Efficacy of Interceptor

Background: The widespread insecticide resistance in malaria vector populations is a serious threat to the efficacy of vector control tools. As a result, the World Health Organization (WHO) supports the development of alternative tools that combine several insecticides with the aim of improving vector control and the management of insecticide resistance. In the present study, a long-lasting insecticidal net treated with a mixture of chlorfenapyr and alphacypermethrin was evaluated against wild pyrethroid-resistant Anopheles gambiae s.s in M’bé, Côte d’Ivoire. Centers for Disease Control and Prevention (CDC) bottle tests were carried out with resistant An. gambiae s.s. of M’bé and the susceptible strain, to assess the resistance level to chlorfenapyr and alphacypermethrin. Results: CDC bottle bioassays revealed a high level of resistance of An. gambiae s.s. population from M’bé to alphacypermethrin, whereas they revealed low resistance to chlorfenapyr. In experimental huts, Interceptor® G2 that was unwashed or washed 20 times killed 87% and 82% of An. gambiae s.s., respectively, whereas Interceptor® LN that was either unwashed or washed 20 times killed only about 10% of the mosquitoes. The blood-feeding inhibition induced by Interceptor® was not significantly different compared to untreated nets, whereas Interceptor® G2 that was unwashed or washed 20 times induced 42% and 34% inhibition of blood-feeding, respectively. Conclusion: Interceptor® G2 met the WHOPES criteria to undergo a phase III study. Investigation of its efficacy at a community level and the conduct of randomized controlled trials dealing with epidemiological outputs are warranted in order to study the potential of Interceptor® G2 to better protect communities

Physiological and behavioural resistance of malaria vectors in rural West-Africa: a data mining study to address their fine-scale spatiotemporal heterogeneity, drivers, and predictability

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Insecticide resistance and biting behaviour of malaria vectors in rural West-Africa : a data mining study to adress their fine-scale spatiotemporal heterogeneity, drivers, and predictability

Insecticide resistance and behavioral adaptation of malaria mosquitoes impact the efficacy of long-lasting insecticide nets - currently the main malaria vector control tool. To develop and deploy complementary, efficient and cost-effective control interventions, a good understanding of the drivers of these physiological and behavioural traits is needed. In this data-mining work, we modeled a set of indicators of physiological resistances to insecticide (prevalence of three target-site mutations) and biting behaviours (early- and late-biting, exophagy) of anopheles mosquitoes in two rural areas of West-Africa, located in Burkina Faso and Cote d’Ivoire. To this aim, we used mosquito field collections along with heterogeneous, multisource and multi-scale environmental data. The objectives were i) to assess the small-scale spatial and temporal heterogeneity of the indicators, ii) to better understand their drivers, and iii) to assess their spatio-temporal predictability, at scales that are consistent with operational action. The explanatory variables covered a wide range of potential environmental determinants of vector resistance to insecticide or feeding behaviour : vector control, human availability and nocturnal behaviour, macro and micro-climatic conditions, landscape, etc. The resulting models revealed many statistically significant associations, although their predictive powers were overall weak. We interpreted and discussed these associations in light of several topics of interest, such as : respective contribution of public health and agriculture in the development of physiological resistances, biological costs associated with physiological resistances, biological mechanisms underlying biting behavior, and impact of micro-climatic conditions on the time or place of biting. To our knowledge, our work is the first studying insecticide resistance and feeding behaviour of malaria vectors at such fine spatial scale with such a large dataset of both mosquito and environmental data

Data-driven and interpretable machine-learning modeling to explore the fine-scale environmental determinants of malaria vectors biting rates in rural Burkina Faso

International audienceBackground Improving the knowledge and understanding of the environmental determinants of malaria vector abundance at fine spatiotemporal scales is essential to design locally tailored vector control intervention. This work is aimed at exploring the environmental tenets of human-biting activity in the main malaria vectors ( Anopheles gambiae s.s. , Anopheles coluzzii and Anopheles funestus ) in the health district of Diébougou, rural Burkina Faso.Methods Anopheles human-biting activity was monitored in 27 villages during 15 months (in 2017–2018), and environmental variables (meteorological and landscape) were extracted from high-resolution satellite imagery. A two-step data-driven modeling study was then carried out. Correlation coefficients between the biting rates of each vector species and the environmental variables taken at various temporal lags and spatial distances from the biting events were first calculated. Then, multivariate machine-learning models were generated and interpreted to (i) pinpoint primary and secondary environmental drivers of variation in the biting rates of each species and (ii) identify complex associations between the environmental conditions and the biting rates.Results Meteorological and landscape variables were often significantly correlated with the vectors’ biting rates. Many nonlinear associations and thresholds were unveiled by the multivariate models, for both meteorological and landscape variables. From these results, several aspects of the bio-ecology of the main malaria vectors were identified or hypothesized for the Diébougou area, including breeding site typologies, development and survival rates in relation to weather, flight ranges from breeding sites and dispersal related to landscape openness.Conclusions Using high-resolution data in an interpretable machine-learning modeling framework proved to be an efficient way to enhance the knowledge of the complex links between the environment and the malaria vectors at a local scale. More broadly, the emerging field of interpretable machine learning has significant potential to help improve our understanding of the complex processes leading to malaria transmission, and to aid in developing operational tools to support the fight against the disease (e.g. vector control intervention plans, seasonal maps of predicted biting rates, early warning systems). Graphical abstrac

The current insecticide resistance status of Anopheles gambiae (s.l.) (Culicidae) in rural and urban areas of Bouaké, Côte d’Ivoire

Abstract Background Several studies were carried out in experimental hut station in areas surrounding the city of Bouaké, after the crisis in Côte d’Ivoire. They reported increasing resistance levels to insecticide for malaria transmiting mosquitoes. The present work aims to evaluate the current resistance level of An. gambiae ( s.l.) in rural and urban areas in the city of Bouaké. Methods Larvae of Anopheles gambiae (s.l.) were collected from five different study sites and reared to adult stages. The resistance status was assessed using the WHO bioassay test kits for adult mosquitoes, with eight insecticides belonging to pyrethroids, organochlorines, carbamates and organophosphates classes. Molecular assays were performed to identify the molecular forms of An. gambiae (s.l.), the L1014F kdr and the ace-1R alleles in individual mosquitoes. The synergist PBO was used to investigate the role of enzymes in resistance. Biochemical assays were performed to detect potential increased activities in mixed function oxidase (MFO) levels, non-specific esterases (NSE) and glutathione S-transferases (GST). Results High resistance levels to pyrethroids, organochlorines, and carbamates were observed in Anopheles gambiae (s.l.) from Bouaké. Mortalities ranged between 0 and 73% for the eight tested insecticides. The pre-exposure to PBO restored full or partial susceptibility to pyrethroids in the different sites. The same trend was observed with the carbamates in five sites, but to a lesser extent. With DDT, pre-exposure to PBO did not increase the mortality rate of An. gambiae (s.l.) from the same sites. Tolerance to organophosphates was observed. An increased activity of NSE and higher level of MFO were found compared to the Kisumu susceptible reference strain. Two molecular forms, S form [(An. gambiae (s.s)] and M form (An. coluzzi) were identified. The kdr allele frequencies vary from 85.9 to 99.8% for An. gambiae (s.s.) and from 81.7 to 99.6% for An. coluzzii. The ace-1R frequencies vary between 25.6 and 38.8% for An. gambiae (s.s.) and from 28.6 to 36.7% for An. coluzzii. Conclusion Resistance to insecticides is widespread within both An. gambiae (s.s.) and An. coluzzii. Two mechanisms of resistance, i.e. metabolic and target-site mutation seemed to largely explain the high resistance level of mosquitoes in Bouaké. Pyrethroid resistance was found exclusively due to the metabolic mechanism

Insecticide resistance status of malaria vectors Anopheles gambiae (s.l.) of southwest Burkina Faso and residual efficacy of indoor residual spraying with microencapsulated pirimiphos-methyl insecticide

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Anopheles bionomics, insecticide resistance and malaria transmission in southwest Burkina Faso: A pre-intervention study

International audienc

Entomological monitoring data driving decision-making for appropriate and sustainable malaria vector control in Côte d’Ivoire

Abstract Background Entomological surveillance provides critical information on vectors for appropriate malaria vector control and strategic decision-making. The widely documented insecticide resistance of malaria vectors in Côte d’Ivoire requires that any vector control intervention deployment be driven by entomological data to optimize its effectiveness and appropriate resource allocations. To achieve this goal, this study documents the results of monthly vector surveillance and insecticide susceptibility tests conducted in 2019 and a review of all previous entomological monitoring data used to guide vector control decision making. Furthermore, susceptibility to pirimiphos-methyl and clothianidin was assessed in addition to chlorfenapyr and pyrethroids (intensity and piperonyl butoxide (PBO) synergism) tests previously reported. Vector bionomic data were conducted monthly in four sites (Sakassou, Béoumi, Dabakala and Nassian) that were selected based on their reported high malaria incidence. Adult mosquitoes were collected using human landing catches (HLCs), pyrethrum spray catches (PSCs), and human-baited CDC light traps to assess vector density, behaviour, species composition and sporozoite infectivity. Results Pirimiphos-methyl and clothianidin susceptibility was observed in 8 and 10 sites, respectively, while previous data reported chlorfenapyr (200 µg/bottle) susceptibility in 13 of the sites, high pyrethroid resistance intensity and increased mortality with PBO pre-exposure at all 17 tested sites. Anopheles gambiae sensu lato was the predominant malaria vector collected in all four bionomic sites. Vector density was relatively higher in Sakassou throughout the year with mean biting rates of 278.2 bites per person per night (b/p/n) compared to Béoumi, Dabakala and Nassian (mean of 48.5, 81.4 and 26.6 b/p/n, respectively). The mean entomological inoculation rate (EIR) was 4.44 infective bites per person per night (ib/p/n) in Sakassou, 0.34 ib/p/n in Beoumi, 1.17 ib/p/n in Dabakala and 1.02 ib/p/n in Nassian. The highest EIRs were recorded in October in Béoumi (1.71 ib/p/n) and Nassian (3.22 ib/p/n), in July in Dabakala (4.46 ib/p/n) and in May in Sakassou (15.6 ib/p/n). Conclusion Based on all results and data review, the National Malaria Control Programme developed and implemented a stratified insecticide-treated net (ITN) mass distribution in 2021 considering new generation ITNs. These results also supported the selection of clothianidin-based products and an optimal spraying time for the first indoor residual spraying (IRS) campaign in Sakassou and Nassian in 2020