Spatio-temporal agent-based modelling of malaria
Camelia R Walker1, Md Nurul Anwar2, Leandra Bräuninger3
1School of Mathematics and Statistics, The University of Melbourne, Parkville, Australia; Melbourne School of Population and Global Health, The University of Melbourne, Parkville, Australia.
Abstract:
Plasmodium falciparum is responsible for the majority of malaria morbidity and mortality each year. Malaria transmission rates vary by location and time of year due to climate and environmental conditions. We show the impact of these factors by developing a stochastic spatiotemporal agent-based malaria model that captures the impact of spatially distributed interventions on malaria transmission. Our model uses spatiotemporal estimates of mosquito climatic suitability and household location data to model the interaction between human and mosquito agents. We apply our model to investigate how strategies for distributing interventions to households in Vietnam impact the disease burden. Our study suggests that providing some level of protection to a wide range of households could reduce malaria prevalence more compared to providing a strong level of protection to a limited number of households.
