【Time】14:00～15:00, June 08, 2016 (Wednesday)

【Venue】Room 510, Shunde Building

【Title】  Big data and population health informatics to counter epidemic threats

【Speaker】Willem van Panhuis, MD, PhD University of Pittsburgh

【Host】Dr. Xiaolei Xie

【Abstract】A large amount of health and climate data is available to counter epidemic threats such as dengue, chikungunya, and zika virus, but political and informatics constraints limit the effective use of this information. Our goal is to use Big Data methods such as agent-based simulation to improve data integration and analysis at the interface of climate and health. We digitized and integrated a century of public health data for the United States to demonstrate the impact of vaccine preventable diseases. In Southeast Asia, we analyzed up to 18 y of monthly surveillance reports on a total of 3.5 million reported dengue cases from 273 provinces in eight countries, covering a subcontinent of ∼107 km2. These data revealed patterns of synchronous dengue transmission across the entire region that coincided with elevated temperatures in 1997–1998 and the strongest El Niño episode of the century. Translating these findings into public health action through modern computational approaches for epidemic simulation and forecasting is constrained by lacking data standards and integration. This study demonstrates major opportunities to improve global population health through Big Data and population health informatics.

【Bio】Dr. Willem van Panhuis is an infectious disease epidemiologist with training in Medicine (Amsterdam) and Global Disease Epidemiology (Johns Hopkins). His research is in the fields of computational epidemiology and population health informatics aims to improve the efficient use of information for public health action. In particular, he uses large-scale public health data to study the spatial spread of infectious diseases, using statistical and agent-based simulation models. Currently, his main focus is on vector borne diseases (dengue and Chikungunya) in Latin America and Southeast Asia, and on vaccine preventable diseases in the US and EU (NEJM, PNAS, NIH Director’s Blog). He is the lead scientist of Project Tycho that provides open access to integrated global disease data (NEJM, New York Times, Wall Street Journal). In addition, He is funded by the US NIH Big Data to Knowledge (BD2K) program to use Big Data approaches to improve access and integration of public health data for research and policy. He is also a co-PI of the NIH funded Models of Infectious Disease Agents Study (MIDAS), a co-investigator of the Bill & Melinda Gates Foundation Vaccine Modeling Initiative (VMI), and he coordinates an outreach program on data and computational epidemiology funded by the Benter Foundation in Pittsburgh and various industry sponsors. He has published papers in The New England Journal of Medicine, The Lancet, and PNAS, which is number 19th out of 1000 similar PNAS papers for online impact; featured by the NIH Director’s Blog. 

All interested are welcome!