Communications of the ACM
Computers Can Predict Effects of HIV Policies
A visualization generated by an agent-based model of New York Citys HIV epidemic shows the risky interactions of unprotected sex or needle sharing among injection drug users (red), non-injection drug users (blue) and non-users (green).
Credit: Brandon Marshall/Brown University
Brown University researchers have developed software that can model the spread of HIV in New York City over several years to make specific predictions about the future of the epidemic under different intervention plans.
"What we’re trying to do is identify the ideal combination of interventions to reduce HIV most dramatically in injection drug users," says Brown University professor Brandon Marshall.
The program projects that with no change in New York City's current HIV programs, the infection rate among injection drug users will be 2.1 percent per 1,000 by 2040. However, strategies such as expanding HIV testing, increasing drug treatment, and providing earlier delivery of antiretroviral therapy could cut the rate by more than 60 percent, to 0.8 per 1,000.
The model creates a virtual reality of 150,000 agents who engage in drug use and sexual activity like real people. "With this model you can really look at the microconnections between people," Marshall says. The researchers calibrated the program until it reproduced the infection rates among injection drug users that were known to occur in New York City between 1992 and 2002.
From Brown University
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Abstracts Copyright © 2012 Information Inc., Bethesda, Maryland, USA
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