Computer Simulation Aims to Predict Public Policy Effects on HIV/AIDS
“The spread of infectious diseases can be mitigated by properly targeted public policies that actually change people’s behaviors. HIV infections and their distribution are particularly susceptible to how they are addressed by public health officials, but it usually takes years to measure the actual results of the policies taken.
In order to help predict which set of policies is most effective, Brandon Marshall, assistant professor of epidemiology at Brown University, developed a computer simulation that involves thousands of virtual humans with unique behavioral patterns. At last week’s International AIDS Society Conference in Washington, D.C., Marshall presented findings from thousands of completed simulations of how New York City’s HIV/AIDS population becomes infected. By using historical data gathered in years past, Marshall was able to tune and calibrate the algorithms to correctly predict the past, and so hopefully the future…”