Accurate HIV incidence estimates are critical to the success of prevention trials
The recently completed study of the contraceptive female diaphragm indicates that the cervical barrier does not provide any additional benefit over already available HIV prevention strategies in reducing HIV transmission in women. This first randomized controlled trial of the latex diaphragm was funded by the Bill & Melinda Gates Foundation and was conducted by researchers at the University of California, San Francisco. It involved nearly 5000 volunteers in Durban and Johannesburg, South Africa, and Harare, Zimbabwe. Results of the trial showed that HIV incidence rates (see Primer, this issue) among women in the control group who only received condoms and counseling were nearly identical—at around 4%—to those seen in women who also received a diaphragm and lubricating gel. During the 18-month study, 158 new HIV infections occurred in the group of women who received the diaphragm, with 151 occurring in the control group.
Nancy Padian, principal investigator of the trial, says these results do not support adding the diaphragm to the current list of HIV prevention strategies. She promoted the idea of testing the diaphragm, which shields the cervix, as a way to prevent HIV transmission after research showed that the cervix was a potential hot-spot for HIV infection (see VAXNovember 2006 Spotlight article, Capping infection). Prior to starting the efficacy trial, Padian conducted several acceptability studies to determine if African women were willing to use a diaphragm. As with most HIV prevention methods other than vaccines, compliance is a key factor in determining the success of the intervention. In this study, women who received diaphragms reported using them during only 70% of their sexual acts. These women reported that their partners also used condoms 54% of the time, while women in the control group who were not using the diaphragm reported that their partners used condoms 85% of the time.
Since condom use was lower in the diaphragm group, yet the number of new infections was equivalent, it is possible that the diaphragm contributed to protection. However the trial was not designed to compare the protective effects of the diaphragm to condoms. Researchers are still trying to find ways to help protect women who are at an increasingly high risk of HIV infection and may not be able to get their partner(s) to use condoms.
The National AIDS Control Organization in India recently revised their national HIV prevalence estimates, drastically lowering the estimated number of HIV-infected people in the country to 2.5 million, a figure less than half of that projected by the Joint United Nations Programme on HIV/AIDS (UNAIDS). India was recently thought to have surpassed South Africa in its total number of HIV-infected individuals, based on surveillance data collected from antenatal clinics and high-risk individuals.
The new prevalence data in India reflects the country's efforts to expand their national HIV/AIDS surveillance system. Last year alone the government added 400 new testing sites and also conducted a population-based survey that tested 102,000 individuals for HIV infection. This resulted in a much different estimate of the HIV prevalence within the general population. These new figures are endorsed by both UNAIDS and the World Health Organization.
The additional surveillance shows that in some of the southern states, including Tamil Nadu, the HIV prevalence has started to either stabilize or decline. This is promising news since HIV prevention has been a focus in these regions for several years. But Indian officials warn against assuming the country's HIV epidemic is sharply declining. Surveillance data from 2006 suggests that HIV infection rates among groups at high risk of HIV infection, including injection-drug users and men who have sex with men, are increasing, especially in urban centers.
All articles written by Kristen Jill Kresge
Why are HIV incidence rates important for AIDS vaccine trials?
To capture the severity of an epidemic, researchers often refer to prevalence and incidence rates. For HIV, prevalence refers to the number of individuals in a population infected with the virus at a certain time point. HIV prevalence can be determined by conducting widespread testing in a region or country and then projecting the total number of infected people.
Incidence refers to the number of people who are newly infected with HIV over time. These figures are usually reported as a percentage and represent the rate of people who are infected in a year or during another specified period of time. Incidence is more difficult to determine than prevalence, but it is also more valuable because it shows how the epidemic is progressing at the current time. This can help explain the dynamics of the epidemic, the speed at which HIV is spreading in light of current sexual or drug-use behaviors, and the effectiveness of available HIV prevention technologies. Accurate estimates of HIV incidence are also indispensable to the design of HIV prevention trials, including those testing AIDS vaccine candidates.
The "power" of incidence
Researchers are searching for a vaccine that could prevent transmission of HIV. But to test the efficacy of vaccine candidates, some volunteers must become infected through exposure in their community for researchers to know if an intervention is effective or not. Volunteers are never purposely exposed to HIV. Researchers compare the number of infections that naturally occur during the trial between a group of volunteers that received the vaccine and another that didn't.
Statisticians "power" a study to show if an intervention is effective based on the number of people they predict will become HIV-infected during the trial. This prediction is based on the HIV incidence in that population and determines, among other things, how many volunteers must be included in the trial.
If the actual incidence during the course of the trial ends up being much lower than predicted, it can profoundly affect the study. Even small differences can have an enormous impact. In a trial where statisticians assume an HIV incidence rate of 5% and a rate of only 4% is actually observed, 25% more volunteers would have to be recruited or the trial would be inconclusive. Expanding recruitment affects the length and cost of the trial. If the incidence is too low the trial could also be stopped prematurely by the data safety monitoring board (see VAX June 2007 Primer onUnderstanding Data Safety Monitoring Boards).
For these reasons it is critical to start a trial with the most accurate incidence estimates possible within the specific population where a study will occur.
Ways to measure incidence
The gold standard method for measuring HIV incidence is the prospective cohort study where researchers follow large groups of HIV uninfected individuals over long periods of time, testing them at regular intervals to see if any have become HIV infected, enabling them to determine the rate of infection. These studies are time-consuming, labor-intensive, and expensive, and add substantially to the already complex process of conducting a clinical trial. Consequently some sponsors may use previously-published incidence data to design a study. But this approach can be risky. Two Phase III microbicide trials that were based on previously-published HIV incidence data were recently stopped before investigators could determine the efficacy of the candidates because the incidence during the trials was so much lower than anticipated (see Spotlight article).
There are several other faster ways to estimate HIV incidence. One involves using mathematical models to predict incidence based on existing prevalence data. Another approach is to test large numbers of people for HIV using immunological tests that can identify people who were recently infected with HIV. These tests recognize either parts of HIV or antibodies to the virus that are detectable within a defined period very early in the course of HIV infection. One of the immunological tests or assays detects the plasma levels of p24 antigen, which is an HIV protein that reaches peak levels very soon after a person is infected. Once the immune system generates HIV-specific antibodies, generally within just a couple of months after initial infection, they bind to the p24 antigen and make it undetectable.
Another approach is to use a combination of two HIV antibody tests (ELISA assays) of differing sensitivity. If antibodies to HIV are detectable by the more sensitive test, another test that is purposely made less sensitive is used to see if antibodies are still detectable. The theory is that only individuals who have been HIV infected for a long time would have developed a strong and broad enough immune response to the virus to be detectable by the less sensitive test.
A third method for detecting recent infection is known as the BED assay, because it was originally developed based on the B, E, and D clades of HIV (see VAX July 2006 Primer on Understanding HIV Clades). The premise of this test is that as the immune system ramps up production of HIV-specific antibodies over time, these responses evolve from having a weaker to a stronger attraction or ability to bind to HIV. The BED assay involves an HIV antibody test that measures the percentage of all antibodies that are specific to HIV. This ratio is then compared with a set of predefined parameters to determine if an infection is classified as recent or not.
Unfortunately none of these methods are reliable or work universally—all of them substantially overestimate incidence in African populations and this can be dangerous when starting AIDS vaccine trials. Researchers generally agree that there is no substitute for the traditional cohort study to accurately determine HIV incidence. Several groups, including IAVI and the US Military HIV Research Program, are currently conducting incidence studies in Africa in preparation for efficacy trials of AIDS vaccine candidates.