Dr Penny Hancock
Senior Postdoctoral Researcher in Geospatial Modelling
I am interested in the ecology and evolution of mosquito-borne disease systems, with applications to mosquito control techniques. As part of the Malaria Atlas Project (MAP) team I am performing spatial analysis of the dynamics and spread of insecticide resistance in Anopheles mosquito vectors of malaria across Africa. This research interprets spatial datasets of insecticide resistance observations (representing phenotypic and genetic information) using a combination of geostatistical and machine learning approaches. The models are informed by a suite of environmental predictor variables.
I also research novel mosquito control strategies involving field releases of Wolbachia bacteria, aimed at Aedes mosquito species that vector the dengue and Zika viruses. I am developing mechanistic models of the spread of Wolbachia infections through field mosquito populations, focussing on representing patterns of spatial and demographic heterogeneity that occur in nature. Animations showing simulated patterns of spatial spread of Wolbachia following releases can be seen here: https://appliedecologistsblog.com/2019/07/10/the-amorphous-heterogeneous-spatial-spread-of-wolbachia/
Global estimation of anti-malarial drug effectiveness for the treatment of uncomplicated Plasmodium falciparum malaria 1991-2019.
Rathmes G. et al, (2020), Malaria journal, 19
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
Mapping Geospatial Processes Affecting the Environmental Fate of Agricultural Pesticides in Africa.
Hendriks CMJ. et al, (2019), International journal of environmental research and public health, 16
Analysis-ready datasets for insecticide resistance phenotype and genotype frequency in African malaria vectors.
Moyes CL. et al, (2019), Scientific data, 6