Spatial-temporal pattern of malaria in Burkina Faso from 2013 to 2020.

Despite the implementation of different strategies to fight against malaria in Burkina Faso since 2005, it remains today the leading cause of hospitalization and death. Adapting interventions to the spatial and temporal distribution of malaria could help to reduce this burden. This study aims to determine the structure and stability of malaria hotspots in Burkina Faso, with the objective of adapting interventions at small geographical scales. Data on malaria cases from 2013 to 2020 were acquired at municipalities level. Municipality-wise malaria endemicity levels were mapped through geographical information system (GIS) tools. Spatial statistical analysis using Kulldoff sweeps were carried out to identify malaria hotspots. Then we mapped the monthly malaria risk. Malaria is endemic in all the municipalities of Burkina Faso. However, two stable main spatial clusters (South-Western and Eastern part of the country) are emerging with seasonal reinforcement. Interventions targeting the identified clusters could significantly reduce the incidence of malaria in Burkina Faso. This also prompts for further studies to identify the local determinants of this high transmission for the future success of malaria control

Insecticide resistance profiles of Anopheles gambiae s.l. in Togo and genetic mechanisms involved, during 3-year survey: Is there any need for resistance management?

This work is licensed under a Creative Commons Attribution 4.0 International License.Background Malaria, one of the world’s greatest public health challenges, is an endemic disease with stable transmission in Togo. Combating malaria requires an effective vector control. This study provides temporal data on insecticide resistance status in the major malaria vector Anopheles gambiae sensu lato (s.l.) from Togo. Methods Two to 5 days old females of An. gambiae s.l., originating from three localities (Baguida, Kovié, Kolokopé) were subjected to insecticide-impregnated papers during 3 years (2012, 2013, 2016) as follows: organochlorides (4% DDT), pyrethroids (0.05% deltamethrin, 0.75% permethrin, 0.05% lambdacyhalothrin), carbamates (0.4% bendiocarb and 0.1% propoxur), and organophosphates (5% malathion, 0.4% chlorpyrifos methyl, 1% fenitrothion) following the WHO standard protocol. Dead and surviving mosquitoes were stored separately in Eppendorf tubes containing silica gel for DNA extraction, species identification, and kdr and ace-1 genotyping. Results Knockdown times (KDT50 and KDT95) were high in An. gambiae s.l. The lowest KDTs were recorded at Baguida in 2013 for deltamethrin (KDT50 = 24.7, CI [22.4–27.12] and KDT95 = 90.78, CI [76.35–113.49]). No KDTs were recorded for DDT and in some instances for permethrin. In general, An. gambiae s.l. was resistant to most of the four classes of insecticides during the survey periods regardless of locality and year, except to chlorpyrifos methyl. In some instances, mosquitoes were fully susceptible to fenitrothion (Kolokopé: 100% and Kovié: 98.05%, CI [95.82–100.26]) and malathion (100% at both Kolokopé and Kovié) in 2013, and malathion only (Kolokopé; 100%) in 2016. Anopheles coluzzii, An. gambiae and Anopheles arabiensis were the three sibling species identified at the three localities with some hybrids at Baguida (2013), and Kovié (2012 and 2016), respectively. Anopheles gambiae was relatively dominant (61.6%). The kdr 1014F allele frequency was > 0.9 in most of the cases, except at Kolokopé (f (1014F) = 0.63, CI [0.55–0.71]) in 2013. The kdr 1014S allele frequency was below 0.02. The highest ace-1 frequencies were identified in An. gambiae at Baguida (2012: 0.52, CI [0.34–0.69] and 2013: 0.66, CI [0.46–0.86]). Conclusion The resistance status is worrying in Togo and should be considered in future malaria vector resistance management programmes by decision-makers.Organization for Women in Science for the Developing Worl

Surveys of Arboviruses Vectors in Four Cities Stretching Along a Railway Transect of Burkina Faso: Risk Transmission and Insecticide Susceptibility Status of Potential Vectors

Background: A severe outbreak of dengue occurred in Burkina Faso in 2016, with the most cases reported in Ouagadougou, that highlights the necessity to implement vector surveillance system. This study aims to estimate the risk of arboviruses transmission and the insecticide susceptibility status of potential vectors in four sites in Burkina Faso.Methods: From June to September 2016, house-to-house cross sectional entomological surveys were performed in four cities stretching along a southwest-to-northeast railway transect. The household surveys analyzed the presence of Aedes spp. larvae in containers holding water and the World Health Organization (WHO) larval abundance indices were estimated. WHO tube assays was used to evaluate the insecticide susceptibility within Aedes populations from these localities.Results: A total of 31,378 mosquitoes' larvae were collected from 1,330 containers holding water. Aedes spp. was the most abundant (95.19%) followed by Culex spp. (4.75%). Aedes aegypti a key vector of arboviruses (ARBOV) in West Africa was the major Aedes species found (98.60%). The relative larval indices, house index, container and Breteau indexes were high, up to 70, 35, and 10, respectively. Aedes aegypti tended to breed mainly in discarded tires and terracotta jars. Except in Banfora the western city, Ae. aegypti populations were resistant to deltamethrin 0.05% in the other localities with low mortality rate under 20% in Ouagadougou whereas they were fully susceptible to malathion 5% whatever the site. Intermediate resistance was observed in the four sites with mortality rates varying between 78 and 94% with bendiocarb 0.1%.Conclusions: This study provided basic information on entomological indices that can help to monitor the risks of ARBOV epidemics in the main cities along the railway in Burkina Faso. In these cities, all larval indices exceeded the risk level of ARBOV outbreak. Aedes aegypti the main species collected was resistant to deltamethrin 0.05% and bendiocarb 0.1% whereas they were fully susceptible to malathion 5%. The monitoring of insecticide resistance is also important to be integrated to the vector surveillance system in Burkina Faso

Evidence that agricultural use of pesticides selects pyrethroid resistance within Anopheles gambiae s.l. populations from cotton growing areas in Burkina Faso, West Africa.

Many studies have shown the role of agriculture in the selection and spread of resistance of Anopheles gambiae s.l. to insecticides. However, no study has directly demonstrated the presence of insecticides in breeding sources as a source of selection for this resistance. It is in this context that we investigated the presence of pesticide residues in breeding habitats and their formal involvement in vector resistance to insecticides in areas of West Africa with intensive farming. This study was carried out from June to November 2013 in Dano, southwest Burkina Faso in areas of conventional (CC) and biological cotton (BC) growing. Water and sediment samples collected from breeding sites located near BC and CC fields were submitted for chromatographic analysis to research and titrate the residual insecticide content found there. Larvae were also collected in these breeding sites and used in toxicity tests to compare their mortality to those of the susceptible strain, Anopheles gambiae Kisumu. All tested mosquitoes (living and dead) were analyzed by PCR for species identification and characterization of resistance genes. The toxicity analysis of water from breeding sites showed significantly lower mortality rates in breeding site water from biological cotton (WBC) growing sites compared to that from conventional cotton (WCC) sites respective to both An. gambiae Kisumu (WBC: 80.75% vs WCC: 92.75%) and a wild-type strain (49.75% vs 66.5%). The allele frequencies L1014F, L1014S kdr, and G116S ace -1R mutations conferring resistance, respectively, to pyrethroids and carbamates / organophosphates were 0.95, 0.4 and 0.12. Deltamethrin and lambda-cyhalothrin were identified in the water samples taken in October/November from mosquitoes breeding in the CC growing area. The concentrations obtained were respectively 0.0147ug/L and 1.49 ug/L to deltamethrin and lambdacyhalothrin. Our results provided evidence by direct analysis (biological and chromatographic tests) of the role of agriculture as a source of selection pressure on vectors to insecticides used in growing areas

Analysis of the Genetic Variation of the Fruitless Gene within the Anopheles gambiae (Diptera: Culicidae) Complex Populations in Africa

Targeting genes involved in sexual determinism, for vector or pest control purposes, requires a better understanding of their polymorphism in natural populations in order to ensure a rapid spread of the construct. By using genomic data from An. gambiae s.l., we analyzed the genetic variation and the conservation score of the fru gene in 18 natural populations across Africa. A total of 34,339 SNPs were identified, including 3.11% non-synonymous segregating sites. Overall, the nucleotide diversity was low, and the Tajima’s D neutrality test was negative, indicating an excess of low frequency SNPs in the fru gene. The allelic frequencies of the non-synonymous SNPs were low (freq < 0.26), except for two SNPs identified at high frequencies (freq > 0.8) in the zinc-finger A and B protein domains. The conservation score was variable throughout the fru gene, with maximum values in the exonic regions compared to the intronic regions. These results showed a low genetic variation overall in the exonic regions, especially the male sex-specific exon and the BTB-exon 1 of the fru gene. These findings will facilitate the development of an effective gene drive construct targeting the fru gene that can rapidly spread without encountering resistance in wild populations

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

Uneven malaria transmission in geographically distinct districts of Bobo-Dioulasso, Burkina Faso

Abstract Background Urbanization is a main trend in developing countries and leads to health transition. Although non-communicable diseases are increasing in cities of low-income countries, vector-borne diseases such as malaria, are still present. In the case of malaria, transmission is lower than in rural areas, but is uneven and not well documented. In this study, we wanted to evaluate intra-urban malaria transmission in a West African country (Burkina Faso). Methods A cross-sectional study on 847 adults (35 to 59 year-old) and 881 children (6 months to 5 year-old) living in 1045 households of four districts (Dogona, Yeguere, Tounouma and Secteur 25) of Bobo-Dioulasso was performed between October and November 2013. The districts were selected according to a geographical approach that took into account the city heterogeneity. Malaria prevalence was evaluated using thick and thin blood smears. Human exposure to Anopheles bites was measured by assessing the level of IgG against the Anopheles gSG6-P1 salivary peptide. Adult mosquitoes were collected using CDC traps and indoor insecticide spraying in some houses of the four neighbourhoods. The Anopheles species and Plasmodium falciparum infection rate were determined using PCR assays. Results In this study, 98.5% of the malaria infections were due to Plasmodium falciparum. Malaria transmission occurred in the four districts. Malaria prevalence was higher in children than in adults (19.2 vs 4.4%), and higher in the central districts than in the peripheral ones (P = 0.001). The median IgG level was more elevated in P. falciparum-infected than in non-infected individuals (P < 0.001). Anopheles arabiensis was the main vector identified (83.2%; 227 of the 273 tested mosquito specimens). Five P. falciparum-infected mosquitoes were caught, and they were all caught in the central district of Tounouma where 28.6% (14/49) of the tested blood-fed mosquito specimens had a human blood meal. Conclusions This study showed that urban malaria transmission occurred in Bobo-Dioulasso, in all the four studied areas, but mainly in central districts. Environmental determinants primarily explain this situation, which calls for better urban management

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