Title: Multi-Disciplinary, -Compartment, and -Scale Analyses and Models of Emerging Zoonoses with Application to Ebola
1. Department of Environmental Science, Policy and Management, UC Berkeley, CA, USA (wgetz at berkeley.edu) 2. School of Mathematical Sciences, University of KwaZulu-Natal, Durban 4000, South Africa 3. Numerus, Inc., 850 Iron Point Road, Suit 153, Folsom, CA 95630, USA 4. Department of Fish and Wildlife Conservation, Virginia Tech, Blacksburg, VA, USA 5. Spatial Epidemiology and Ecology Research Laboratory, Department of Geography, UF, Gainesville, FL, USA 6. Emerging Pathogens Institute, UF, Gainesville, FL, USA 7. Computer Science Department, Oberlin College, Oberlin, Ohio, OH 44074, USA
Preparedness and rational management of outbreaks of emerging infectious diseases requires models that include characterization of i) environmental and spatiotemporal of pathogen reservoir spaces, ii) stochastic transmission chains in spillover (animal-human transmission) and host (human-to-human transmission) epidemic spaces, ii.) immunological and behavioral diversity in humans hosts, iv) the impacts of treatments and interventions on the course of the epidemic, and v.) the socioeconomic milieu in which these interventions are implement. We are still far from this level of integration of the components needed to put together this level of analysis. Here we will review the status of several of these components and their current level of integration. We will then excogitate, in the context of Ebola, how we might move forward to more fully integrate these components to obtain more useful models.
Title: Modeling Social Pathways of Epidemics
Disease evolution, interventions to contain the disease, and behavioral responses to outbreaks and interventions, are interrelated through a complicated feedback process. Just like the disease, individuals' perceptions and their behavior continuously evolve based on their assessment of the outbreak which motivate self-guided behavioral adaptations. Some of these adaptations dynamically change the social contact network, which in turn affect opportunities for transmission and hence the spread of the disease. This research uses a realistic social contact network that captures the heterogeneity in demographics and interactions inherent in social contact networks. It will demonstrate the utility of dynamic modeling and a detailed interaction graph through simulation of the spread of Influenza on a large regional social network in the US.
Title: Ebola Outbreaks in Uganda: Same level of risks, difference in approaches
It is easy to praise and appreciate the efforts made in containing one of the most lethal viruses that strikes a population with everything low (low level of economic development, low level of health systems and services, low level of literacy, low level of responsiveness, low levels of communication, lowest per capita income). At the same time it is difficult to keep in mind what really makes the difference in response to major outbreaks of Ebola-type in these circumstances. In this talk, we share experiences of how Uganda, a country within the same economic limits as other Ebola-prone regions, responded to the past four Ebola outbreaks. Through this, we provoke our minds on possible modeling approaches that can render future spontaneous controls and limit mortality of the outbreaks.