Imperial College London


Faculty of MedicineSchool of Public Health

Lecturer in Biostatistics / Epidemiology (Non Clinical)







St Marys Multiple BuildingsSt Mary's Campus





My main area of research involves developing mathematical models of mosquito populations that transmit human diseases, and investigating how they respond to disease control strategies. As part of my work with the Target Malaria project, I am modelling releases of genetically engineered transgenes into populations of Anopheles gambiae mosquitoes that transmit malaria. This work looks at the spread dynamics of the transgene in wild mosquito populations and how this can act to reduce malaria prevalence in humans. I am particularly interested in how natural mosquito ecology affects these dynamics. 

A related aspect of this research involves modelling the release and spread of Wolbachia bacteria in Aedes aegypti mosquito populations that transmit the dengue virus. I have used field cage experiments to develop models that take into account the impacts of density dependent demographic rates in Ae. aegypti on the spatial spread of Wolbachia throughout natural mosquito populations.

Since my doctoral training at the Australian National University I have continued researching spatial statistics, and have applied these techniques to develop maps describing the geographic distribution of insecticide resistance in African Anopheles malaria vectors. I have combined spatial statistics with machine learning approaches to quantify patterns of geographic spread of resistance to pyrethroids, the main insecticide used in long-lasting insecticidal bednets (LLINs). We are now adapting these models to investigate the spread of genetic variants that underlie pyrethroid resistance across different regions of Africa.

Selected Publications

Journal Articles

Hancock PA, Lynd A, Wiebe A, et al., 2022, Modelling spatiotemporal trends in the frequency of genetic mutations conferring insecticide target-site resistance in African mosquito malaria vector species, BMC Biology, Vol:20, ISSN:1741-7007, Pages:1-17

Adib K, Hancock PA, Rahimli A, et al., 2021, A participatory modelling approach for investigating the spread of COVID-19 in countries of the Eastern Mediterranean Region to support public health decision-making, Bmj Global Health, Vol:6, ISSN:2059-7908, Pages:1-7

Moyes CL, Athinya DK, Seethaler T, et al., 2020, Evaluating insecticide resistance across African districts to aid malaria control decisions, Proceedings of the National Academy of Sciences of the United States of America, Vol:117, ISSN:0027-8424, Pages:22042-22050

Hancock PA, Hendriks CJM, Tangena J-A, et al., 2020, Mapping trends in insecticide resistance phenotypes in African malaria vectors, PLOS Biology, Vol:18, ISSN:1544-9173, Pages:1-23

Hancock PA, Ritchie SA, Koenraadt CJM, et al., 2019, Predicting the spatial dynamics of <i>Wolbachia</i> infections in <i>Aedes aegypti</i> arbovirus vector populations in heterogeneous landscapes, Journal of Applied Ecology, Vol:56, ISSN:0021-8901, Pages:1674-1686

Hancock PA, Wiebe A, Gleave KA, et al., 2018, Associated patterns of insecticide resistance in field populations of malaria vectors across Africa, Proceedings of the National Academy of Sciences of the United States of America, Vol:115, ISSN:0027-8424, Pages:5938-5943

Hancock PA, White VL, Ritchie SA, et al., 2016, Predicting Wolbachia invasion dynamics in Aedes aegypti populations using models of density-dependent demographic traits, Bmc Biology, Vol:14

Hancock PA, White VL, Callahan AG, et al., 2016, Density-dependent population dynamics in Aedes aegypti slow the spread of wMel Wolbachia, Journal of Applied Ecology, Vol:53, ISSN:0021-8901, Pages:785-793

Hancock PA, Sinkins SP, Godfray HCJ, 2011, Strategies for introducing Wolbachia to reduce transmission of mosquito-borne diseases, PLOS Neglected Tropical Diseases, Vol:5, ISSN:1935-2727, Pages:1-10

Hancock PA, Sinkins SP, Godfray HCJ, 2011, Population dynamic models of the spread of Wolbachia, American Naturalist, Vol:177, ISSN:0003-0147, Pages:323-333

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