A spatial map of malaria transmission across Africa

Project information

Infectious disease mapping provides a powerful synthesis of evidence in an effective, visually condensed form. Our research focuses on the development of new mapping approaches, and how these can be used to the evaluate Plasmodium falciparum transmission trends, and trends in insecticide resistance in mosquito vector populations, in high burden Sub-Saharan Africa.

Our methodological research centres on the development and integration of new spatial mapping techniques that draw from the fields of probability theory and machine learning. Specifically, we focus on kernel methods, and develop efficient and flexible parameterisations that can leverage information from satellite imagery (such as vegetation density) and capture residual variation in space and time.

We apply novel spatial methods to map Plasmodium falciparum malaria transmission through time and investigate epidemiological aspects such as the impact of housing on transmission, the impact of environmental and socio-economic factors on mosquito net efficacy, and an evaluation of the landscape of residual transmission after mosquito net scale up. We also investigate spatiotemporal trends in characteristics of the malaria vector population. We have developed Africa-wide maps demonstrating the geographic spread of resistance to pyrethroid and DDT insecticides in mosquitoes from the Anopheles gambiae complex. We use joint modelling frameworks to link trends in insecticide resistance phenotypes to underlying genetic mechanisms of resistance in Anopheles species.

Recent publications

Hancock, P.A., Lynd, A., Wiebe, A., Devine, M., Essandoh, J., Wat’senga, F., Manzambi, E.Z., Agossa, F., Donnelly, M.J., Weetman, D., and Moyes, C.L. Modelling spatiotemporal trends in the frequency of genetic mutations conferring insecticide target-site resistance in African mosquito malaria vector species. BMC Biol 20, 46 (2022). 

Routledge I, Unwin HJT, Bhatt S, 2021, Inference of malaria reproduction numbers in three elimination settings by combining temporal data and distance metrics, SCIENTIFIC REPORTS, Vol: 11, ISSN: 2045-2322

Bertozzi-Villa A, Bever CA, Koenker H, Weiss DJ, Vargas-Ruiz C, Nandi AK, Gibson HS, Harris J, Battle KE, Rumisha SF, Keddie S, Amratia P, Arambepola R, Cameron E, Chestnutt EG, Collins EL, Millar J, Mishra S, Rozier J, Symons T, Twohig KA, Hollingsworth TD, Gething PW, Bhatt Set al., 2021, Maps and metrics of insecticide-treated net access, use, and nets-per-capita in Africa from 2000-2020, NATURE COMMUNICATIONS, Vol: 12, ISSN: 2041-1723

Hancock, P. A., Hendriks, C. J. M., Tangena, J. A., Gibson, H., Hemingway, J., Coleman, M., Gething, P. W., Cameron, E., Bhatt, S. & Moyes, C. L. 2020. Mapping trends in insecticide resistance phenotypes in African malaria vectors. PLoS Biol 18(6)

Bhatt S, Cameron E, Flaxman SR, Weiss DJ, Smith DL, Gething PW., 2017, Improved prediction accuracy for disease risk mapping using Gaussian Process stacked generalisation.  J R Soc Interface, Sep;14(134):20170520