1275. Will an App-Optimized HIV Self-testing Strategy Work for South Africans? Results From a Large Cohort Study. (26th November 2018)

• Record Type: Journal Article
• Authors: Pai, Nitika Pant; Esmail, Ali; Marathe, Gayatri; Oelofse, Suzette; Pretorius, Marietjie; Smallwood, Megan; Daher, Jana; Janssen, Ricky; Saha-Chaudhuri, Paramita; Engel, Nora; Dheda, Keertan
• Is Part Of: Open forum infectious diseases. Volume 5(2018)Supplement 1
• Page Start: S388
• Page End: S388
• Publication Date: 2018-11-26
• Subjects: Communicable diseases -- Periodicals; Medical microbiology -- Periodicals; Infection -- Periodicals; 616.9
• DOI: 10.1093/ofid/ofy210.1108
• Languages: English
• ISSNs: 2328-8957

Abstract

Abstract: Background: HIV self-testing (HIVST) offers a potential for expanded test access; challenges remain in operationalizing rapid personalized linkages and referrals to care. We investigated if an app-optimized personalized HIVST strategy improved referrals, detected new infections and expedited linkages to care and treatment. Methods: In an ongoing cohort study ( n = 2, 000) based in South Africa, from November 2016 to January 2018, to participants presenting to self-test at community township based clinics, we offered a choice of the following strategies: (a) unsupervised HIVST; (b) supervised HIVST. We also observed participants opting for conventional HIV testing (ConvHT) in geographically separated clinics. We observed outcomes (i.e., linkage initiation, referrals, disease detection) and compared it between the two (HIVST vs. ConvHT) for the same duration. Results: Of 2, 000 participants, 1, 000 participants were on HIVST, 599 (59.9%) chose unsupervised HIVST, 401 (40.1%) on supervised HIVST; compared with 1, 000 participants on ConvHT. Participants in HIVST vs. ConvHT were comparable young (mean age 27.7 [SD = 9.0] vs. 29.5 [SD = 8.4]); female (64.0% vs. 74.7%); poor monthly income <3, 000 RAND ($253 USD) (79.9% vs. 76.4%). With HIV ST (vs. ConvHT), many more referrals (17.4% [15.1–19.9] vs. 2.6% [1.7–3.8]; RR 6.69 [95% CI: 4.47–10.01]), and many new infections (86 (8.6% (6.9–10.5)) vs. 57 (5.7% (4.3–7.3)); Odds Ratio 1.55 [95% CI 1.1–2.2]) were noted. Break up: 45 infections in supervised HIVST 45 (52.3%); 41 infections in unsupervised HIVST (47.6%)]. Preference for HIVST was at 91.6%. With an app-optimized HIVST strategy, linkages to care were operationalized within a day in all participants (99.7% (HIVST) vs. 99.2% (ConvHT); RR 1.005 [95% CI: 0.99–1.01]); 99.8% supervised HIVST, 99.7% unsupervised HIVST. Conclusion: Our app-optimized HIVST strategy successfully increased test referrals, detected new infections, and operationalized linkages within a day. This innovative, patient preferred strategy holds promise for a global scale up in digitally literate populations worldwide. Disclosures: All authors: No reported disclosures.