Mapping trends in insecticide resistance phenotypes in African malaria vectors

Abstract

Mitigating the threat of insecticide resistance in African malaria vector populations requires comprehensive information about where resistance occurs, to what degree, and how this has changed over time. Estimating these trends is complicated by the sparse, heterogeneous distribution of observations of resistance phenotypes in field populations. We use 6,423 observations of the prevalence of resistance to the most important vector control insecticides to inform a Bayesian geostatistical ensemble modelling approach, generating fine-scale predictive maps of resistance phenotypes in mosquitoes from the Anopheles gambiae complex across Africa. Our models are informed by a suite of 111 predictor variables describing potential drivers of selection for resistance. Our maps show alarming increases in the prevalence of resistance to pyrethroids and DDT across sub-Saharan Africa from 2005 to 2017, with mean mortality following insecticide exposure declining from almost 100% to less than 30% in some areas, as well as substantial spatial variation in resistance trends.

Mapping insecticide resistance in mosquitoes to aid malaria control

“…This ensemble model generated a posterior distribution of predictions for every cell in a fine resolution (2.5 arc minute, approximately 5km) grid. Validation of the outputs by Hancock et al using withheld data (out-of-sample validation) showed that the ensemble model produced robust predictions within the area and time-frame for which data on pyrethroid resistance were available (6). For the current study we used the model output for mortality after deltamethrin exposure in a standard susceptibility test.…”

“…To address these issues, we propose using the results of a recently developed geostatistical ensemble model that was fitted to a published series of susceptibility test surveillance data covering 31 African countries and spanning a period of 13 years (6,15). The geostatistical ensemble model accounts for noise in the susceptibility test data and provides a set of thirteen fine-resolution, annual maps for each year from 2005 to 2017, representing the mean prevalence of resistance in Anopheles gambiae s.l.…”

“…Further, the model was re-run to test its ability to provide next-year predictions. The ensemble model has been described in full by Hancock et al (6). Briefly, the Bayesian geostatistical ensemble model was fited to over 6,000 data points from susceptibility tests that exposed An.…”

“…For the current study we used the model output for mortality after deltamethrin exposure in a standard susceptibility test. We selected deltamethrin resistance because this pyrethroid has the largest volume of susceptibility test data available, and the deltamethrin resistance outputs had the narrowest credible intervals (6). There are, however, strong associations among the patterns of resistance to all four pyrethroids (α-cypermethrin, deltamethrin, permethrin, and λ-cyhalothrin) (19).…”

“…For this reason, the Global Plan for IRM places particular emphasis on prolonging the effectiveness of pyrethroids in vector control. All currently recommended insecticidetreated net formulations use pyrethroids, but dramatic increases in pyrethroid resistance in the major African malaria vectors have occurred from 2005 to 2017 (4,6). Fortunately, three partner compounds have recently been introduced to net formulations.…”