Abstract: Emergent epidemics present major challenges to both global health and international politics. The 2014-2015 Ebola outbreak in West Africa alone took over ten thousand lives despite international aid nearing $5 billion from 70 countries. In retrospect, the declaration of the Public Health Emergency of International Concern came late, over 4 months after the first international transmission event. These apparent systemic failures likely reflect the fact that emergent epidemics are incredibly difficult to predict. The last decade saw Ebola outbreaks in the Democratic Republic of Congo in 2018, 2017, 2014 and 2012, as well as Uganda in 2007, but these previous outbreaks never exceeded 500 cases, compared to nearly 30,000 cases in the West African outbreak.
A key problem rests in the dynamics of emergent epidemics that are shaped in large part by societal and behavioral factors, which are all highly variable. In this talk, we will discuss behavioral factors using stories from local communities, contact tracing, genomic data, and reports from the most extensive social mobilization effort to date. These distinct data sources all influence how we use and interpret models from epidemiology, network theory and collective behavior. Slowly but surely, this synergy between scientific fields, data sources, and modeling approaches paves the way for a new approach to epidemiology.