Knowledge of the number of recent HIV infections is important for epidemiologic surveillance. Over the past decade approaches have been developed to estimate this number by testing HIV-seropositive specimens with assays that discriminate the lower concentration and avidity of HIV antibodies in early infection. We have investigated whether this “recency” information can also be gained from an HIV confirmatory assay.
Methods and Findings
The ability of a line immunoassay (INNO-LIA HIV I/II Score, Innogenetics) to distinguish recent from older HIV-1 infection was evaluated in comparison with the Calypte HIV-1 BED Incidence enzyme immunoassay (BED-EIA). Both tests were conducted prospectively in all HIV infections newly diagnosed in Switzerland from July 2005 to June 2006. Clinical and laboratory information indicative of recent or older infection was obtained from physicians at the time of HIV diagnosis and used as the reference standard. BED-EIA and various recency algorithms utilizing the antibody reaction to INNO-LIA's five HIV-1 antigen bands were evaluated by logistic regression analysis. A total of 765 HIV-1 infections, 748 (97.8%) with complete test results, were newly diagnosed during the study. A negative or indeterminate HIV antibody assay at diagnosis, symptoms of primary HIV infection, or a negative HIV test during the past 12 mo classified 195 infections (26.1%) as recent (≤ 12 mo). Symptoms of CDC stages B or C classified 161 infections as older (21.5%), and 392 patients with no symptoms remained unclassified. BED-EIA ruled 65% of the 195 recent infections as recent and 80% of the 161 older infections as older. Two INNO-LIA algorithms showed 50% and 40% sensitivity combined with 95% and 99% specificity, respectively. Estimation of recent infection in the entire study population, based on actual results of the three tests and adjusted for a test's sensitivity and specificity, yielded 37% for BED-EIA compared to 35% and 33% for the two INNO-LIA algorithms. Window-based estimation with BED-EIA yielded 41% (95% confidence interval 36%–46%).
Recency information can be extracted from INNO-LIA-based confirmatory testing at no additional costs. This method should improve epidemiologic surveillance in countries that routinely use INNO-LIA for HIV confirmation.
Jörg Schüpbach and colleagues show that a second-generation Western blot antibody test used to confirm HIV infection can also be used to determine rates of recent HIV infection.
Since the first diagnosed cases of AIDS (acquired immunodeficiency syndrome) in 1981, the AIDS epidemic has spread rapidly. Now, 40 million people are infected with HIV (human immunodeficiency virus), the cause of AIDS. HIV infects and kills immune system cells, leaving infected individuals susceptible to other infectious diseases and tumors. The first, often undiagnosed, stage of HIV infection (primary HIV infection) lasts a few weeks and often involves a flu-like illness. During this stage, the immune system begins to respond to HIV by producing antibodies (proteins that recognize viral molecules called antigens). The time needed for these antibodies to appear on testing “seroconversion” (usually 6–12 weeks) is called the window period of the test; HIV antibody tests done during this period give false negative results. During the second, symptom-free stage of HIV infection, which can last many years, the virus gradually destroys the immune system so that by the third stage of infection unusual infections (for example, persistant yeast infections of the mouth) begin to occur. The fourth stage is characterized by multiple AIDS-indicator conditions such as severe bacterial, fungal, or viral infections, and cancers such as Kaposi sarcoma.
Why Was This Study Done?
To monitor the AIDS/HIV epidemic and HIV prevention programs, it is necessary to know how many people in a population have been recently infected with HIV. Serologic testing algorithms for recent HIV seroconversion (STARHS) provide a way to get this information. Early during seroconversion, low levels of antibodies that bind only weakly to their viral antigens (low-affinity antibodies) are made. Later on, antibody concentrations and tightness of binding increase. STARHS calculate the number of recently infected people by analyzing data from special “detuned” HIV antibody assays (for example, a commercially available test called the BED-EIA) that preferentially detect low-concentration, low-avidity antibodies. This type of test cannot, however, be used to determine whether an individual has an HIV infection, because it will miss a substantial fraction of infected people. Diagnosing HIV in an individual person requires more sensitive tests for antibody detection. In this study, the researchers have investigated whether a test called INNO-LIA, which is already being used in some countries to diagnose HIV infection, can also provide information about the recency (newness) of HIV infections.
What Did the Researchers Do and Find?
Between July 2005 and June 2006, 765 HIV infections were newly diagnosed in Switzerland. Using clinical and laboratory information collected at diagnosis, the researchers classified 195 of these infections as recent infections (occurring within the past year) and 161 as older infections. (The remaining infections could not be classified based on the available medical infomation.) The researchers then compared the ability of INNO-LIA (which measures antibodies to five HIV-1 antigens) and BED-EIA to distinguish recent from older HIV infections. BED-EIA correctly identified as recent 65% of the infections classified as recent based on the clinical information, and identified as older 80% of the infections classified as older based on the clinical information. In other words, this test was 65% sensitive (able to detect 65% of the truly recent infections as defined in this study) and was 80% specific (80% accurate in eliminating non-recent infections.) The two best algorithms (mathematical procedures) for converting INNO-LIA data into estimates of recent HV infections had sensitivities of 50% and 40% and specificities of 95% and 99%, respectively. Using actual test results and taking into account these sensitivities and specificities gave estimates of 35% and 33% for the proportion of the whole study population that had been recently infected. BED-EIA gave an estimate of 37%. Finally, a widely used window-based algorithm for recency estimation that uses the numbers of cases that are defined as recent by BED-EIA and the length of the window period for BED-EIA to calculate the annual number of new infections in populations indicated that 41% of the whole study population had been recently infected.
What Do These Findings Mean?
These findings indicate that numbers of recent HIV infections can be extracted from the INNO-LIA HIV diagnostic test and are comparable to those obtained using a window-based algorithm. The test could, therefore, provide a cost-effective means to improve HIV surveillance in countries like Switzerland that already use it for HIV diagnosis. However, because this approach relies on knowing the sensitivity and specificity of the INNO-LIA algorithms, which may vary between populations, the use of these algorithms to estimate numbers of recent HIV infections must be preceded by an assessment of their sensitivity and specificity in each new setting.
Please access these Web sites via the online version of this summary at http://dx.doi.org/10.1371/journal.pmed.0040343.
HIV InSite has comprehensive information on all aspects of HIV/AIDS, including fact sheets on the symptoms of HIV infection, HIV testing, and a chapter on laboratory tests for HIV antibodies
NAM, a UK registered charity, provides information about all aspects of HIV and AIDS, including fact sheets on the stages of HIV infection and HIV testing
The US Centers for Disease Control and Prevention (CDC) provides information on HIV/AIDS, including information on HIV testing and on HIV surveillance by the CDC (in English and Spanish)
Information is available from Avert, an international AIDS charity, on the stages of HIV infection and on HIV testing
Details on the US Centers for Disease Control and Prevention and the World Health Organiztion HIV classification systems are available from the US Department of Veterans Affairs