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Use of routine HIV testing data for early detection of emerging HIV epidemics in high-risk subpopulations: A concept demonstration study.

ABSTRACT: Introduction:HIV epidemics in hard-to-reach high-risk subpopulations are often discovered years after epidemic emergence in settings with poor surveillance infrastructure. Using hypothesis-generation modeling, we aimed to investigate and demonstrate the concept of using routine HIV testing data to identify and characterize hidden epidemics in high-risk subpopulations. We also compared this approach to surveillance based on AIDS case notifications. Methods:A deterministic mathematical model was developed to simulate an emerging HIV epidemic in a high-risk subpopulation. A stochastic Monte Carlo simulation was implemented on the total population to simulate the sampling process of generating routine HIV testing data. Epidemiological measures were estimated on the simulated epidemic and on the generated testing sample. Sensitivity analyses were conducted on the results. Results:In the simulated epidemic, HIV prevalence saturated at 32% in the high-risk subpopulation and at 0.33% in the total population. The epidemic started its emerging-epidemic phase 28 years after infection introduction, and saturated 67 years after infection introduction. In the simulated HIV testing sample, a significant time trend in prevalence was identified, and the generated metrics of epidemic emergence and saturation were similar to those of the simulated epidemic. The epidemic was identified 4.0 (95% CI 3.4-4.6) years after epidemic emergence using routine HIV testing, but 29.7 (95% CI 15.8-52.1) years after emergence using AIDS case notifications. In the sensitivity analyses, none of the sampling biases affected the conclusion of an emerging epidemic, but some affected the estimated epidemic growth rate. Conclusions:Routine HIV testing data provides a tool to identify and characterize hidden and emerging epidemics in high-risk subpopulations. This approach can be specially useful in resource-limited settings, and can be applied alone, or along with other complementary data, to provide a meaningful characterization of emerging but hidden epidemics.

SUBMITTER: Ayoub HH

PROVIDER: S-EPMC6326224 | biostudies-literature | 2018

REPOSITORIES: biostudies-literature

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Use of routine HIV testing data for early detection of emerging HIV epidemics in high-risk subpopulations: A concept demonstration study.

Ayoub Houssein H HH Awad Susanne F SF Abu-Raddad Laith J LJ

Infectious Disease Modelling 20181106

<h4>Introduction</h4>HIV epidemics in hard-to-reach high-risk subpopulations are often discovered years after epidemic emergence in settings with poor surveillance infrastructure. Using hypothesis-generation modeling, we aimed to investigate and demonstrate the concept of using routine HIV testing data to identify and characterize hidden epidemics in high-risk subpopulations. We also compared this approach to surveillance based on AIDS case notifications.<h4>Methods</h4>A deterministic mathemati ...[more]

PMID: 30839930

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Project description:IntroductionMisclassification errors have been reported in rapid diagnostic HIV tests (RDTs) in sub-Saharan African countries. These errors can lead to missed opportunities for prevention-of-mother-to-child-transmission (PMTCT), early infant diagnosis and adult HIV-prevention, unnecessary lifelong antiretroviral treatment (ART) and wasted resources. Few national estimates or systematic quantifications of sources of errors have been produced. We conducted a comprehensive assessment of possible sources of misclassification errors in routine HIV testing in Zimbabwe.MethodsRDT-based HIV test results were extracted from routine PMTCT programme records at 62 sites during national antenatal HIV surveillance in 2017. Positive- (PPA) and negative-percent agreement (NPA) for HIV RDT results and the false-HIV-positivity rate for people with previous HIV-positive results ("known-positives") were calculated using results from external quality assurance testing done for HIV surveillance purposes. Data on indicators of quality management systems, RDT kit performance under local climatic conditions and user/clerical errors were collected using HIV surveillance forms, data-loggers and a Smartphone camera application (7 sites). Proportions of cases with errors were compared for tests done in the presence/absence of potential sources of errors.ResultsNPA was 99.9% for both pregnant women (N = 17224) and male partners (N = 2173). PPA was 90.0% (N = 1187) and 93.4% (N = 136) for women and men respectively. 3.5% (N = 1921) of known-positive individuals on ART were HIV negative. Humidity and temperature exceeding manufacturers' recommendations, particularly in storerooms (88.6% and 97.3% respectively), and premature readings of RDT output (56.0%) were common. False-HIV-negative cases, including interpretation errors, occurred despite staff training and good algorithm compliance, and were not reduced by existing external or internal quality assurance procedures. PPA was lower when testing room humidity exceeded 60% (88.0% vs. 93.3%; p = 0.007).ConclusionsFalse-HIV-negative results were still common in Zimbabwe in 2017 and could be reduced with HIV testing algorithms that use RDTs with higher sensitivity under real-world conditions and greater practicality under busy clinic conditions, and by strengthening proficiency testing procedures in external quality assurance systems. New false-HIV-positive RDT results were infrequent but earlier errors in testing may have resulted in large numbers of uninfected individuals being on ART.

Dataset Information

Use of routine HIV testing data for early detection of emerging HIV epidemics in high-risk subpopulations: A concept demonstration study.

Publications

Use of routine HIV testing data for early detection of emerging HIV epidemics in high-risk subpopulations: A concept demonstration study.

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