Incorporating Heterogeneity in Malaria Models: Methods, Examples, and Implications

Incorporating heterogeneity in malaria transmission models is essential to capturing the complexity of disease dynamics and accurately assessing the effectiveness of control strategies.

In this talk, I will explore how variations in spatial, temporal, demographic, and genetic factors can profoundly shape malaria spread and intervention outcomes. By examining models that address these diverse sources of heterogeneity, I aim to provide insights into how factors such as age-related immunity, genetic resistance, and seasonal patterns interact to influence transmission rates, disease severity, and population susceptibility.

Focusing on the implications of recent advancements—such as the introduction of malaria vaccines—I will discuss how these heterogeneous elements impact key parameters in disease modeling, including the basic reproduction number and patterns of infection across different demographic groups. This approach sheds light on the nuanced effects of interventions and the role of varying population structures, ultimately supporting more tailored and effective malaria control strategies.