HIV prevalence estimates: Fact or fiction?
Science and politics often clash. There may be no better example than the issue of HIV in South Africa. Here, where there are more HIV-infected individuals than any other place on Earth, the science of HIV/AIDS and the use of antiretrovirals to treat those already infected have been incredibly controversial political issues.
Politics has always been at the forefront of the HIV/AIDS pandemic elsewhere as well. Even before it had a name, HIV was a political issue. In the days when it first started spreading in the US, rapidly killing those who became infected, the people who would soon be branded AIDS activists implored the US government to openly discuss and actively confront this new disease. As a result there is more legislation in the US devoted to HIV/AIDS than any other disease.
Now some are suggesting that science and politics may be colliding again—this time in the fundamental way scientists measure the scope of the global HIV/AIDS epidemic. Some epidemiologists, whose job it is to track the progress of epidemics, have called into question the accuracy of global HIV prevalence estimates, which represent the total number of people who are thought to be infected with the virus in a region or country at a specific point in time. Prevalence figures are used by governments, public-health agencies, and donor organizations to gauge the severity of the pandemic and this, in turn, drives decisions about how and where money is spent on both HIV prevention and treatment.
In recent years many of the HIV prevalence estimates have been revised based on improved data. In almost all cases the new estimates are lower than previously thought, sometimes dramatically. As a result the total number of people in the world thought to be infected with HIV keeps going down. A few years ago The Joint United Nations Programme on HIV/AIDS (UNAIDS) estimated that 42 million people were HIV infected. As of 2006 the number stands just below 40 million. The question about the accuracy of the estimates was pushed to the forefront recently when India, a country UNAIDS had previously estimated to have five million HIV-infected individuals, cut its HIV prevalence numbers by half.
But more accurate prevalence estimates do not mean that the epidemic is under control. "Even if you cut the [HIV prevalence] numbers in sub-Saharan Africa in half, it's still a huge problem," says James Chin, a retired epidemiologist and faculty member of the University of California in Berkeley.
Getting better data
HIV prevalence estimates are generated by epidemiologists using HIV infection data from small subsets of the population. This epidemiological data is then combined with national population estimates in mathematical models. These prevalence figures are often reported as a percentage, meaning that in a given country a certain percentage of the population is thought to be HIV infected.
In South Africa the national HIV prevalence among adults between the ages of 15 and 49 is estimated by UNAIDS to be nearly 19%. The number of HIV infections is not evenly distributed within the population—many countries have epidemics that are still mainly contained within certain regions or in groups that are at especially high risk, such as injection drug users or commercial sex workers. In some regions of South Africa or in high-risk populations, the prevalence estimates can be twice as high as the national estimate.
Since its inception in 1995, UNAIDS and the World Health Organization (WHO) have been releasing annual estimates of regional HIV prevalence and biannual estimates of national HIV prevalence that serve as the standard measure of the extent of the pandemic and therefore are given a great deal of international attention.
There are several factors that contribute to declining HIV prevalence, including the increased or improved surveillance of HIV infection in many countries, better population estimates, and more accurate computer models for estimating prevalence. The positive influence of HIV prevention campaigns also plays a role, though it is often difficult to directly pinpoint.
But in most cases recent revisions to the UNAIDS figures have been based on the collection of better data that more accurately represents the burden of HIV infection in individual countries. Many countries are conducting more rigorous surveillance of their HIV epidemics, both in the general population and in high-risk groups, either by increasing access to voluntary counseling and testing services or conducting household surveys that are part of the broader demographic and health surveys (DHS). These household, or population-based surveys, allow researchers to track the spread of several diseases in developing countries and monitor trends in the overall health of a population. In DHS surveys, researchers randomly visit a select number of households in a community and collect medical information from the available family members. Recently this survey was altered to include collection of a saliva sample that could later be used to conduct an HIV test.
Previously prevalence estimates were based primarily on data collected from pregnant women who visit antenatal clinics, one of the few settings where there is almost mandatory HIV testing. The original method of projecting prevalence based on data from pregnant women was established in the 1980s by Chin when he was working at the Global Program on AIDS at WHO, long before the job of tracking the pandemic came under the purview of UNAIDS. The idea was the HIV prevalence data collected from sexually active women would be a good surrogate for national prevalence.
But in most cases this data was not representative of HIV infection for the entire population. Most antenatal clinics are located in urban areas, where the HIV prevalence is generally much higher, and the pregnant women who would take advantage of healthcare generally have a higher income, which introduces another bias. Zambia conducted the country's first population-based health study and found that estimates for HIV prevalence based on the number of HIV-infected pregnant women were identical in urban areas, but neglecting rural populations led to a gross overestimation of the overall HIV prevalence in the country. "Data from antenatal clinics helps monitor trends over time," says Karen Stanecki, a senior advisor at UNAIDS in Switzerland. But as the revisions have shown, it may not be a good way to predict national HIV/AIDS prevalence. "The intent [with data from pregnant women] is to monitor changes, not to predict the actual number of people who are infected," says Prabhat Jha, professor of epidemiology at the Center for Global Health Research at the University of Toronto.
Watch out for falling estimates
Following pressure from donor organizations to come up with more accurate prevalence estimates, more countries began conducting population-based surveys instead. As a result the estimates of HIV prevalence often dropped, sometimes precipitously. In 2003 after conducting a population-based survey, Kenya reduced its estimated HIV prevalence from 2.3 million HIV-infected individuals to 1.2 million. "That was a huge reduction," Chin says.
Following that, more than a dozen other countries conducted population-based surveys that led to revisions in the UNAIDS prevalence estimates. In Ethiopia the total number of HIV-infected individuals was cut by half to one million. Cambodia also lowered its national prevalence estimate, from 1.8% of the population to less than 1%. India was one of the latest countries to release new figures showing that the estimated national HIV prevalence is only half of what was previously projected by UNAIDS.
Now 30 countries have conducted population-based surveys to help better estimate the extent of their HIV/AIDS epidemics. In Benin, Mali, and Niger the results from these surveys were nearly identical to the figures estimated using data from antenatal clinics, but in the majority of cases the new figures were lower.
Population-based surveys have several advantages—they reach more individuals in rural areas and include men, who are obviously excluded from surveys in antenatal clinics. But they have disadvantages as well. "The other side of the coin is that people may refuse HIV testing," says Stanecki. "This introduces a bias." These household surveys are also limited to countries where there is a well-developed HIV/AIDS epidemic. "We don't recommend that they be conducted in countries with low-level prevalence," Stanecki adds. Population-based surveys are only applicable in countries where 1% or more of the population is HIV infected, which excludes many countries.
These surveys also tend to exclude marginalized individuals who are often at the highest risk of HIV infection, including injection drug users, commercial sex workers, or transient workers. In countries where the HIV epidemic is still confined within high-risk groups, population-based surveys could therefore drastically underestimate the total number of infected individuals. To adjust for these discrepancies epidemiologists count on other data collected specifically within these populations. But the models are still rather imperfect. "There's always going to be a lot of bias," says Seth Berkley, president of IAVI, who was involved in tracking the HIV epidemic in Uganda when epidemiologists first starting estimating prevalence there. But for most diseases there are few people concerned about the accuracy of prevalence estimates. "The numbers for HIV are probably better than for any other disease ever," adds Berkley. "It's AIDS that has been the big controversy."
Also, the onus of collecting better data falls on the individual countries that have to pay for and conduct population-based surveys. "We don't do any surveys," says Stanecki. "Surveillance is done by the countries themselves." UNAIDS and WHO work with countries, holding regional training workshops on the modeling tools and assisting with calculations of national HIV prevalence estimates.
Politics at play
There are obvious political reasons both for and against individual nations collecting better data on the scope of the HIV/AIDS epidemic. Some countries are motivated to conduct household surveys to show that the epidemics are not as bad as estimates suggest and to prove to the international community that the government is handling the epidemic. Other countries may be leery of showing that there is less of an HIV/AIDS problem because it could result in funding cuts for the country's AIDS-related programs. This controversy was reignited when India's National AIDS Control Organization (NACO) released new prevalence estimates in July, in cooperation with UNAIDS and WHO.
NACO reported that the new estimates were the result of a considerable increase in the number of HIV testing sites in both rural and urban areas and in low-prevalence Indian states, as well as the conduct of comprehensive household surveys. Most agree that these new estimates are more accurate than before. Jha refers to the previous prevalence estimates in India as "guesstimates" and says that the "sources for the new data are better, but still not perfect." There is still a risk that basing the new prevalence estimates on household surveys, which limit access to high-risk individuals, may underestimate the scope of the problem.
As HIV prevalence estimates continue to decrease, some epidemiologists are questioning whether politics might be interfering with the science of tracking the pandemic. "Each year we get numbers from UNAIDS, but we don't have easy access to the supporting analyses and calculations," says David Ho, director of the Aaron Diamond AIDS Research Center in New York City. "Those [analyses] should be put out there for the entire scientific community to comment, along with the conclusions and projections," he says.
Stanecki says this process is already in place. UNAIDS appoints a reference group, including independent scientists and experts, to review the models and publishes all of the findings from this group, she says. But the exact method that was used to establish the new prevalence figures for India has not yet been released publicly. Jha says that, if anything, the Indian experience should argue for making the prevalence numbers "completely transparent in the future."
Mind the gap
Whether or not the numbers are too high, funding and expanding HIV prevention and treatment programs remains critical—only a minority of HIV-infected individuals in developing countries currently receives life-saving antiretrovirals (ARVs) and last year alone four million people were newly infected with the virus.
There is still an enormous gap between what is needed to control and eventually end the HIV/AIDS pandemic and what is currently being done. "The numbers are lower, but there's still the possibility of explosive growth," says Jha. There is an overwhelming need for improving the availability of ARVs to HIV-infected individuals in developing countries and new prevention methods, including AIDS vaccines, to help prevent the millions of new HIV infections that still occur each year. "What India, and the rest of the world, should do is focus on prevention especially for high-risk populations and continue accelerating vaccine research," says Jha.