Last Updated: 13/02/2025
Movement rates of African malaria vectors and their implications in models of vector control interventions
Objectives
This project will comprise field experiments, based on the fluorescent marking of emergent mosquitoes to estimate the key determinants of Anopheles movement rates (both while host-seeking and ovipositing) in real-world landscapes near Bagamoyo, Tanzania, and the impact of interventions upon them.
Mathematical models of mosquito dispersal will be developed, and parameterised with these field data, as well as with the results of previous small-scale semi-field experiments, field experiments in experimental huts, and large-scale field trials of SRs, and of OBTs. These models will be validated against a large field trial of OBTs in Rusinga, Kenya and a large field trial of SRs in Tanzania. The calibrated models will be linked to models of malaria transmission and disease and will thus contribute to predictions of the likely impacts of different strategies for field deployment of entomological interventions in heterogeneous environments, on mosquito population densities and on disease in humans.
Many interventions against mosquito vectors of disease are currently under development. These include new insecticidal compounds applied in established interventions like indoor residual spraying (IRS) and insecticide-treated mosquito nets (ITNs). Also under development are novel or un-established interventions such as spatial repellents (SR) and odour-baited mosquito traps (OBT). Each of these interventions has effects over larger areas than the immediate vicinity to which they are applied because mosquitoes move between aquatic breeding sites and vertebrate hosts to complete their life cycle. As a consequence, impacts on mosquito populations under natural conditions can be far greater than estimated from standard tests carried out at small-scale. These community/area/ or mass effects driven by mosquito movement mean that large-scale field-testing of vector control interventions raises both statistical and operational issues that have a spatial dimension, different from those of clinical trials of health interventions that only protect directly treated individuals, such as chemotherapy or chemoprophylaxis. To accelerate product development, registration and implementation and make interventions more cost-efficient, it is especially important to understand how a mosquito control intervention with specific performance criteria, as measured in small-scale experiments (such as mortality or repellency) will perform in the real world. This can be achieved by modelling relationships between small-scale and real-world performance indicators, to enable effects on transmission and public health outcomes to be extrapolated from small high-throughput experiments without the need to repeat larger scale field trials. However, uncertainties in our understanding of mosquito dispersal limit the potential of predictive modelling of vector control interventions and little is known about whether/how best to target such interventions in real-world environments that are heterogeneous in the spatial distributions of mosquito breeding-sites, of humans and other hosts, and of existing interventions.
Jan 2016 — Dec 2018
$445,049
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