Biostatistics seminar series

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Full description:

This talk explores the multifaceted nature of infectious disease modeling, emphasizing the need to integrate disease dynamics, environmental factors, and social determinants of health to better understand and address the global challenges of infectious disease transmission and control. We begin by examining a within-host joint model of longitudinal and survival data for Leishmania infection, incorporating key drivers such as pathogen load, antibody levels, disease status, and some regulatory and inflammatory responses of the immune system. This model captures individual trajectories of disease progression and identifies which responses are associated with a higher risk of death. While this model provides interesting and important results, modeling the intricacies of the immune response presents numerous challenges. A critical gap remains in understanding how within-host disease progression interacts with population-level transmission dynamics. The talk is followed by a discussion on climate-driven infectious disease modeling, using Malaria transmission as a case study. We analyzed site-specific and age-specific responses to climatic factors in Kenya, uncovering patterns between local precipitation and temperature with malaria cases via simple mixed-effects models. Our findings highlight shifts in age-specific susceptibilities, with older subjects exhibiting higher burdens, particularly after periods of high precipitation. To conclude, we introduce an integrative approach that holds the potential for the integration of within-host immunological processes, between-host dynamics, environmental influences, and health equity considerations. The framework offers a deeper understanding of infectious disease dynamics across diverse regions and populations, providing actionable insights to improve public health interventions globally.