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Computers can predict effects of HIV policies
Date:7/27/2012

PROVIDENCE, R.I. [Brown University] Policymakers struggling to stop the spread of HIV grapple with "what if" questions on the scale of millions of people and decades of time. They need a way to predict the impact of many potential interventions, alone or in combination. In two papers to be presented at the 2012 International AIDS Society Conference in Washington, D.C., Brandon Marshall, assistant professor of epidemiology at Brown University, will unveil a computer program calibrated to model accurately the spread of HIV in New York City over a decade and to make specific predictions about the future of the epidemic under various intervention scenarios.

"It reflects what's seen in the real world," said Marshall. "What we're trying to do is identify the ideal combination of interventions to reduce HIV most dramatically in injection drug users."

In an analysis that he'll present at 11 a.m. in Session Room 6 on Friday, July 27, Marshall projects that with no change in New York City's current programs, the infection rate among injection drug users will be 2.1 per 1,000 in 2040. Expanding HIV testing would drop the rate only 12 percent to 1.9 per 1,000; increasing drug treatment would reduce the rate 26 percent to 1.6 per 1,000; providing earlier delivery of antiretroviral therapy and better adherence would drop the rate 45 percent to 1.2 per 1,000; and expanding needle exchange programs would reduce the rate 34 percent to 1.4 per 1,000. Most importantly, doing all four of those things would cut the rate by more than 60 percent, to 0.8 per 1,000.

"These results show that a comprehensive set of proven interventions must be scaled up immediately if we are to substantially reduce the spread of HIV among drug users," Marshall said.

Virtual reality, real choices

The model is unique in that it creates a virtual reality of 150,000 "agents," a programming term for simulated individuals, who in the case of the model, e
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Contact: David Orenstein
david_orenstein@brown.edu
401-863-1862
Brown University
Source:Eurekalert  

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Computers can predict effects of HIV policies
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