Pitt’s Graduate School of Public Health Announces Program in Computational Public Health
School funds several projects to improve understanding of public health by using predictive models
PITTSBURGH, April 15, 2008 — To address and solve problems such as obesity, poor food choices and inadequate use of vaccination, the University of Pittsburgh Graduate School of Public Health (GSPH) has created a program in computational and systems modeling that provides start-up funding to investigators who are applying simulations and predictive models to public health.
“Quantitative tools have become increasingly important to understanding and addressing global health problems,” said Donald Burke, M.D., dean, GSPH and associate vice chancellor for global health, University of Pittsburgh. “By using informatics and computational modeling and simulation, we can understand more about current public health challenges and determine the best strategies to prevent disease and improve human health.”
Funding for the program is designed to stimulate collaborations that can be parlayed into more substantial funding from external sources. A total of five projects were funded with grants of $20,000 each. They will explore:
- Effect of aflatoxin regulations on global risks for liver cancer and world food trade – Aflatoxin, produced by a food-borne fungus, is the most potent natural liver carcinogen to humans. It is found in corn, peanuts, pine nuts, pistachios and almonds. While many nations worldwide have developed regulations to limit its levels in foods, these regulations can be excessively prohibitive, leading to massive export market losses that could debilitate less developed countries. To guide public health decision-makers in balancing the tradeoff between human health and food market losses incurred from limiting aflatoxin, Felicia Wu, Ph.D., assistant professor, Department of Environmental and Occupational Health, is developing a mathematical programming model to estimate the economic and health impacts of different global aflatoxin standards. This model will help guide policymakers as they develop global food quality regulations.
- Environmental influences on obesity – Using a simulation model, Ravi K. Sharma, Ph.D., assistant professor, Department of Behavioral and Community Health Sciences, will predict what could happen to obesity rates over time if social and environmental characteristics of a community are changed. Dr. Sharma and colleagues will address how changes in a community’s environment combine with personal risk factors to influence obesity.
- Commitment, cooperation and dilemma in food choices – Healthy eating has a powerful effect in preventing disease, but what we eat often is a “social choice” that partly depends on those around us. To understand more about how people make food choices when they are alone and with others, Christopher Keane, Ph.D., assistant professor, Department of Behavioral and Community Health Sciences, has developed a game based on food vouchers to examine how people bargain with themselves and others, and how unhealthy food choices spread through social networks.
- Using a lottery-choice decision game to model vaccine behavior – To explore why people may refuse vaccination for themselves or their children, Steven Albert, Ph.D., professor, Department of Behavioral and Community Health Sciences, has developed a lottery-choice game to determine if those who refuse vaccination are more adverse to risk generally compared to those who accept vaccination. Childhood vaccination, hepatitis B vaccination in mid-life and influenza vaccination in the elderly will be examined.
- Long-term care system in Pennsylvania using an ecological approach – What reforms are needed to improve health and the long-term care system infrastructure for the elderly? To answer this question and provide policymakers, researchers and institutional managers with a fuller understanding of county and regional long-term care market dynamics, Michael Lin, Ph.D., assistant professor, Department of Health Policy and Management, and colleagues from GSPH and Pitt’s College of Arts and Sciences are projecting the growth and stability of formal long-term care organizations throughout Pennsylvania by using area-specific information and simulation analyses.
The Computational and Systems Models in Public Health pilot grant program provides funding for a one-year period. For more information on GSPH, visit http://www.publichealth.pitt.edu/.