A novel age-structured mosquito model for assessing the mechanisms behind vector control success
Davis EL., Hollingsworth TD., Keeling MJ.
Abstract Background: Vector control is a vital tool utilised by malaria control and elimination programmes worldwide, and as such it is important that we can accurately quantify the expected public health impact of a range of vector control methods. There are very few previous models that consider vector control induced changes in the age-structure of the vector population and the resulting impact this will have on transmission.Methods: The steady-state solution of a novel age-structured deterministic compartmental model describing the mosquito gonotrophic cycle is analytically derived, with the age of each mosquito measured in the number of gonotrophic cycles (or successful blood meals) completed. From this model we derive analytical expressions for key transmission measures, such as the effective reproductive ratio under control, Rc, and investigate the impact of combinations of commonly used vector control methods on the age-structure of the vector population.Results: Our model output is an explicit solution that can be used to directly quantify key transmission statistics and investigate the age-structured impact of vector control. Application of this model confirms current knowledge thatadult-acting interventions, such as IRS or LLINs, can be highly effective at reducing transmission, due to the dual effects of repelling and killing mosquitoes. However, we demonstrate how larval measures can be implemented in addition to adult-acting measures to reduce Rc and mitigate the impact of waning insecticidal efficacy. We also find that mid-ranges of LLIN coverage see the largest effect of reduced net integrity on transmission.Conclusions: Whilst well-maintain adult-acting vector control measures are substantially more effective than larval-based interventions, incorporating larval control in existing LLIN or IRS programmes could substantially reduce transmission. This would most benefit areas with low coverage or poor maintenance of interventions.