MOVE | Modelling to Optimize Vector Elimination: Destabilising mosquito populations

Summary
Control of vector-borne diseases from Chagas to Malaria to Dengue largely relies on reducing or eliminating the arthropod vector populations. These public health initiatives routinely lead to at least initial declines in vector populations. The challenge is that as populations decline, unexpected evolutionary (such as insecticide resistance) and ecological changes (such as population fragmentation and altered density-dependence) can occur that might facilitate or undermine control efforts. However, the relative importance of these ecological intra- and inter-specific processes in regulating vector populations is almost unknown, which hinders the prediction of vector population dynamics and how different interventions might be most effectively deployed to sustainably suppress vectors. Although vector surveillance has generated extensive high-resolution time series datasets to assess the factors that underpin population persistence and regulation, the cutting-edge analytical tools required to overcome the complexity of these data have been mostly developed by ecologists and have rarely been applied in medical entomology. Filling both these knowledge and methodological gaps will require closer integration of public health science, medical entomology and ecology that I intend to deliver through this proposal. As a quantitative ecologist, I will work closely with medical entomologists and public health scientists, to develop and apply sophisticated state-space models to longitudinal vector surveillance data from five malaria endemic countries. I will determine how interventions impact vector: 1) population regulation, 2) metapopulation connectivity and persistence, and 3) community composition. This unprecedented demographic dissection of vector populations will simultaneously challenge ecological theory and explore how to harness intra- and inter-specific processes in vector populations to accelerate 'end-game' strategies that move from vector control to elimination.
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More information & hyperlinks
Web resources: https://cordis.europa.eu/project/id/852957
Start date: 01-02-2020
End date: 30-04-2026
Total budget - Public funding: 1 259 763,00 Euro - 1 259 763,00 Euro
Cordis data

Original description

Control of vector-borne diseases from Chagas to Malaria to Dengue largely relies on reducing or eliminating the arthropod vector populations. These public health initiatives routinely lead to at least initial declines in vector populations. The challenge is that as populations decline, unexpected evolutionary (such as insecticide resistance) and ecological changes (such as population fragmentation and altered density-dependence) can occur that might facilitate or undermine control efforts. However, the relative importance of these ecological intra- and inter-specific processes in regulating vector populations is almost unknown, which hinders the prediction of vector population dynamics and how different interventions might be most effectively deployed to sustainably suppress vectors. Although vector surveillance has generated extensive high-resolution time series datasets to assess the factors that underpin population persistence and regulation, the cutting-edge analytical tools required to overcome the complexity of these data have been mostly developed by ecologists and have rarely been applied in medical entomology. Filling both these knowledge and methodological gaps will require closer integration of public health science, medical entomology and ecology that I intend to deliver through this proposal. As a quantitative ecologist, I will work closely with medical entomologists and public health scientists, to develop and apply sophisticated state-space models to longitudinal vector surveillance data from five malaria endemic countries. I will determine how interventions impact vector: 1) population regulation, 2) metapopulation connectivity and persistence, and 3) community composition. This unprecedented demographic dissection of vector populations will simultaneously challenge ecological theory and explore how to harness intra- and inter-specific processes in vector populations to accelerate 'end-game' strategies that move from vector control to elimination.

Status

SIGNED

Call topic

ERC-2019-STG

Update Date

27-04-2024
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Horizon 2020
H2020-EU.1. EXCELLENT SCIENCE
H2020-EU.1.1. EXCELLENT SCIENCE - European Research Council (ERC)
ERC-2019
ERC-2019-STG