Approaches and impacts of digital health in HIV self-testing uptake & use among populations from low- and middle-income countries: a descriptive systematic review and meta-analysis.

Background: Human immunodeficiency virus self-tests (HIVSTs) offer a convenient, private, and accessible alternative to standard testing in healthcare settings. Digital health (dHealth) is defined as technologies that interface with individual or community populations to monitor and address health needs. Such technologies may improve the uptake and use of HIVST in low- and middle-income countries (LMICs). However, this has not been well characterized, and there remains controversy on the impact of this public health approach with specific concerns regarding feasibility and confidentiality. This systematic review and meta-analysis evaluated the impacts of dHealth on uptake and use of HIVST in LMICs. Methods: Six databases (PubMed, OVID: Global Health, Embase, CINAHL, Web of Science, and Cochrane Library) were searched from January 1, 1990 to January 4, 2024. Inclusion criteria using the population, intervention, control, outcomes (PICO) framework included World Health Organization (WHO) defined LMICs, HIVST programming with dHealth interventions, identification of at least one outcome of interest, and appropriate study type: randomized controlled trials (RCTs) or observational studies. Two reviewers screened eligible records (κ=0.86) and then proceeded with data extraction. Risks of bias and quality analysis were accessed via the Cochrane Risk of Bias Tool 2.0 and the New Castle Ottawa Scale. County income classification, healthcare setting, dHealth HIVST uptake, HIVST use, and prevalence of HIV positivity data were collected. Pooled estimates were calculated using random-effects models with assessment of heterogeneity. Results: Of 1,708 reports screened, 5 met inclusion criteria. The cumulative sample was 2,581 subjects, from 3 RCTs and 2 observational studies. The studies were primarily from Africa (60%) and investigated dHealth interventions like text messaging, social media platforms (WeChat), and a specific HIVST app. Two studies focused on men who have sex with men (MSM) and one studied adolescent refugees. The pooled HIVST uptake was 83.5% in the exposed group compared to 66.8% in the unexposed group. Pooled analysis showed no increase in HIVST use with dHealth programming [odds ratio (OR): 0.96, 95% confidence interval (CI): 0.31-2.99]. The pooled prevalence of confirmatory testing was 82.5% in the intervention arm and 25.1% in the control arm. Rates of HIV identification was similar across study arms. Two of the five reports had low quality of evidence with the remaining reports having moderate quality. Common themes across the studies included high risk for selection bias and attrition bias. Conclusions: The pooled analysis showed no significant difference with dHealth interventions in HIVST programming outcomes. Of the included reports, most investigations took place in the community, within African countries, and used dHealth interventions like text messaging and WeChat. Most populations were upper-middle income, and highly heterogeneous. Further investigation is needed to better understand how dHealth modalities can be used across HIVST programs in LMICs and address specific controversies related to feasibility, usability, and confidentiality.