Integrating data from across insecticide susceptibility bioassay types using a mechanistic model incorporating mosquito genetic variation and behaviour
Authors: Denz Adrian , Kont Mara D. , Sanou Antoine , Churcher Thomas S. , Lambert Ben 
Published: March 2024

Malaria kills roughly 500,000 people each year, and our most effective intervention against the disease is insecticide treated nets (ITNs) which kill mosquitoes. Mosquito resistance to the most important class of insecticidal compounds, pyrethroids, has increased dramatically over the past few decades, but it remains difficult to assess the impact of resistance on public health. Past work has shown how mortality data from cheap-to-conduct discriminating-dose susceptibility bioassays can be used to predict mosquito mortality in more expensive and more true-to-life experimental hut trials. We developed a new predictive approach for modelling these data which incorporates data from intensity-dose susceptibility bioassays, which is a WHO-recommended test increasingly used in malarial regions that outputs a more detailed measure of pyrethroid resistance. This new mechanistic model explicitly estimates epidemiologically important quantities that describe the interaction of mosquitoes with the insecticide. The model accounts for variation in insecticide tolerance in the mosquito population, for example, due to genetic variability. The utility of the model is illustrated by fitting it to data from a systematic review of experimental hut trials that evaluated the efficacy of pyrethroid-only ITNs. This work represents a first step towards using intensity-dose susceptibility bioassay data to predict the epidemiological benefit of ITNs and determine the effects of resistance to pyrethroids on public health.

Author summary

Bednets laden with insecticides that kill mosquitoes have been responsible for substantial reductions in the burden of malaria in the last few decades. Mosquito resistance to insecticides threatens to halt further progress and potentially erode these gains. It is important to be able to gauge changes in insecticide resistance over time and how these changes affect the effectiveness of bednets. Important tools for quantifying these changes include intensity-dose susceptibility bioassays, which expose mosquitoes to a range of insecticide doses and measure their mortality, and experimental hut trials, which are more expensive and aim to mimic how mosquitoes interact with insecticides on bednets in the field. Here, we develop a mathematical model which includes mechanistic detail about how mosquitoes interact with insecticides in each of these types of experiments. We show how our models allow us to make accurate predictions of mosquito mortality in hut trials using data from intensity-dose susceptibility bioassays which are more sensitive than the traditional disciminating dose bioassays while being less expensive than experimental hut trials. Our models provide a more granular understanding of this important class of experiments and could be embedded into larger transmission dynamics models of malaria to predict the public health impact of changes in insecticide resistance measured by surveillance programmes.