According to an article published on isgtw, Researchers at the University of Pittsburgh, together with the Pittsburgh Supercomputing Center (PSC), and the School of Computer Science at Carnegie Mellon University, Pennsylvania, US, have developed a new version of their agent-based modeling system for epidemic dynamics. The large-scale modeling program, known as FRED (Framework for Reconstructing Epidemiological Dynamics), enables researchers to investigate and understand the possible courses of future epidemics – and how they might control and alleviate them.

FRED is able to simulate the fine-grained actions of individuals in a given region, as they go about their daily lives and interact with other individuals in their households, neighborhoods, schools, and workplaces. These simulations combine US census data with other school and workplace databases to ensure a realistic representation of the US population. The numbers of households, people, children in schools, adults at work, and commuting distances are accurate to within a few percent over most US communities.

Researchers can introduce a virtual disease into societal models, and see how it transmits from person to person as they evaluate various interventions.“What are the possible effective vaccination programs, school closure policies, sick leave policies, or social distancing norms? These are the policy questions we are interested in,” says John Grefenstette, director of the Public Health Dynamics Laboratory at the School of Public Health at Pittsburgh.

“FRED currently supports a variety of epidemic research areas from how viruses evolve resistance, to human behaviors like which sub-populations decide to accept a vaccine if it is available or decide to stay home when sick, and how this behavior affects a population level epidemic. The models in FRED account for these variations as well as combinations of variations to predict a more accurately how an epidemic spreads,” explains Grefenstette.

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