Abstract

Abstract Aedes aegypti (L.) is an invasive mosquito responsible for vectoring diseases such as dengue, Zika and Chikungunya. Dengue affects a large proportion of the global population, with the World Health Organization estimating that half the global population is at risk, with 390 million infections occurring each year. Control of mosquito vector populations over large geographical scales can be improved and made economically viable by computer models with potential to aid decision support. We introduce a method for estimating mosquito abundance (population size) over time in biocontrol programmes that involve the release of sterilised insects. We employ Bayesian state‐space modelling to provide insight into population trajectories using data from an application of incompatible insect technique (IIT) biological control, in Far North Queensland, Australia. The general approach could be adapted to other insect species. We demonstrate how the modelling approach can estimate trajectories of abundance over time as an unmarked–release–recapture analysis. Additionally, it provides a means for quantifying population suppression in IIT programmes (a statistic that can be challenging to estimate in practice) using counterfactuals. Modelling results show that estimated population trajectories exhibit similar temporal patterns to raw trapping rate data collected in the field, for example, the presence of peaks (and troughs) associated with the timing of rainfall events. Additional confidence in our model was demonstrated through a cross‐validation study where we left out each of the six landscapes from our dataset, fit the model using the remaining five regions and assessed its predictive skill. Modelled counterfactuals allowed us to estimate that population suppression in treated landscapes was 95%–99%. Synthesis and applications. Our model can provide valuable insights that can shape decision support systems in sterile insect technique and incompatible insect technique programmes operating over large geographical scales. The model helps determine how many sterile/incompatible insects should be released over time and how population control is progressing (via use of counterfactual scenarios). These outcomes are achieved because the model provides estimates of wild‐type populations over time, even when there has been no differentiation between sterile/incompatible and wild‐type insects caught in traps.

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