Spatio-temporal agent-based modelling of malaria

TL;DR

This paper develops a stochastic spatiotemporal agent-based model to analyze how climate, environment, and intervention strategies affect malaria transmission and control in Vietnam.

Contribution

It introduces a novel agent-based model incorporating spatial and temporal factors to evaluate intervention impacts on malaria transmission.

Findings

Wider distribution of moderate protection reduces malaria prevalence more.

Spatially targeted interventions can be optimized based on environmental suitability.

Model demonstrates the importance of environmental factors in transmission dynamics.

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 shows that providing some level of protection to a wide range of households reduces malaria prevalence more compared to providing a strong level of protection to a limited number of households.