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.
A new malaria vector in Africa: Predicting the expansion range of Anopheles stephensi and identifying the urban populations at risk
Sinka M. et al, (2020), Proceedings of the National Academy of Sciences, 202003976 - 202003976
Evaluating insecticide resistance across African districts to aid malaria control decisions
Moyes CL. et al, (2020), Proceedings of the National Academy of Sciences, 202006781 - 202006781
Modelling geospatial distributions of the triatomine vectors of Trypanosoma cruzi in Latin America.
Bender A. et al, (2020), PLoS neglected tropical diseases, 14
Mapping trends in insecticide resistance phenotypes in African malaria vectors
Hancock PA. et al, (2020), PLOS Biology, 18, e3000633 - e3000633
Vector bionomics and vectorial capacity as emergent properties of mosquito behaviors and ecology.
Wu SL. et al, (2020), PLoS computational biology, 16