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The Public Health Dynamics Laboratory at the University of Pittsburgh is on the vanguard of public health research and computational modeling. The following programs represent the first major Pitt projects to take advantage of this new intersection of disciplines.

University of Pittsburgh MIDAS Center of Excellence (NIGMS). The Modeling of Infectious Disease Agent Study was initiated by NIGMS to investigate novel computational and mathematical models of existing and emerging infectious diseases. In 2009, the University of Pittsburgh was designated a MIDAS National Center of Excellence, leading a collaborative network of scientists in the development and the use of computational models that will prepare the nation to respond to outbreaks of infectious diseases, such as the H1N1 swine flu. MIDAS's research mission includes the development of computational tools for the analysis of the dynamics of emergent diseases and for the predictive evaluation of the effectiveness of proposed intervention strategies.

Vaccine Modeling Initiative (Gates Foundation). The Vaccine Modeling Initiative is a research partnership among infectious disease modeling teams at the University of Pittsburgh, The Pennsylvania State University and Imperial College London, headquartered at the Graduate School of Public Health. The project focuses on the evaluation of new vaccine technologies for influenza, measles and dengue, a mosquito-borne infection, diseases that affect millions of people globally. Project investigators use computational models to assess how differing vaccine strategies impact the spread of disease, essentially creating maps of disease and resultant treatment with vaccines. The goal is to guide public health experts across the globe in making decisions about vaccine strategies that have the greatest likelihood to succeed.

The Public Health Adaptive Systems Studies (PHASYS) is one of nine Preparedness and Emergency Response Research Centers funded through a five-year grant from the Centers for Disease Control and Prevention’s Office of Public Health Preparedness and Response. Located in the University of Pittsburgh Graduate School of Public Health (GSPH) Center for Public Health Practice, PHASYS draws faculty from GSPH, the Graduate School of Public and International Affairs, Pitt’s School of Medicine, the National Institute of Health’s Modeling Infectious Disease Agent Study (MIDAS), Johns Hopkins School of Medicine, and personnel from the Brookings Institution and the Health Officers Association of California. A central assumption within PHASYS is that the public health system must adapt from its routine functioning in order to be effective in an emergency. The research focus takes two parallel approaches to understanding this adaptive response: (1) original research on criteria and metrics for public health systems and (2) agent-based systems modeling. Utilizing an infectious disease outbreak as its initial focus, the research will later progress to exploring an all hazards approach.

Fogarty Training in Thailand (FIC/NIH). The Fogarty training grant seeks to strengthen the epidemiologic research capacity for planning and response to emerging influenza outbreaks in Thailand. The detection of human cases of avian influenza in 2004 initiated concern both in Thailand and internationally that a new pandemic of influenza was about to begin and that there is a need to expand the number of scientists in Thailand with training in infectious disease epidemiology. The Fogarty training focuses on methodologies that provide the most information to decision makers during an incipient outbreak. Computational simulations of the spread of a novel variant of influenza in the Thai population, should one emerge, provide an invaluable tool for conducting "epidemiology in silicon" to evaluate control measures such as the use of vaccines, antivirals, and quarantine before an actual event.

Social Mixing and Respiratory Transmission (SMART) Schools. The Study Social Mixing and Respiratory Transmission Schools study was initiated by the US Centers for Disease Control and Prevention. The project seeks to measure child-child contact rates in Pittsburgh schools. It also aims to correlate Influenza-Like Illness with stay-at-home behavior.

Predict the Influenza Season and DARPA (Defense Advanced Research Projects Agency) Forecasting Chikungunya Challenge. Epidemiological forecasting is critically needed for decision-making by public health officials, commercial and non-commercial institutions, and the general public. Developing the Theory and Practice of Epidemiological forecasting (the DELPHI group) focuses on developing the technological capability of epi-forecasting, and its role in decision making, both public and private. Please visit the DELPHI page for more information.

The Pediatric Acute Liver Failure (PALF) Study has developed a discrete event simulation model that represents the entire US organ allocation system, with a complex algorithm for determining the progression of disease.

The Operations Research Collaboration for Alcohol Abuse and AIDS (ORCAA) is a collaboration with New York University. The purpose of ORCCA is to develop an Implementation Science Resource Core to support the research efforts of several CHAART consortia, building upon existing infrastructure within these consortia. That includes incorporating a complex, physiologically-based model of HIV progression into an agent-based model.

The Hurricane Sandy Research Grant is one of 44 grants from the Department of Health and Human Services (HHS) Office of the Assistant Secretary for Preparedness and Response (ASPR), the award provides a framework for conducting scientific research before, during, and after a disaster. The research helps us to better understand how to build more resilient communities and improve our preparedness, response, and recovery efforts. To minimize post-disaster deficits in access to primary area services, the University of Pittsburgh grant developed HAZEL. HAZEL (HAZard-area primary CarE Locator) is a modeling tool that gives New York health officials a dynamic modeling tool to prepare for, monitor, and respond to the access deficit for populations in need of primary care during a post-disaster recovery.



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