Predictive Modeling: Managing Tropical Diseases in Africa
The School of Human Evolution and Social Change will host a guest lecture by epidemiologist Edwin Michael, who will discuss how new methods of data analysis and modeling can help health programs beat tropical diseases.
There is increasing recognition that large-scale disease control or elimination issues belong to a decision and policy domain marked by significant uncertainty, complexity and heterogeneity. New “smart” decision tools able to deal with this complexity are required for effective management of these programs.
Such tools require the integration of deep, domain knowledge of disease transmission models and complex, parasite extinction dynamics. They connect to data from multiple sources, and reliably assimilate information from data into models in order to capture local dynamics and incorporate the effects of heterogeneous transmission/extinction dynamics across endemic settings.
Michael will describe the development of a platform that couples geolocated data discovery, assembly and transformation to serve as inputs into a Bayesian data assimilation modeling framework. This allows simulations of the transmission dynamics and control of the major vector-borne disease, lymphatic filariasis (LF), across a major endemic spatial domain, focusing on continental Africa. He will also highlight how such a platform supports learning of site-specific models of LF transmission and how it may be used to answer key outstanding policy questions for the program, eliminating this highly debilitating disease from this important disease endemic continent.
Edwin Michael is an epidemiologist who studies the spread and control of infectious tropical diseases. The overriding objective of his research is to address the next generation of critical questions regarding the population ecology, epidemiology and control of neglected tropical and vector-borne diseases, which includes lymphatic filariasis and malaria. In his laboratory, he also studies the influence of global climate change on vector and environmentally mediated infectious disease transmission, as well as the epidemiology of chronic and infectious disease co-occurrence and morbidity in developing populations.