was an increase in the density of An. gambiae (s.l.), An. marshallii, An. ziemannii and An. paludis. A change in the biting behaviour from indoor to outdoor was recorded in Olama. Very few indoor resting mosquitoes were collected. A change in the night biting cycle was recorded with mosquitoes displaying a shift from night biting to late evening/early in the night. Several mosquitoes were found positive for Plasmodium infection, thus sustaining continuous transmission of malaria in both sites. Reduction of malaria transmission in Nyabessan was lower than that seen in Olama and associated with deforestation and the construction of a dam that may have enabled a more efficient vector, An. gambiae (s.l.), to invade the area. A high level of resistance to pyrethroids (permethrin and deltamethrin) was detected for An. gambiae in both sites. High parasite prevalence was recorded in both sites, with children of 0–16 years being the most affected. In both Olama and Nyabessan, bed net usage appeared to correlate to protection against malaria infection. The study shows important changes in the bionomics of vector populations and malaria transmission patterns in the equatorial forest region. The changes call for more concerted efforts to address challenges such as insecticide resistance, environmental modifications or behavioural changes affecting the performance of current control measures.

Targeted malaria control interventions are expected to be cost-effective. Clinical, parasitological and serological markers of malaria transmission have been used to detect malaria transmission hotspots, but few studies have examined the relationship between the different potential markers in low transmission areas. The present study reports on the relationships between clinical, parasitological, serological and entomological markers of malaria transmission in an area of low transmission intensity in Coastal Kenya. Longitudinal data collected from 831 children aged 5–17 months, cross-sectional survey data from 800 older children and adults, and entomological survey data collected in Ganze on the Kenyan Coast were used in the present study. The spatial scan statistic test used to detect malaria transmission hotspots was based on incidence of clinical malaria episodes, prevalence of asymptomatic asexual parasites carriage detected by microscopy and polymerase chain reaction (PCR), seroprevalence of antibodies to two Plasmodium falciparum merozoite antigens (AMA1 and MSP1-19) and densities of Anopheles mosquitoes in CDC light-trap catches. There was considerable overlapping of hotspots by these different markers, but only weak to moderate correlation between parasitological and serological markers. PCR prevalence and seroprevalence of antibodies to AMA1 or MSP1-19 appeared to be more sensitive markers of hotspots at very low transmission intensity. These findings may support the choice of either serology or PCR as markers in the detection of malaria transmission hotspots for targeted interventions.

Background: The distribution of anopheline mosquitoes is determined by temporally dynamic environmental and human-associated variables, operating over a range of spatial scales. Macro-spatial short-term trends are driven predominantly by prior (lagged) seasonal changes in climate, which regulate the abundance of suitable aquatic larval habitats. Micro-spatial distribution is determined by the location of these habitats, proximity and abundance of available human bloodmeals and prevailing micro-climatic conditions. The challenge of analysing—in a single coherent statistical framework—the lagged and distributed effect of seasonal climate changes simultaneously with the effects of an underlying hierarchy of spatial factors has hitherto not been addressed.Methods: Data onAnopheles gambiaesensu stricto andA. funestuscollected from households in Kilifi district, Kenya, were analysed using polynomial distributed lag generalized linear mixed models (PDL GLMMs).Results: Anopheline density was positively and significantly associated with amount of rainfall between 4 to 47 days, negatively and significantly associated with maximum daily temperature between 5 and 35 days, and positively and significantly associated with maximum daily temperature between 29 and 48 days in the past (depending onAnophelesspecies). Multiple-occupancy households harboured greater mosquito numbers than single-occupancy households. A significant degree of mosquito clustering within households was identified.Conclusions: The PDL GLMMs developed here represent a generalizable framework for analysing hierarchically-structured data in combination with explanatory variables which elicit lagged effects. The framework is a valuable tool for facilitating detailed understanding of determinants of the spatio-temporal distribution ofAnopheles. Such understanding facilitates delivery of targeted, cost-effective and, in certain circumstances, preventative antivectorial interventions against malaria.