Mobile HIV Screening in Cape Town, South Africa: Clinical Impact, Cost and Cost-Effectiveness

Background: Mobile HIV screening may facilitate early HIV diagnosis. Our objective was to examine the cost-effectiveness of adding a mobile screening unit to current medical facility-based HIV testing in Cape Town, South Africa. Methods and Findings: We used the Cost Effectiveness of Preventing AIDS Complications International (CEPAC-I) computer simulation model to evaluate two HIV screening strategies in Cape Town: 1) medical facility-based testing (the current standard of care) and 2) addition of a mobile HIV-testing unit intervention in the same community. Baseline input parameters were derived from a Cape Town-based mobile unit that tested 18,870 individuals over 2 years: prevalence of previously undiagnosed HIV (6.6%), mean CD4 count at diagnosis (males 423/µL, females 516/µL), CD4 count-dependent linkage to care rates (males 31%–58%, females 49%–58%), mobile unit intervention cost (includes acquisition, operation and HIV test costs, $29.30 per negative result and$31.30 per positive result). We conducted extensive sensitivity analyses to evaluate input uncertainty. Model outcomes included site of HIV diagnosis, life expectancy, medical costs, and the incremental cost-effectiveness ratio (ICER) of the intervention compared to medical facility-based testing. We considered the intervention to be “very cost-effective” when the ICER was less than South Africa's annual per capita Gross Domestic Product (GDP) ($8,200 in 2012). We projected that, with medical facility-based testing, the discounted (undiscounted) HIV-infected population life expectancy was 132.2 (197.7) months; this increased to 140.7 (211.7) months with the addition of the mobile unit. The ICER for the mobile unit was$2,400/year of life saved (YLS). Results were most sensitive to the previously undiagnosed HIV prevalence, linkage to care rates, and frequency of HIV testing at medical facilities. Conclusion: The addition of mobile HIV screening to current testing programs can improve survival and be very cost-effective in South Africa and other resource-limited settings, and should be a priority

Model-derived survival and engagement in care of HIV-infected individuals in Cape Town at 5 years from the start of observation.

<p>The bar graphs shows the proportion (out of the initial 1,240 HIV-infected population) at 5 years who are alive, diagnosed, linked to and retained in care, are on ART, and are HIV RNA suppressed on ART. HIV: human immunodeficiency virus, RNA: ribonucleic acid, ART: antiretroviral therapy.</p

Multi-way sensitivity analyses on prevalence of HIV, linkage to care and facility-based HIV testing frequency.

<p>Prevalence of undiagnosed HIV is varied on the horizontal axis and linkage to care on the vertical axis. Figure a) represents the base case medical facility-based program HIV testing frequency of once every 4 years. Figure b) represents annual medical facility-based program HIV testing. Light gray represents scenarios with an incremental cost-effectiveness ratio (ICER) <1× South African <i>per capita</i> gross domestic product ($8,200), dark gray represents scenarios with an ICER$8,200/YLS to $24,600/YLS and black represents scenarios with an ICER >$24,600/YLS. HIV: human immunodeficiency virus, ICER: incremental cost-effectiveness ratio.</p

Model outcomes and cost-effectiveness of mobile unit HIV testing in Cape Town, South Africa.

*<p>Incremental cost-effectiveness ratios <1× South African <i>per capita</i> gross domestic product (8,200) considered very cost-effective based on WHO suggestions [28]. Costs in 2012 US. Discounted at 3% per year (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0085197#s2" target="_blank">methods</a>). YLS: years of life saved.</p

Model-derived mechanisms of HIV linkage in Cape Town, South Africa.

<p>The charts display the proportion of HIV-infected individuals linked to care with the medical facility-based strategy, and the mobile unit intervention strategy. HIV: human immunodeficiency virus, OI: Opportunistic Infection.</p