Dr Catherine Moyes
Associate Professor and Research Group Leader
The Geospatial Modelling of Insect Vectors (GMIV) Group
My main interest is in surveillance for infectious disease control. My group is particularly interested in the insects that transmit disease-causing pathogens. By controlling these insects we can prevent infections in humans. My group models spatial heterogeneity in the geographical distributions of these species, in their capacity to transmit pathogens, and in their behaviour.
One major area of work is insecticide resistance in malaria vectors (mosquitoes). We are predicting spatiotemporal variation in resistance, and investigating associations with the potential drivers of selection, in order to look for associations between resistance and residual variation in malaria parasite prevalence. There are important overlaps in the Anopheles vectors of malaria and the Aedes vectors of dengue, chikungunya and Zika in terms of potential drivers of selection, behaviours and habitats so my goal is to consider resistance within both mosquito genera.
My work on vector-borne diseases extends to vector-borne zoonotic diseases and we have developed models that incorporate spatial distributions of vector species, reservoir species and vaccination coverage to define variation in the infection risk and incidence of yellow fever. This approach is currently being developed further to map Japanese encephalitis and American trypanosomiasis infection risks. I also lead a programme of work on spatial variation in Plasmodium knowlesi malaria. This malaria is found in certain monkey species in SE Asia and is regularly transmitted to humans. Knowledge of this disease lags behind the other human malarias and we are investigating the potential distribution of human infections, links with deforestation, and the impact of this disease in areas where the other human malarias are being eliminated.
This work is funded by Wellcome, NIAID and WHO-TDR.
Indoor residual spraying for malaria control in sub-Saharan Africa 1997 to 2017: an adjusted retrospective analysis
Tangena J-AA. et al, (2020), Malaria Journal, 19
Vector bionomics and vectorial capacity as emergent properties of mosquito behaviors and ecology.
Wu SL. et al, (2020), PLoS computational biology, 16
Mapping insecticide resistance in mosquitoes to aid malaria control
Moyes CL. et al, (2020)
Mapping Trends in Insecticide Resistance Phenotypes in African Malaria Vectors
Hancock PA. et al, (2020)
Analysis-ready datasets for insecticide resistance phenotype and genotype frequency in African malaria vectors
Moyes CL. et al, (2019), Scientific Data, 6