Improving the accuracy of entomological measures of risk for vector borne diseases

Lead Research Organisation: Imperial College London
Department Name: School of Public Health

Abstract

Mosquito-borne diseases are a significant global health problem. Despite large declines, malaria remains a leading cause of mortality worldwide (730,500 deaths in 2015), and, dengue-associated mortality is a growing concern, increasing 48.7% from 2005-2015. Interventions to reduce vector-human interactions have been key to the observed decline in malaria prevalence and incidence. However, randomised controlled trials of vector-control methods for Aedes-transmitted diseases have shown variable efficacy; both ITNs and indoor residual spraying had no significant impact on dengue risk. And insecticide resistance in anopheline and Aedes mosquitoes has been identified in numerous settings. Evaluating the efficacy of interventions that prevent vector-human interactions is therefore a public health priority.

The entomological inoculation rate (EIR), or average number of infectious bites per person per year, is primarily dependent on the vector age, extrinsic incubation period (EIP) of the virus or parasite and vector biting behaviour. This project will adopt a modelling approach in order to identifying the impacts of environmental change and intervention programs on the EIR and the mechanisms through which EIR changes.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
NE/P012345/1 30/09/2017 29/09/2023
2131872 Studentship NE/P012345/1 30/09/2018 30/03/2022 Isaac James Stopard
 
Description The extrinsic incubation period (EIP) is an important determinant of malaria transmission intensity. The EIP cannot be measured in individual mosquitoes directly but must be inferred at the population scale. Here we develop a mathematical model that improves the existing methods to do this. Further work is required to understand how this will affect our understanding of malaria transmission and how to prevent it, but two key questions have arisen from the work: (1) how does variability in the EIP affect malaria transmission and (2) does parasite load affect the EIP.
Exploitation Route This model results of this model may be applied by both mathematical epidemiologists to predict malaria transmission and medical entomologists to understand malaria parasite development.
Sectors Environment,Pharmaceuticals and Medical Biotechnology