Building the capacity of West African countries in Aedes surveillance: inaugural meeting of the West African Aedes Surveillance Network (WAASuN).

Arboviral diseases such as dengue, Zika and chikungunya transmitted by Aedes mosquitoes have been reported in 34 African countries. Available data indicate that in recent years there have been dengue and chikungunya outbreaks in the West Africa subregion, in countries including Côte d'Ivoire, Burkina Faso, Gabon, Senegal, and Benin. These viral diseases are causing an increased public health burden, which impedes poverty reduction and sustainable development. Aedes surveillance and control capacity, which are key to reducing the prevalence of arboviral infections, need to be strengthened in West Africa, to provide information essential for the formulation of effective vector control strategies and the prediction of arboviral disease outbreaks. In line with these objectives, the West African Aedes Surveillance Network (WAASuN) was created in 2017 at a meeting held in Sierra Leone comprising African scientists working on Aedes mosquitoes. This manuscript describes the proceedings and discusses key highlights of the meeting.

Resistance intensity status of Anopheles gambiae s.l. species at KOLOKOPE, eastern plateau Togo: A potential site to assess new vector control tools.

According to WHO recommendations, the deployment of the next generation of Long-Lasting Insecticidal Nets (LLINs) for malaria vector control requires appropriate investigations on the insecticide resistance profile of the vector. Most of the next generation of LLINs are impregnated with a combination of pyrethroid insecticides and piperonyl butoxide (PBO), a synergist with an additional impact on the increase in the mortality rate of Anopheles gambiae s.l. (Diptera: Culicidae). Kolokopé is a cotton-growing area in the central region of Togo characterized by an intensive use of agricultural pesticides and insecticides where there is a phase II experimental hut station. For the characterization of the site, WHO susceptibility tests using diagnostic doses of ten insecticides, PBO synergist assays and intensity assays of three pyrethroids (5x and 10x) were conducted on adult female mosquitoes obtained from larvae collected around the site. Anopheles gambiae s.l. from Kolokopé showed high resistance to pyrethroids and DDT, but to a lesser extent to carbamates and organophosphates. Likewise, high intensity of resistance to pyrethroid was observed with less than 40% mortality at 10x deltamethrin, 52 and 29% mortality at 10x permethrin and 10x alphacypermethrin, respectively. Also, PBO treatment resulted in increased mortality which was higher than the mortality rate at 10x doses of pyrethroids. The high pyrethroid intensity resistance recorded at Kolokopé could be mainly due to the selection pressure on An. gambiae s.l. caused by the excessive use of insecticide in agriculture. These results can be used to assess the next generation of LLINs either in experimental hut or at a community trial.

Diversity of larval habitats of Anopheles mosquitoes in urban areas of Benin and influence of their physicochemical and bacteriological characteristics on larval density.

BACKGROUND: The implementation of anti-larval strategies in the fight against malaria vectors requires fundamental knowledge of their oviposition sites. The aim of this study was to assess the spatial and temporal distribution of Anopheles breeding sites as well as the influence of abiotic and biotic factors on the proliferation of larvae in urban and non-urban areas of Benin. METHODS: Sampling of Anopheles larvae was carried out during the rainy and dry seasons in urbanized and non-urbanized areas of the cities of Cotonou, Bohicon, Parakou, and Natitingou in Benin. The Anopheles larval breeding sites were georeferenced and characterized by their nature, type, physicochemical (pH, temperature, dissolved oxygen, conductivity, turbidity, salinity) and biological attributes (larval density and coliform density). RESULTS: A total of 198 positive breeding sites for Anopheles larvae were identified, comprising 163 (82.3%) in the rainy season and 35 (17.7%) in the dry season. Out of these larval habitats, 61.9% were located in urbanized areas, and were predominantly puddles. Principal component analysis revealed a high positive correlation of larval density with temperature and dissolved oxygen, and with salinity in the coastal zone. In addition, cross-sectional analysis of the microbiological results with larval density showed a significant negative correlation between larval productivity and faecal coliform load. CONCLUSIONS: This study indicated the presence of multiple larval habitats of Anopheles in the urban areas which were created through human activities, and associations between larval density and intrinsic factors of the habitats such as temperature, dissolved oxygen and faecal coliform load. This type of information may be useful for the implementation of appropriate control strategies in urban areas, including regulation of the human activities that lead to the creation of breeding sites, proper environmental management and targeted larvicidal use.

Application of Deep Learning to Community-Science-Based Mosquito Monitoring and Detection of Novel Species.

Mosquito-borne diseases account for human morbidity and mortality worldwide, caused by the parasites (e.g., malaria) or viruses (e.g., dengue, Zika) transmitted through bites of infected female mosquitoes. Globally, billions of people are at risk of infection, imposing significant economic and public health burdens. As such, efficient methods to monitor mosquito populations and prevent the spread of these diseases are at a premium. One proposed technique is to apply acoustic monitoring to the challenge of identifying wingbeats of individual mosquitoes. Although researchers have successfully used wingbeats to survey mosquito populations, implementation of these techniques in areas most affected by mosquito-borne diseases remains challenging. Here, methods utilizing easily accessible equipment and encouraging community-scientist participation are more likely to provide sufficient monitoring. We present a practical, community-science-based method of monitoring mosquito populations using smartphones. We applied deep-learning algorithms (TensorFlow Inception v3) to spectrogram images generated from smartphone recordings associated with six mosquito species to develop a multiclass mosquito identification system, and flag potential invasive vectors not present in our sound reference library. Though TensorFlow did not flag potential invasive species with high accuracy, it was able to identify species present in the reference library at an 85% correct identification rate, an identification rate markedly higher than similar studies employing expensive recording devices. Given that we used smartphone recordings with limited sample sizes, these results are promising. With further optimization, we propose this novel technique as a way to accurately and efficiently monitor mosquito populations in areas where doing so is most critical.

Genome-environment association methods comparison supports omnigenic adaptation to ecological niche in malaria vector mosquitoes.

The concept of a fundamental ecological niche is central to questions of geographic distribution, population demography, species conservation, and evolutionary potential. However, robust inference of genomic regions associated with evolutionary adaptation to particular environmental conditions remains difficult due to the myriad of potential confounding processes that can generate heterogeneous patterns of variation across the genome. Here, we interrogate the potential role of genome environment association (GEA) testing as an initial step in building an understanding of the genetic basis of ecological niche. We leverage publicly available genomic data from the Anopheles gambiae 1000 Genomes (Ag1000g) Consortium to test the ability of multiple analytically unique GEA methods to handle confounding patterns of genetic variation, control false positive rates, and discern associations with broadly relevant climate variables from random allele frequency patterns throughout the genome. We found evidence supporting the ability of commonly implemented GEA methods to account for confounding patterns of spatial and genetic variation, and control false positive rates. However, we fail to find evidence supporting the ability of GEA tests to reject signals of adaptation to randomly simulated environmental variables, indicating that discerning between true signals of genome environment adaptation and genome environment correlations resulting from alternative evolutionary processes, remains challenging. Because signals of environmental adaptation are so diffuse and confounded throughout the genome, we argue that genomic adaptation to ecological niche is likely best understood under an omnigenic model wherein highly interconnected, genome-wide gene regulatory networks shape genomic adaptation to key environmental conditions.

Potential Roles of Environmental and Socio-Economic Factors in the Distribution of Insecticide Resistance in Anopheles gambiae sensu lato (Culicidae: Diptera) Across Togo, West Africa.

Vector control strategies recommended by the World Health Organization are threatened by resistance of Anopheles mosquitoes to insecticides. Information on the distribution of resistant genotypes of malaria vectors is increasingly needed to address the problem. Ten years of published and unpublished data on malaria vector susceptibility/resistance and resistance genes have been collected across Togo. Relationships between the spatial distribution of resistance status and environmental, socio-economic, and landscape features were tested using randomization tests, and calculating Spearman rank and Pearson correlation coefficients between mosquito mortality and different gridded values. Anopheles gambiae sensu lato was resistant to DDT, pyrethroids, and the majority of carbamates and organophosphates. Three sibling species were found (i.e., An. gambiae, Anopheles coluzzii, and Anopheles arabiensis) with four resistance genes, including kdr (L1014F, L1014S, and N1575Y) and ace1 (G119S). The most frequent resistance gene was L1014F. Overall, no association was found between the susceptibility/resistance status and environmental features, suggesting that evolution of resistance may be most closely related to extreme selection from local insecticide use. Nevertheless, further research is necessary for firm conclusions about this lack of association, and the potential role of landscape characteristics such as presence of crops and percentage of tree cover.

High Levels of Knockdown Resistance in Anopheles coluzzii and Anopheles gambiae (Diptera: Culicidae), Major Malaria Vectors in Togo, West Africa: A 2011 Monitoring Report.

A survey of susceptibility to DDT, deltamethrin, bendiocarb, and chlorpyrifos-methyl was conducted in five localities in 2011 in Togo, West Africa, to assess the insecticide resistance status of Anopheles gambiae s.l. (Diptera: Culicidae). Female populations of An. gambaie s.l. emerged from collected larvae (F0) were exposed to insecticide-impregnated papers using World Health Organization test kits for adult mosquitoes; the susceptible reference strain Kisumu was used as a control. Resistance to DDT and deltamethrin was observed within the mosquito populations tested. Anopheles gambiae s.s. and Anopheles coluzzii represented the only species recorded in the study sites. The frequency of knockdown resistance (kdr L1014F) mutation determined using polymerase chain reaction diagnostic tests was lower in An. gambiae than in An. coluzzii in all of the localities except Kolokopé. Further investigations of An. gambiae s.l. resistance are needed in Togo to help the National Malaria Control Programme in vector control decision making and implementation of resistance management strategy.

First report of the presence of L1014S Knockdown-resistance mutation in Anopheles gambiae s.s and Anopheles coluzzii from Togo, West Africa.

Background: To optimize the success of insecticide-based malaria control intervention, knowledge of the distribution of Anopheles gambiae species and insecticide resistance mechanisms is necessary. This paper reported an updated data on pyrethroids/DDT resistance in the An. gambiae s.l population from Togo.  Methods: From December 2013 to April 2015, females of indoor-resting An. gambiae s.l were captured in three locations belonging to three different ecological zones. Resistance to DDT, permethrin and deltamethrin was screened in F1 progeny of collected mosquitoes using WHO susceptibility tests. The identification of species of An. gambiae complex and the detection of kdr and ace.1 R allele were carried out using DNA-based molecular techniques. Results:An. gambiae from Kovié and Nangbéto were highly resistant to DDT and permethrin with mortalities rate ranging from 0.83% to 1.58% for DDT and zero to 8.54% for permethrin. Mosquitoes collected in Nangbéto displayed 81.53% mortality with deltamethrin. An. coluzzii and An. gambiae s.s were found in sympatry in Nangbéto and Mango . The allelic frequency of L1014F was high, ranging from 66 to 100% in both An. coluzzii and An. gambiae s.s. For the first time we detected the L1014S allele in both An. coluzzii and An. gambiaes.s. from Togo at the frequency ranging from 5% to 13% in all the sites. The kdr N1575Y was present at various frequencies in both species ranging from 10% to 45%. Both An. gambiae s.s. and An. coluzzii shared the ace1 R mutation in all investigated sites with allelic frequency ranging from 4% to 16%. Conclusion: These results showed that multiple mutations are involved in insecticides resistance in An. gambiae populations from Togo including the kdr L1014F, L1014S, and N1575Y and ace.1 R G119S mutations.