To help the nation — and the world — understand and prepare for contagious outbreaks, the National Institutes of Health's Models of Infectious Disease Agent Study (MIDAS) adds new research expertise to increase its capacity to simulate disease spread, evaluate different intervention strategies and help inform public health officials and policymakers.
In recent years, a number of new diseases have emerged and infected people around the world. In 2003, a respiratory illness called SARS spread quickly from China to 37 other countries. A few years later, the United States experienced a major spike in cases of MRSA, the drug-resistant "superbug" version of Staphylococcus aureus. And just this summer, an H1N1 strain of flu caused international concern as it traveled to nearly all the continents.
Some of the best available tools for studying infectious disease dynamics and interventions are computational models. They incorporate basic information about a disease and the affected communities to simulate the spread of an infectious agent under any number of conditions. The results can help scientists, health officials and policymakers develop and implement control measures both before and during an outbreak.
"Models can't tell us what will happen, but they do allow us to explore a range of possibilities for disease containment," said Jeremy M. Berg, PhD, director of the National Institute of General Medical Sciences, the NIH component supporting MIDAS. "Since its launch in 2004, the MIDAS research network has been at the forefront of infectious disease modeling efforts, and we hope it continues to serve an important role in preparing for possible outbreaks."
The new MIDAS grants, which include two Centers of Excellence and three research projects, will receive an estimated total of up to $40 million over the next five years.
The Centers of Excellence will carry out research on modeling, develop outreach programs in public health policy and establish training programs worldwide.
The Center for Communicable Disease Dynamics will be led by Marc Lipsitch, DPhil, of the Harvard School of Public Health in Boston. Its core research program focuses on modeling drug resistance, seasonal infectious diseases and the allocation of interventions. Its team will work closely with health officials around the world to integrate public health knowledge into the models and vice versa.
The Pittsburgh MIDAS Center of Excellence will be led by Donald Burke, MD, of the University of Pittsburgh in Pennsylvania. This group will study fundamental questions about the behavioral, environmental and evolutionary factors underlying infectious disease epidemics and use this information to develop real-time models for particular localities, such as cities or states. The three newly funded research groups will develop computational models of how infectious diseases develop, spread and can be contained or mitigated through public health interventions.
Diane Lauderdale, PhD, of the University of Chicago and Charles Macal, Ph.D., of Argonne National Laboratory in Illinois will create a dynamic model of MRSA in Chicago to examine factors contributing to its spread and to identify interventions with the greatest potential to curtail new infections.
Elizabeth Halloran, DSc, MD, and Ira Longini, PhD, both of the University of Washington and the Fred Hutchinson Cancer Research Center in Seattle, will develop models to assess the effectiveness and optimal distribution of a variety of control measures, including vaccination, school closures and other social distancing strategies.
Alison Galvani, PhD, of the School of Public Health Yale University in New Haven, Conn., and Lauren Ancel Meyers, PhD, of the University of Texas at Austin will develop new models that integrate individuals' perceptions and behaviors regarding flu and will identify intervention strategies that are likely to achieve high levels of adherence and minimize influenza-related disease and mortality.
In addition to these projects, MIDAS scientists have already published preliminary findings on the origin, infectiousness and likely spread of the 2009 H1N1 virus. This research builds on the MIDAS program's existing focus on modeling pandemic flu.