Computer model predicts effects of policy on HIV infection rates

It can take years or decades to learn the effects of intervention strategies to reduce the spread of AIDS, but a Brown University researcher claims success with a predictive computer simulation in a presentation at the International AIDS Society Conference in Washington, D.C.

Brandon Marshall, assistant professor of epidemiology, presented a model to accurately predict the spread of HIV among injection drug users in New York City over a decade and to make specific predictions, according to a Brown announcement. It explored six scenarios: ramping up needle exchanges, enrolling more people in substance abuse treatment programs, increasing the rate of testing, starting people on medication earlier, a combination of these four intervention strategies and sticking with the current policies.

Starting with a decade of known infection rates (1992 to 2002), it created 150,000 individual hypothetical "agents" or individuals, each of which made plausible behavior decisions such as having protected sex one day but unprotected sex the next or starting drug treatment and then dropping out.

"With this model you can really look at the micro-connections between people. It reflects what's seen in the real world," Marshall said.

Processing the massive data set required a supercomputer cluster at Brown. Even so, it took 72 hours to run each scenario, reports Scientific American. And the researchers ran each one thousands of times to ensure accuracy.

Looking at the scenarios between now and 2040, Marshall found that the most effective single intervention was to start treatment earlier, which lowered new infections by 45 percent. Increasing by half the number of people tested for HIV reduced new infections by only about 12 percent; increasing drug treatment would reduce the rate 26 percent; and expanding needle exchange programs would reduce the rate 34 percent. Combining all four of the interventions would cut infections by 62 percent.

These interventions must be scaled up immediately to have substantial effect on the spread of HIV among intravenous drug users, said Marshall, who had expected the interventions to provide better results.

Going forward, he and his colleagues are exploring the cost-effectiveness of the interventions.

HIV data is among the government-collected health information made available to researchers, policy-makers and the public in May by the Department of Health and Human Services.

And a Kaiser Permanente health challenge seeks to increase the number of providers using its  toolkit of clinical best practices  for treating HIV-positive people.

Meanwhile, two studies from Kenya found weekly text messages helped HIV patients adhere to their medication regimen.

To learn more:
- read the Brown article
- here's the Scientific American article


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