San Francisco Chronicle - Thursday, August 1, 2002
Sabin Russell, Chronicle Medical Writer

Computer modeling suggests that, while HIV will continue to tear up the lives of individuals, under certain conditions it may slowly ebb out of infected populations -- such as San Francisco's -- by failing to infect more people than it kills.

"The good news is that it is possible to eradicate it; the bad news is that it will take decades," said Sally Blower, a mathematician and medical researcher at UCLA.

The significance of the finding is that it lends mathematical support to the notion that treating large numbers of people in an infected population with antiviral drugs can change the course of an epidemic. "Treatment is prevention," Blower said. "It ought to be thought of as such."

While treatment has obvious benefits to an individual, Blower said her model showed that it also benefited the uninfected, by reducing their chances of eventually contracting the disease. It is an argument made by advocates of cheap AIDS drugs for Africa.

Blower said her findings contrasted with the bleak forecasts that came out of the Barcelona AIDS conference last month that at least 65 million would perish by 2020.

"I hope that she is right. Obviously, it would be terrific. But there are reasons for skepticism," said Elliot Marseille, of the Institute for Health Policy Studies in San Francisco. Marseille said that Blower's study assumed that treatment with antiviral drugs reduced transmission rates but that there was no proof that really happens.

"Current data suggest most transmission occurs shortly after infection, but most treatment begins later on," he said. "So it is not clear what impact treatment would have on reducing infection."

Blower's work is described in a paper published today in the British scientific monthly The Lancet Infectious Diseases. Her model is based on her studies of the gay population in San Francisco, where one in three is believed infected today with HIV, the virus that causes AIDS.

Blower and her colleagues poured thousands of scenarios into computers that perform one of the dark arts of mathematics known as "uncertainty analysis."

Each scenario presumed very high rates of antiviral drug treatment, different rates of risky sexual behavior within that population, and different rates of development of drug-resistant strains of the AIDS virus.

Out of the computer came three different probabilities that the AIDS epidemic in San Francisco would eventually die out:

-- The chances of this happening, within 50 to 100 years, was 85 percent if risky sexual behavior -- as measured by the number of unprotected sex acts -- was reduced by 25 percent.

-- If risky sexual behavior remained at constant levels, the probability of eradicating the epidemic was an even 50 percent.

-- Should riskier sex increase by 25 percent, the protective effects of antiviral treatment still give slim odds of eradication -- but only 13 percent.

These odds are based on the computer's estimate of how, under various circumstances, the population would reach a threshold where one person, on average, infects no more than one person in his or her lifetime. When this replication rate slips below 1, the epidemic begins to ebb. When it is above 1, the epidemic is growing.

"The important thing is to know in which direction you are going," Blower said.

Skeptics of Blower's assertions said she might also be vastly overestimating the amount of infected people in San Francisco who are actually taking antiviral drugs. Blower assumes between 50 and 90 percent of the affected population are taking the drugs.

But James G. Kahn, of the Institute for Health Policy Studies, said unpublished research suggested that 1 in 4 HIV-positive San Franciscans were actually getting the antiviral therapy.

Tom Coates, director of the UCSF AIDS Research Institute, said Blower's work was "interesting in theory, but all we have to go on is our experience. We've introduced antivirals, and infection rates have gone up."

Blower contends that this only proves the validity of her method. At a previous post at UCSF, Blower used the same model to forecast in 2000 that widespread use of antiviral drugs would trigger an increase in AIDS infections in San Francisco as gay men abandon their fears and safer sexual practices.

Shortly thereafter, the city Department of Public Health disclosed that, in fact, infection rates had turned up after years of decline.

E-mail Sabin Russell at srussell@sfchronicle.com.

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