CANCELLED due to travel challenges.
Dr. Wilbert Van Panhuis
Assistant Professor of Epidemiology and Assistant Professor of Biomedical Informatics
“Population health informatics to counter epidemic threats: data integration and epidemic simulation”
Wednesday, January 18, 2017, at 2:00 PM
Hesburgh Library 107
ABSTRACT: Many datasets that could be used to counter epidemic threats are not used due to challenges in accessing and standardizing datasets, and in integrating data into novel analyses such as epidemic simulation. Panhuis’ research aims to improve the acquisition, standardization, and integration of information about epidemic threats. His team digitized and integrated a century of public health data for the United States to demonstrate that vaccines prevented 100 million disease cases and they used data on dengue fever from 8 countries in Southeast Asia to find that synchronous dengue transmission in this region coincided with elevated temperatures caused by El Niño. They are now improving the availability and usability of these, and other data for epidemic simulation by re-representing datasets in a machine-readable format. So far, they have re-represented information on Chikungunya virus epidemics and developed an agent-based simulation model of this disease for the entire population of Colombia, representing 45 million people in over 10 million households, schools, and workplaces. Using this simulation model, they found information about previous dengue outbreaks that can help target mosquito control against Chikungunya.
BIO: As an infectious disease epidemiologist with training in Medicine (Amsterdam) and Global Disease Epidemiology (Johns Hopkins), Panhuis’ research aims to improve the efficient use of information for public health action. He uses large-scale public health data to study the spatial spread of infectious diseases, using statistical and agent-based simulation models. His main focus is on VBD in Latin America and Southeast Asia, and on vaccine preventable diseases in the US and EU. Panhuis is the lead scientist of Project Tycho that provides open access to integrated global disease data, and is funded by the US NIH Big Data to Knowledge program to use Big Data approaches to improve access and integration of public health data for research and policy. He is co-PI of the NIH Models of Infectious Disease Agents Study, a co-investigator of the Gates Foundation Vaccine Modeling Initiative, and coordinator of an outreach program on data and computational epidemiology funded by the Benter Foundation in Pittsburgh and various industry sponsors.