Dr Catherine Moyes
Associate Professor and Research Group Leader
My main interest is in surveillance for infectious disease control. My group has developed methods to use data captured from the internet in geospatial models that predict disease risk. We have used this approach to generate updating maps of dengue, chikungunya and melioidosis risk for the Atlas of Baseline Risk Assessment for Infectious Diseases.
I also lead the Malaria Atlas Project’s work on insecticide resistance in malaria vectors. 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. Under the umbrella of the Malaria Atlas Project, 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.
malariaAtlas: an R interface to global malariometric data hosted by the Malaria Atlas Project.
Pfeffer DA. et al, (2018), Malaria journal, 17
Human candidate gene polymorphisms and risk of severe malaria in children in Kilifi, Kenya: a case-control association study.
Ndila CM. et al, (2018), The Lancet. Haematology, 5, e333 - e345
Entomological Surveillance as a Cornerstone of Malaria Elimination: A Critical Appraisal
Killeen GF. et al, (2018), Towards Malaria Elimination, 403 - 429
Associated patterns of insecticide resistance in field populations of malaria vectors across Africa.
Hancock PA. et al, (2018), Proceedings of the National Academy of Sciences of the United States of America, 115, 5938 - 5943
Existing and potential infection risk zones of yellow fever worldwide: a modelling analysis.
Shearer FM. et al, (2018), The Lancet. Global health, 6, e270 - e278