Social network-based approaches to HIV testing: a systematic review and meta-analysis
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Published on: October 31, 2010
Annabelle Choong1,2, Yi Ming Lyu1,2, Cheryl C Johnson3
1Central Clinical School, Monash University, Melbourne, Victoria, Australia.
Introduction:
Social network-based testing approaches (SNAs) encourage individuals ("test promoters") to motivate sexual partners and/or those in their social networks to test for HIV. We conducted a systematic review to examine the effectiveness, acceptability and cost-effectiveness of SNA.
Methods:
We searched five databases from January 2010 to May 2023, and included studies that compared SNA with non-SNA. We used random-effects meta-analysis to combine effect estimates. Certainty was assessed using the GRADE approach.
Results:
We identified 47 studies. SNA may increase uptake of HIV testing compared to non-SNA (RR 2.04, 95% CI: 1.06-3.95, Low certainty). The proportion of first-time testers was probably higher among partners or social contacts of test promoters using SNA compared to non-SNA (RR 1.49, 95% CI: 1.22-1.81, Moderate certainty). The proportion of people who tested positive for HIV may be higher among partners or social contacts of test promoters using SNA compared to non-SNA (RR 1.84, 95% CI: 1.01-3.35, Low certainty). There were no reports of any adverse events or harms associated with SNA. Based on six cost-effectiveness studies, SNA was generally cheaper per person tested and per person diagnosed compared to non-SNA. Based on 23 qualitative studies, SNA is likely to be acceptable to a variety of populations.
Discussion:
Our review collated evidence for SNA to HIV testing covering the key populations and the general population who may benefit from HIV testing. We summarized evidence for the effectiveness, acceptability and cost-effectiveness of different models of SNA. While we did not identify an ideal model of SNA that could be immediately scaled up, for each setting and population targeted, we recommend various implementation considerations as our meta-analysis showed the effectiveness might differ due to factors which include the testing modality (i.e. use of HIV self-testing), type of test promoters, long or short duration of recruitment and use of financial incentives.
Conclusions:
Social network-based approaches may enhance HIV testing uptake, increase the proportion of first-time testers and those testing positive for HIV. Heterogeneity among studies highlights the need for context-specific adaptations, but the overall positive impact of SNA on HIV testing outcomes could support its integration into existing HIV testing services.
