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Open Access

Peer-reviewed

Research Article

Demand creation for HIV testing services: A systematic review and meta-analysis

Abstract

Background

HIV testing services (HTS) are the first steps in reaching the UNAIDS 95-95-95 goals to achieve and maintain low HIV incidence. Evaluating the effectiveness of different demand creation interventions to increase uptake of efficient and effective HTS is useful to prioritize limited programmatic resources. This review was undertaken to inform World Health Organization (WHO) 2019 HIV testing guidelines and assessed the research question, “Which demand creation strategies are effective for enhancing uptake of HTS?” focused on populations globally.

Methods and findings

The following electronic databases were searched through September 28, 2021: PubMed, PsycInfo, Cochrane CENTRAL, CINAHL Complete, Web of Science Core Collection, EMBASE, and Global Health Database; we searched IAS and AIDS conferences. We systematically searched for randomized controlled trials (RCTs) that compared any demand creation intervention (incentives, mobilization, counseling, tailoring, and digital interventions) to either a control or other demand creation intervention and reported HTS uptake. We pooled trials to evaluate categories of demand creation interventions using random-effects models for meta-analysis and assessed study quality with Cochrane’s risk of bias 1 tool. This study was funded by the WHO and registered in Prospero with ID CRD42022296947.

We screened 10,583 records and 507 conference abstracts, reviewed 952 full texts, and included 124 RCTs for data extraction. The majority of studies were from the African (N = 53) and Americas (N = 54) regions. We found that mobilization (relative risk [RR]: 2.01, 95% confidence interval [CI]: [1.30, 3.09], p < 0.05; risk difference [RD]: 0.29, 95% CI [0.16, 0.43], p < 0.05, N = 4 RCTs), couple-oriented counseling (RR: 1.98, 95% CI [1.02, 3.86], p < 0.05; RD: 0.12, 95% CI [0.03, 0.21], p < 0.05, N = 4 RCTs), peer-led interventions (RR: 1.57, 95% CI [1.15, 2.15], p < 0.05; RD: 0.18, 95% CI [0.06, 0.31], p < 0.05, N = 10 RCTs), motivation-oriented counseling (RR: 1.53, 95% CI [1.07, 2.20], p < 0.05; RD: 0.17, 95% CI [0.00, 0.34], p < 0.05, N = 4 RCTs), short message service (SMS) (RR: 1.53, 95% CI [1.09, 2.16], p < 0.05; RD: 0.11, 95% CI [0.03, 0.19], p < 0.05, N = 5 RCTs), and conditional fixed value incentives (RR: 1.52, 95% CI [1.21, 1.91], p < 0.05; RD: 0.15, 95% CI [0.07, 0.22], p < 0.05, N = 11 RCTs) all significantly and importantly (≥50% relative increase) increased HTS uptake and had medium risk of bias.

Lottery-based incentives and audio-based interventions less importantly (25% to 49% increase) but not significantly increased HTS uptake (medium risk of bias). Personal invitation letters and personalized message content significantly but not importantly (<25% increase) increased HTS uptake (medium risk of bias). Reduced duration counseling had comparable performance to standard duration counseling (low risk of bias) and video-based interventions were comparable or better than in-person counseling (medium risk of bias). Heterogeneity of effect among pooled studies was high. This study was limited in that we restricted to randomized trials, which may be systematically less readily available for key populations; additionally, we compare only pooled estimates for interventions with multiple studies rather than single study estimates, and there was evidence of publication bias for several interventions.

Conclusions

Mobilization, couple- and motivation-oriented counseling, peer-led interventions, conditional fixed value incentives, and SMS are high-impact demand creation interventions and should be prioritized for programmatic consideration. Reduced duration counseling and video-based interventions are an efficient and effective alternative to address staffing shortages. Investment in demand creation activities should prioritize those with undiagnosed HIV or ongoing HIV exposure. Selection of demand creation interventions must consider risks and benefits, context-specific factors, feasibility and sustainability, country ownership, and universal health coverage across disease areas.

Author summary

Why was this study done?

  • This review was undertaken to inform World Health Organization (WHO) 2019 and 2023 HIV testing guidelines.
  • HIV testing services (HTS) is the first step in reaching global goals for HIV management and control.
  • Evaluating the effectiveness of different demand creation interventions to increase uptake of HTS is useful to prioritize limited programmatic resources.

What did the researchers do and find?

  • We conducted a systematic review and meta-analysis to answer the question, “Which demand creation strategies are effective for enhancing uptake of HTS?” focused on populations globally.
  • We found that several classes of demand creation interventions had important and significant impacts on HIV testing uptake. These included: mobilization, couple- and motivation-oriented counseling, peer-led interventions, conditional fixed value incentives, and short message service (SMS) interventions.
  • We also found that reduced duration counseling and video-based interventions are an efficient and effective alternative to address staffing shortages.
  • Box 1 provides a description of what each of these categories of demand creation interventions mean.

What do these findings mean?

  • These findings can allow policymakers to select effective demand creation strategies, prioritize resources efficiently, and de-prioritize less effective strategies for their own countries.
  • The impact of an effective intervention may vary depending on where and how it is implemented; policy decisions should consider setting, feasibility and sustainability, country ownership, and universal health coverage.

Citation: Wagner AD, Njuguna IN, Neary J, Lawley KA, Louden DKN, Tiwari R, et al. (2023) Demand creation for HIV testing services: A systematic review and meta-analysis. PLoS Med 20(3): e1004169. https://doi.org/10.1371/journal.pmed.1004169

Received: September 2, 2022; Accepted: January 5, 2023; Published: March 21, 2023

This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

Data Availability: All relevant data are within the manuscript and its Supporting information files.

Funding: The funding for this work was directly provided to WHO through grants from BMGF INV-024432 (to CJ) and OPP1177903 (to CJ). These grants are used to support WHO’s systematic reviews for guideline development. WHO then collaborated and sub-contracted UW (to ADW and to AD) for their support on this systematic review. BMGF had no direct role in the study and systematic review. WHO contributed to the study starting with protocol development to align study and analysis with WHO guideline handbook and methodologies.

Competing interests: The authors have declared that no competing interests exist.

Abbreviations: ART, antiretroviral therapy; CI, confidence interval; COVID-19, Coronavirus Disease 2019; EPOC, Effective Practice and Organisation of Care; GDG, Guideline Development Group; HTS, HIV testing services; MSM, men who have sex with men; PICO, population, intervention, comparator, outcome; PLWH, people living with HIV; PrEP, pre-exposure prophylaxis; PWID, people who inject drugs; RCT, randomized controlled trial; RD, risk difference; RR, relative risk; SMS, short message service; UN, United Nations; VMMC, voluntary medical male circumcision; WHO, World Health Organization

Introduction

The United Nations (UN) has set ambitious targets to have 95% of people living with HIV (PLWH) diagnosed, 95% of them on antiretroviral therapy (ART), and 95% of them virally suppressed by 2025 [1]. At the end of 2021, 85% of PLWH knew their status [2]. Despite substantial progress, gaps remain, with 7.8 million PLWH unaware of their status; additionally, there were still 1.5 million new HIV infections in the past year [2]. Those most affected by HIV remain unreached, particularly men and adolescents and young adults (aged 10 to 24) in southern Africa, key populations and their partners (including men who have sex with men [MSM], people who inject drugs [PWID], people in prisons and other closed settings, sex workers, and transgender people). Populations historically most affected by HIV have experienced societal marginalization, stigma, and low engagement with health care.

Demand creation includes activities intended to improve an individual’s knowledge and attitudes, motivation and intentions, and eventually decision and behavior to seek HIV testing services (HTS). Demand creation interventions include those intended to directly impact a barrier individuals may face in accessing HTS, for example, incentives, community mobilization campaigns, and counseling-oriented interventions. Interventions that have an indirect impact on a person’s demand for HTS or which might influence supply of, or access to HTS are not considered demand creation, for example, provider training, health service quality improvement, operational flow improvement, and novel HIV testing locations or modalities.

Closing the gaps and reaching the remaining PLWH who do not know their status will require generating demand for HTS among this population, as well as people at high ongoing risk and with limited access or uptake of health services. Resources for HIV funding dropped by US $1 billion in 2018, marking the first time that global HIV funding declined since 2000 [3]. In the face of plateauing and declining resources, prioritizing limited resources toward effective demand creation approaches is essential. Additionally, while supply side strategies for improving HIV testing uptake have improved coverage of HIV testing and testing frequency, the remaining populations may require re-prioritizing demand generation strategies.

We conducted a systematic review to assess which demand creation approaches for HTS were effective in order to provide clearer guidance to countries, programs, and key stakeholders. Findings of this review informed the World Health Organization’s (WHO) update to the consolidated guidelines on HTS [4] and are informing the update in 2023. Findings of the review can also be used to inform program planning.

Methods

Guiding frameworks

We followed the PRISMA guidance for the appropriate conduct and reporting of systematic reviews and meta-analyses. The review protocol was developed with input from University of Washington researchers, the WHO Guideline Development Group (GDG) and the WHO HIV Department. The full review protocol is available in Prospero with ID CRD42022296947 [5]. The review departed from the protocol in the following ways: (1) we did not include non-experimental studies, as there was sufficient data from randomized controlled trials (RCTs); and (2) we did not present GRADE tables.

To categorize demand creation strategies for HTS, we used the User-Centric Behavioral Framework, which blends the social-ecological framework (individual, personal, cultural/societal, and structural levels of influence) with the stages of change framework (unaware, aware, pre-intention, intention, action) [6]. This framework has previously been used to categorize demand creation strategies for voluntary medical male circumcision (VMMC), which has many of the same demand-related barriers as HIV testing. We used the framework to consider interventions that generated demand by moving individuals along the spectrum from unawareness to action, distinguishing demand generation from supply-side interventions. We categorized interventions using an inductive approach; major categories and subcategories were developed in collaboration with WHO and the GDG. Intervention categories were not mutually exclusive and included: (1) incentivization (subcategories: a: conditional financial and b: lottery); (2) mobilization; (3) tailored or targeted (a: peer-led, b: personalized content and messages, c: personal invitation letters); (4) messaging and counseling (a: general HIV counseling, b: HIV counseling plus economic empowerment, c: couple-oriented counseling, d: message content framing, e: motivation-oriented counseling, f: reduced duration or intensity counseling); and (5) digitization (a: video- or audio-based, b: social media, c: website, d: short message service [SMS]). See Box 1 for a table of definitions and descriptions of each intervention category.

Box 1. Definitions of demand creation categories.

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Search strategy and inclusion criteria

The following electronic databases were searched through September 28, 2021: PubMed, PsycInfo, Cochrane CENTRAL, CINAHL Complete, Web of Science Core Collection, EMBASE, and Global Health Database. CAB Abstracts were searched through October 10, 2019; however, access to this database ceased after this date. No language restrictions were placed on the search. The following conference abstract books were searched: International AIDS Conference 2017, 2018, 2019, 2020, and 2021. The Conference on Retroviruses and Opportunistic Infections 2017, 2018, 2019, 2020, and 2021 were searched through the EMBASE database.

A search strategy was developed by ADW, IN, and DL (a research librarian), with review and adaptation from WHO HTS team members (CJ, MJ, RB, MD) and the independent methodologist (NS). It included 3 components (full strategy in S1 Appendix): (1) an HIV testing term; (2) 4 sets of terms to reflect major groups of demand creation strategies (e.g., incentives; SMS and digital individual media; community media, counseling, and other educational interventions; peer-based interventions); and (3) the sensitivity- and precision-maximizing version of the Cochrane Highly Sensitive Search Strategy for identifying RCTs [7]. The conference abstract book search terms were more limited, due to the limited search ability on conference websites, and can be found in S1 Appendix.

This review was informed by the population, intervention, comparator, outcome (PICO) question: “Which demand creation strategies are effective for enhancing uptake of HIV testing services (HTS)?” In order to be included in the review, studies needed to be published in a peer-reviewed journal or conference abstract, employ an RCT (either cluster- or individual-level randomization, including stepped-wedge studies), and meet PICO criteria. The population of interest was individuals receiving demand creation interventions for HTS; the interventions were those aimed to generate demand for HTS; the comparators were those with either an alternative demand creation strategy or an absence of demand creation strategies (control); the outcomes of interest included in this publication included HTS uptake (percentage of individuals who completed HIV testing among those targeted for intervention or control) and HTS yield (percentage of individuals with reactive HIV tests among those targeted for intervention or control). Yield is available only from a subset of studies and is presented when available.

Data analysis

We used Covidence (Veritas Health Innovation, Melbourne, Australia) to manage search results and determine eligibility for the review. A series of reviewers (ADW, IN, JNE, MAB, RT, HH, NK, CW, JN, KL) were involved in screening titles and abstracts, as well as full-text articles to determine inclusion and for extraction. Two reviewers evaluated each identified abstract independently and subsequently whether records should have full-text review and abstraction; discrepancies at each step were resolved by a third reviewer. Data extraction and quality assessment were conducted by JNE, INN, JN, BM, CO, RB, KL, RT, and ADW. Two reviewers extracted data from each manuscript or abstract; at this step, the second reviewer was not blind to the extraction details of the first reviewer.

Meta-analysis using random-effects models to combine effect estimates was conducted with studies that used the same intervention and control, and outcomes were measured comparably (see details of full meta-analysis approach in S2 Appendix). Relative risks (RR), risk differences (RD), and 95% confidence intervals (CI) were calculated, along with I2 statistics to measure statistical heterogeneity of effect. As recommended by the Cochrane handbook, RRs were our primary estimate and RDs were considered a supporting estimate. Meta-analysis was not conducted in cases where there was clinical heterogeneity (in which the interventions compared were heterogeneous); meta-analysis was conducted and is presented at any level of statistical heterogeneity of effect. At high levels of statistical heterogeneity, subgroup analyses were conducted by region, sex, and age group. To account for clustering in cluster RCTs, the standard error of the effect estimate was inflated by multiplying it by the square root of the design effect. Meta-analysis and data summary were conducted using Stata 17 and Excel by WJ, RT, JN, and ADW.

Evidence magnitude was classified as: important: RR ≥1.5 or RR ≤0.5; less important: RR <1.5 and ≥1.25 or RR>0.5 and <0.75; and not important: RR <1.25 and >0.75. These categorizations were established with the WHO GDG to prioritize high-impact interventions for demand creation. Interpretation of effect size importance followed Effective Practice and Organisation of Care (EPOC) guidance for reporting the effects of interventions [8].

Quality assessment

Risk of bias was assessed using the Cochrane Collaboration’s tool (version 1.0) for assessing risk of bias [9]. This tool assesses random sequence generation (selection bias), allocation concealment (selection bias), blinding of participants and personnel (performance bias), blinding of outcome assessment (detection bias), blinding of outcome assessment (detection bias), incomplete outcome data addressed (attrition bias), incomplete outcome data, and selective reporting (reporting bias). For cluster-randomized trials, an additional set of domains were assessed, based on the Cochrane handbook, including: incorrect analysis of clustered data, comparability with individually randomized trials, recruitment bias, baseline imbalances, and loss of clusters. We assessed risk of publication bias using funnel plots and Egger’s test. We conducted trim-and-fill analyses to address publication bias.

Results

The database search yielded 39,637 records and conference abstract search yielded 507 records; after duplicates were removed, 10,583 records were screened for title and abstract relevance and 9,631 were excluded as not relevant; 952 full-text articles were assessed and 828 were excluded. A total of 124 RCTs were included for data extraction; 113/124 (91%) were published peer-reviewed studies and 11/124 (9%) were conference abstracts (Fig 1); Table 1 summarizes the study characteristics. These 124 RCTs contributed data to analyses about incentives (N = 21), mobilization (N = 12), targeted and tailored interventions (N = 31), counseling (N = 39), and digital interventions (N = 39). RCTs could appear in multiple categories.

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Fig 1. PRISMA flowchart.

RCT, randomized controlled study.

https://doi.org/10.1371/journal.pmed.1004169.g001

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Table 1. RCTs evaluating different demand creation mechanisms.

https://doi.org/10.1371/journal.pmed.1004169.t001

Descriptions of study categories are provided in the text box above (Box 1). Studies represented a range of regions, with 53 trials from the African region, 54 from the region of the Americas, 12 from the Western Pacific region, 9 from the European region, and 7 from the Southeast Asia region (S3 Appendix). Across studies, the risk of bias varied, with many having high or unclear risk of bias elements (Fig 2A and 2B). Among the meta-analysis pooled studies, risk of bias was medium (conditional fixed value incentives, lottery incentives, mobilization, peer-led, personalized messages, personal invitation letters, HIV-specific information and counseling, HIV-specific information with economic empowerment, couples counseling, motivation-oriented counseling, reduced duration counseling, video- and audio-based, SMS) or low (reduced duration counseling). We reviewed each study and identified 4 that had only 1 element of high risk of bias (lack of randomization). Unfortunately, none of the 4 studies tested the same intervention and it was therefore not possible to conduct a sensitivity analysis in the meta-analyses restricted to studies with low risk of bias.

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Fig 2. (A and B) Risk of bias summary.

Panel (A): Pooled studies. Studies are grouped by the meta-analysis that they contributed to. Panel (B): Not pooled studies. Studies that were not pooled are listed in alphabetical order.

https://doi.org/10.1371/journal.pmed.1004169.g002

Incentives

There were 21 RCTs that tested incentives for clients or partners [10–30] (Table 1). Fourteen RCTs were conducted in Africa [11–15,17,18,21,24,25,27,28,30], 6 in the Americas [16,19,20,22,23,26], and 2 in Asia [10,29]. Seven focused on heterosexual couples [12,14,17,20,23,27,30], 4 on heterosexual men [11,15,21,22], 4 on women or caregivers of children [14,16,24,25], 2 on children and adolescents [18,28], 5 on priority populations including sex workers [10,13], previously incarcerated adults [26], and transgender women and MSM [19,29].

Uptake of HTS.

Eleven RCTs reported on uptake of HTS following use of fixed value, conditional incentives of any value compared to no incentive [12–15,18,20,23,24,26,28,29]. Fixed financial incentives significantly and importantly increased uptake of HTS compared to no incentive in the pooled analysis (pooled RR: 1.52, 95% CI [1.21, 1.91], p < 0.05; I2 = 96.4%; pooled RD: 0.15, 95% CI [0.07, 0.22], p < 0.05; I2 = 95.1%) (Figs 3 and 4 and S7 Appendix) with medium risk of bias. Three RCTs reported on uptake of HTS using lottery-based incentives of any value compared to no incentive [15,18,19]. A meta-analysis of these studies showed lottery-based incentives did not significantly but did less importantly impact HTS uptake compared to no incentive (RR: 1.33, 95% CI [0.71, 2.49], p = 0.376; I2 = 87.3%; RD: 0.06, 95% CI [−0.08, 0.20], p = 0.375; I2 = 89.5%) (Figs 3 and 4 and S7 Appendix) with medium risk of bias. Eight RCTs [10,11,16,17,21,22,25,27,30] were not pooled due to intervention and incentive heterogeneity.

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Fig 3. Summary of effect sizes of pooled estimates of uptake from meta-analysis.

Pooled RR effect sizes ranged from near 1.0 (indicating no improvement in uptake of HTS) through nearly 7.0 (indicating a large effect size); not important improvements (RR <1.25) are shown in light blue, less important improvements (RR: 1.25–1.50) are shown in medium blue, and important improvements (RR ≥1.50) are shown in dark blue along the effect size spectrum from left to right. The statistical significance of each pooled estimate is indicated by green points (indicating statistical significance: p < 0.05) or blue points (indicating no statistical significance: p > 0.05). CI, confidence interval; HTS, HIV testing service; RR, relative risk; SMS, short message service; vs., versus.

https://doi.org/10.1371/journal.pmed.1004169.g003

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Fig 4. Meta-analysis plots of HTS uptake in relative and absolute differences.

Panels (A–O) 1: INCENTIVES: (A) conditional fixed value incentives, (B) lottery-based incentives, 2: MOBILIZATION: (C) mobilization, 3: TAILORED or TARGETED: (D) peer-led interventions, (E) personalized messages, (F) personal invitation letters, 4: MESSAGES & COUNSELING: (G) HIV-specific information and counseling, (H) HIV-specific information with economic empowerment, (I) couples counseling, (J) motivation-oriented counseling, (K) reduced duration counseling, 5: DIGITIZATION: (L) video-based vs text, (M) video-based vs. in-person, (N) audio information, (O) SMS. CI, confidence interval; CRCT, cluster-randomized trial; RCT, randomized controlled trial; RD: risk difference; REML, restricted maximum likelihood; RR, relative risk; SMS, short message service; SOC, standard of care.

https://doi.org/10.1371/journal.pmed.1004169.g004

In subgroup analyses by region, the effect of fixed value, conditional incentives was consistent across the African region, region of the Americas, and Western Pacific region (RR: 1.55, 1.45, 1.51, respectively). In subgroup analyses by age and sex, the effect of fixed value, conditional incentives was more pronounced among children and adolescents (RR: 1.75), women (RR: 2.41), and less pronounced among men (RR: 1.44) and trials that included men and women (RR: 1.15). While heterogeneity for lottery-based incentives was high, there were too few trials to explore subgroups (S4 Appendix).

Yield.

Five RCTs reported on the effect of fixed value financial incentives on yield compared to no incentive [14–16,20,24]. A meta-analysis of these studies showed incentives less importantly but not significantly increased yield overall (RR: 1.38, 95% CI [0.68, 2.80], p = 0.374; I2 = 0%; RD: 0.01, 95% CI [−0.00, 0.02], p = 0.322; I2 = <0.1%) (Fig 5 and S7 Appendix). This estimate may be biased due to at least 1 zero count in the numerator.

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Fig 5. Meta-analysis plots of HTS yield in relative and absolute differences.

Panels (A–E): (A) conditional fixed value incentives, (B) mobilization, (C) peer-led interventions, (D) HIV-specific information and counseling, (E) couples counseling. CI, confidence interval; CRCT, cluster-randomized trial; RCT, randomized controlled trial; RD, risk difference; REML, restricted maximum likelihood; RR, relative risk; SOC, standard of care.

https://doi.org/10.1371/journal.pmed.1004169.g005

Mobilization

Twelve RCTs examined the role of mobilization [31–43] (Table 1). Nine RCTs were in Africa [31,33,35,36,38–43] and 3 were in the Americas [32,34,37]. Twelve focused on general population heterosexual adult men and women and while 1 focused on women.

Uptake.

Four RCTs [35–37,39,42] reported on the effect of any mobilization on HTS uptake compared with standard HTS without mobilization. A meta-analysis of these studies showed mobilization significantly and importantly increased HTS uptake in community settings compared to no mobilization (RR: 2.01, 95% CI [1.30, 3.09], p < 0.05; I2 = 94.3%; RD: 0.29, 95% CI [0.16, 0.43], p < 0.05; I2 = 90.8%) (Figs 3 and 4 and S7 Appendix) with medium risk of bias. Eight RCTs [31–34,38,40,41,43] could not be pooled because of heterogeneity of interventions.

In subgroup analyses by region, the effect of mobilization was more pronounced among the African region (RR: 2.16) and Southeast Asian region (RR: 2.99) and less pronounced in the region of the Americas (RR: 0.98). In subgroup analyses by sex, the effect of mobilization was more pronounced among trials that included men and women (RR: 3.05), followed by men alone (RR: 1.88), followed by women alone (RR: 1.33) (S4 Appendix).

Yield.

Two RCTs reported on the effect of mobilization on HTS yield compared to no mobilization [35,42]. A meta-analysis showed mobilization did not significantly but did importantly increase yield (RR: 1.67, 95% CI [0.53, 5.29], p = 0.382; I2 = 0%; RD: 0.01, 95% CI [−0.01, 0.03], p = 0.395; I2 = 0%) (Fig 5 and S7 Appendix).

Targeted and tailored interventions

Thirty-two RCTs reported on the effect of targeted and tailored interventions. Fifteen RCTs assessed peer-led interventions [29,32–34,37,44–53], 13 RCTs assessed personalized content and messages [28,54–65], and 4 RCTs assessed the use of personal invitation letters [66–69].

Peer-led interventions

Fifteen RCTs assessed peer-led interventions [29,32–34,37,44–53] (Table 1). Eleven RCTs were from the Americas [32,34,37,45–49,51–53], 3 were from Africa [33,44,50], and 1 was from China [29]. Eight RCTs focused on MSM [29,45–48,51–53], 5 focused on general population men and women [32–34,37,50], 1 focused on general population men [49], and 1 focused on adolescents [44].

Uptake.

A meta-analysis of 10 studies [29,37,45–49,51–53] of peer-led interventions on HTS uptake showed peer-based interventions importantly and significantly increased HTS uptake compared to standard HTS without peer-based interventions (RR: 1.57, 95% CI [1.15, 2.15], p < 0.05; I2 = 85.3%; RD: 0.18, 95% CI [0.06, 0.31], p < 0.05; I2 = 90.2%) (Figs 3 and 4 and S7 Appendix) with medium risk of bias.

In subgroup analyses by region, the effect of peer-led interventions was more pronounced among the region of the Americas (RR: 1.72) and less pronounced among the Western Pacific region (RR: 0.77). In subgroup analyses by sex, the effect of peer-led interventions was more pronounced among trials that included men alone (RR: 1.68) than trials that included men and women (RR: 0.98). In trials that included men who have sex with men (and 1 trial that additionally included transgender women), the effect of peer-led interventions was RR: 1.61 (S4 Appendix).

Yield.

Two RCTs reported on the effect of peer-led interventions on HTS yield compared to no peer-led intervention [45,53]. A meta-analysis showed peer-led interventions did not significantly or/and did not importantly impact yield (RR: 0.86, 95% CI [0.26, 2.81], p = 0.800; I2 = 0%; RD: −0.00, 95% CI [−0.03, 0.03], p = 0.826; I2 = 0%) (Fig 5 and S7 Appendix).

Personalized content and messages

Thirteen RCTs examined the role of personalized content and messages [29,54–65]. Nine RCTs were from the Americas [54–61,64], 2 were from China [62,65], 1 was from Africa [28], and 1 was from Europe [63]. Seven RCTs focused on MSM [54,55,57,59,62,64,65], 2 focused on general population adults [58,63], 1 focused on adult men [28], 2 focused on adult women [60,61], and 1 focused on adolescents and young adults [56] (Table 1).

Uptake.

Seven RCTs [28,54,57,59,62,63,65], most of which focused on MSM (excluding [28,63]), reported on HTS uptake using personalized content and included a standard of care arm. A meta-analysis of these studies showed tailored content messages did significantly but not importantly increase uptake (RR: 1.03, 95% CI [1.00, 1.05], p < 0.05; I2 = 0%; RD: 0.01, 95% CI [−0.01, 0.02], p = 0.362; I2 = 22.2%) (Figs 3 and 4 and S7 Appendix) with medium risk of bias. This estimate was heavily driven by 1 large study [63], which assessed personalized ethnic and gender messaging and showed a significant but not important increase in HTS uptake (RR: 1.03, 95% CI [1.00, 1.05]).

Personal invitation letters

Four RCTs examined the role of personal invitation letters to male partners [66–69]. All studies were in Africa and focused on the male partners of pregnant women (Table 1).

Uptake.

A meta-analysis of 2 of these studies [66,67] showed that personal invitation letters significantly but not importantly increased uptake (RR: 1.23, 95% CI [1.03, 1.47], p < 0.05; I2 = 0%; RD: 0.04, 95% CI [0.00, 0.07], p < 0.05; I2 = 0%) (Figs 3 and 4 and S7 Appendix) with medium risk of bias. Two other RCTs included invitation letters in both intervention and control [68,69].

Counsel (information and counseling messages)

There were 38 RCTs that reported on the effect of counseling messages: 14 RCTs on general counseling messages prior to HTS [70–83], 4 RCTs on couples counseling [84–87], 12 RCTs on message and content framing prior to HTS [33,88–98], 4 RCTs on motivational counseling messages prior to HTS [99–102], and 4 RCTs on reduced duration counseling prior to HTS [103–106].

HIV-specific counseling with and without economic empowerment

Fourteen RCTs examined the role of general HIV counseling messages and content prior to HTS [70–83] (Table 1). Eight studies were conducted in the Americas [70–72,75,76,81–83], 3 in Africa [73,77,79], 2 in Southeast Asia [74,80], and 1 in Europe [78]. One study focused on general population adults [74], 4 on women [75,77,78,80], 1 on MSM [83], 3 on PWID [70,72,75], and 5 on adolescents [71,73,76,79,81], one of which focused on transgender and non-binary adolescents [81].

Uptake.

Among the 14 RCTs reported on HTS uptake following general HIV counseling messages [70–83], a meta-analysis of 7 RCTs [70–72,78,79,83,95] showed HIV-specific information and counseling messages prior to testing significantly but not importantly increased HTS uptake compared to standard services (RR: 1.22, 95% CI [1.01, 1.48], p < 0.05; I2 = 64.6%; RD: 0.05, 95% CI [0.00, 0.10], p < 0.05; I2 = 76.5%) (Figs 3 and 4 and S7 Appendix) with medium risk of bias. Two RCTs [77,80] reported on HTS uptake following HIV-specific counseling and economic empowerment. A meta-analysis of these studies indicates HIV-specific counseling with economic empowerment significantly and importantly increased HTS uptake (RR: 1.80, 95% CI [1.05, 3.08], p < 0.05; I2 = 0%; RD: 0.05, 95% CI [−0.06, 0.16], p = 0.407; I2 = 78.1%) (Figs 3 and 4 and S7 Appendix) with medium risk of bias. Six RCTs could not be pooled because of heterogeneity of interventions or lack of count data [73–76,81,82].

Yield.

Two RCTs reflecting three regions reported on the effect of HIV-specific information and counseling message interventions on HTS yield [79,95]. A meta-analysis showed HIV-specific information and counseling messages did not significantly impact yield (RR: 1.02, 95% CI [0.56, 1.87], p = 0.945; I2 = 0%; RD: 0.00, 95% CI [−0.00, 0.00], p = 0.925; I2 = 0%) (Fig 5 and S7 Appendix). This estimate may be biased due to at least 1 zero count in the numerator.

Couple-oriented counseling

Four RCTs [84–87] reported on couple-oriented counseling. Three studies were done in Africa [85–87] and 1 in East Asia [84]. One RCT focused on male partners of pregnant women [87], 1 focused on MSM [84], and 2 on heterosexual couples [85,86] (Table 1).

Uptake.

Four RCTs [84–87] reported on HTS uptake following couple-oriented counseling. A meta-analysis of 2 of these studies showed couple-oriented counseling significantly and importantly increased HTS uptake compared with standard HTS (RR: 1.98, 95% CI [1.02, 3.86], p < 0.12; I2 = 97.3%; RD: 0.12, 95% CI [0.03, 0.21], p < 0.05; I2 = 91.0%) (Figs 3 and 4 and S7 Appendix) with medium risk of bias.

In subgroup analyses by region, the effect of couple-oriented counseling was most pronounced in 1 trial from the European region (RR: 21.91) and reasonably comparable across the other regions (RR: 1.80, 1.14, 1.33, 1.23). In subgroup analyses by sex, the effect of couple-oriented counseling was reasonably comparable between trials that included men alone (RR: 2.12) and trials that included men and women (RR: 1.84) (S4 Appendix).

Yield.

Two RCTs reported on the effect of couple-oriented counseling on HTS yield [84,85]. A meta-analysis showed that couple-oriented counseling did significantly and importantly increase yield (RR: 2.74, 95% CI [1.29, 5.80], p < 0.05; I2 = 81.5%; RD: 0.10, 95% CI [0.03, 0.17], p < 0.05; I2 = 65.2%) (Fig 5 and S7 Appendix). It was not possible to explore heterogeneity through subgroup analyses because only 2 trials reported yield.

Message content/framing

Twelve RCTs examined the role of message framing or specific content [33,88–91,93–98] (Table 1). Four studies were in Africa [33,90,93,97], 2 were in Europe [89,94], 3 were in the Americas [88,91,92], and 3 were in Asia [95,96,98]. Four focused on general population adults [33,90,95,96], 1 focused on high-risk individuals [89], 2 focused on general population men [93,97], 3 on general population women [88,91,92], and 2 focused on MSM [94,98]. None of the 12 RCTs could be pooled due to intervention heterogeneity. Trials compared framings such as community versus individual benefits [33], gain versus loss framing [88], motivational versus informational messages [90], risk-related versus risk agnostic framing [94], positive versus avoidance framing [98], and behavioral insights and priming [89], among others.

Motivation-oriented messages and counseling

Four RCTs examined the role of motivational messages and counseling [99–102] (Table 1). Two trials were from Africa [101,102], 1 was from the United States [100], and 1 was from France [99]. All 4 focused on adults with risk factors such as seeking STI services or taking pre-exposure prophylaxis (PrEP).

Uptake.

Three RCTs examined HTS uptake following motivation-oriented messages and counseling [99,100,102]. A meta-analysis of these studies showed motivation-oriented messages and counseling significantly and importantly increased HTS uptake (RR: 1.53, 95% CI [1.07, 2.20], p < 0.05; I2 = 22.1%; RD: 0.17, 95% CI [0.00, 0.34], p < 0.05; I2 = 54.1%) (Figs 3 and 4 and S7 Appendix) with medium risk of bias.

Reduced duration or intensity of counseling (non-inferiority)

Four RCTs examined the role of reduced duration counseling to improve uptake of HIV testing [103–106] (Table 1). All 4 were from the US; 2 focused on women [103,104] and 2 focused on PWID [105,106].

Uptake.

Three RCTs reporting on uptake were pooled [103,105,106]. A meta-analysis indicated reduced duration counseling has a similar effect on HTS uptake compared with longer duration counseling and information (RR: 0.99, 95% CI [0.85, 1.15], p = 0.933; I2 = 67.5%; RD: 0.00, 95% CI [−0.08, 0.09], p = 0.915; I2 = 72.9%) (Figs 3 and 4 and S7 Appendix), suggesting non-inferiority with low risk of bias. There were no differences between shorter intervals (Cohan and colleagues: 2- to 5-min versus 30-s counseling) [103]; multiple sessions and lengths (Edelman and colleagues: 4 sessions at 23 min each versus 2 sessions at 15 min each) [105]; and longer intervals (Merchant and colleagues: 60-min versus 34-min counseling) [106]. One RCT [104] could not be pooled due to intervention heterogeneity.

Digital

There were 39 RCTs that reported on the effect of digital interventions: 12 were video- or audio-based [54,81,107–116], 8 used social media [51,52,59,64,75,117–119], 5 used websites [54,55,94,120,121], 13 used SMS messaging [65,90,95,122–131], and 1 used gamification [132].

Video- or audio-based interventions

There were 12 RCTs that examined the role of video- or audio-based interventions [54,81,107–116] (Table 1). Ten were conducted in the Americas [54,57,81,107,109,111–115], 1 in Europe [113], and 1 in the Western Pacific (Hong Kong SAR) [116]. Five focused on general population adults [108,109,111–113], 4 among MSM [54,110,114,116], 1 among previously incarcerated adults on parole [107], and 2 among adolescents [81,115], the latter of which focused on transgender and non-binary adolescents.

Uptake.

A meta-analysis of 4 studies [54,108,110,114] showed video-based interventions did not significantly and did not importantly increase HTS uptake compared to HTS with text (RR: 1.21, 95% CI [0.87, 1.68], p = 0.269; I2 = 47.8%; RD: 0.01, 95% CI [−0.02, 0.05], p = 0.383; I2 = 30.5%) (Figs 3 and 4 and S7 Appendix) with medium risk of bias.

A meta-analysis of 2 RCTs [109,115] comparing video counseling with in-person counseling showed video-based counseling importantly but not significantly increased HTS uptake compared to in-person counseling (RR: 6.84, 95% CI [0.80, 58.69], p = 0.079; I2 = 96.9%; RD: 0.59, 95% CI [0.01, 1.17], p < 0.05; I2 = 98.6%) (Figs 3 and 4 and S7 Appendix) with medium risk of bias.

A meta-analysis of 3 RCTs [107,112,113] showed audio versus in-person or text did not significantly but did less importantly increase HTS uptake (RR: 1.27, 95% CI [0.68, 2.36], p = 0.454; I2 = 97.6%; RD: 0.03, 95% CI [−0.09, 0.15], p = 0.620; I2 = 88.4%) (Figs 3 and 4 and S7 Appendix) with medium risk of bias. It was not possible to explore heterogeneity with subgroup analyses due to a small number of trials.

Social media-based interventions

Eight RCTs [51,52,59,64,114,117–119] included a social media-based intervention (Table 1). Six were in the Americas [51,52,59,64,114,117] and 2 in Asia [118,119]. All focused on transgender women and/or MSM. Meta-analysis was not conducted, as there was only 1 RCT [117] that included a social media platform for delivering an intervention and had a control that did not include social media.

Website (non-social media)-based interventions

Five RCTs [54,55,94,120,121] included a website-based intervention that was not on social media (Table 1). Two were conducted in the Americas [54,55], 1 in Europe [94], and 2 in Asia [120,121]. All 6 focused on transgender women and/or MSM. Meta-analysis was not conducted, as there were no RCTs that included a website platform for delivering an intervention and had a control that did not include a website.

SMS

Thirteen RCTs [65,90,95,122–131] examined the effect of SMS (Table 1). Eight were conducted in Africa [90,122–125,127–129], 2 in the Americas [126,130], 2 in Asia [65,95], and 1 in Europe [131]. Four focused on general population adults [90,95,127,130], 1 focused on general population men [123], 3 focused on individuals considered to be at high risk including female sex workers and truck drivers [122,124,126], 2 on MSM [65,126], 2 on young people in university [128,129], and 1 on both adolescents and adults [131].

Uptake.

A meta-analysis of 5 RCTs [90,95,122,126,127] showed SMS significantly and importantly increased HTS uptake (RR: 1.53, 95% CI [1.09, 2.16], p < 0.05; I2 = 93.1%; RD: 0.11, 95% CI [0.03, 0.19], p < 0.05; I2 = 90.2%) (Figs 3 and 4 and S7 Appendix) with medium risk of bias. Eight RCTs were not poolable [65,123–125,128–131]).

In subgroup analyses by region, the effect of SMS was most pronounced in 1 trial from the region of the Americas (RR: 4.82), followed by the Southeast Asian region (RR: 2.40), and finally in the African region (RR: 1.16) (S4 Appendix).

Yield.

Three RCTs [95,127,131] reported on yield following SMS compared to no SMS. A meta-analysis was not conducted as none of the studies identified any individuals living with HIV; the numerators were all zero counts.

Publication bias

Using Egger’s tests and funnel plots (S5 Appendix), we observed no evidence of publication bias for incentives (both uptake and yield), peer-led interventions (uptake), personalized letters (uptake), motivation-oriented counseling (uptake), reduced duration counseling (uptake), mobilization (yield), HIV counseling without economic empowerment (yield), and SMS (yield). However, there appeared to be evidence of publication bias for lottery incentives (uptake), mobilization (uptake), HIV counseling without economic empowerment (uptake), couples counseling (uptake), audio versus text formats (uptake), and SMS (uptake). Due to a small number of studies, publication bias could not be assessed for invitation letters (uptake), counseling with economic empowerment (uptake), video versus in-person formats (uptake), peer-led interventions (yield), and couples counseling (yield).

We present trim-and-fill adjusted RR estimates for yield and uptake in S6 Appendix. Adjusted RR estimates generally did not differ substantially from unadjusted estimates, with the following exceptions; the association of mobilization with uptake was attenuated (unadjusted RR: 2.01 versus adjusted RR: 1.79) and with yield was attenuated (unadjusted RR: 1.67 versus adjusted RR: 1.18); the association of peer-led interventions with uptake was attenuated (unadjusted RR: 1.57 versus adjusted RR: 1.42) and with yield was enhanced (unadjusted RR: 0.86 versus RR: 1.06); the association of general counseling with yield was reversed and enhanced (unadjusted RR: 1.02 versus adjusted RR: 0.85); the association of couples counseling and yield was enhanced (unadjusted RR: 2.74 versus adjusted RR: 3.89); the association of motivational interviewing and uptake was attenuated (unadjusted RR: 1.53 versus adjusted RR: 1.21); the association of video versus text counseling and uptake was attenuated (unadjusted RR: 1.21 versus adjusted RR: 1.09) and between video versus in-person and uptake was attenuated (unadjusted RR: 6.84 versus adjusted RR: 2.32); the association of SMS and uptake was attenuated (unadjusted RR: 1.53 versus adjusted RR: 1.23).

Discussion

In this large systematic review and meta-analysis assessing strategies to increase demand for HTS, we found that mobilization, couple-oriented counseling, peer-led interventions, motivation-oriented counseling, SMS, and conditional fixed value incentives all significantly and importantly (≥50% increase) increased HTS uptake. Lottery-based incentives and audio-based interventions less importantly (25% to 49% increase) but not significantly increased HTS uptake. Personal invitation letters and personalized message content significantly but not importantly (<25% increase) increased HTS uptake. Reduced duration counseling had comparable performance to standard duration counseling and video-based interventions were comparable or better than in-person counseling. Pooled estimates reflected trials with an average medium risk of bias, limiting the strength of conclusions drawn. Finally, message framing, social media interventions, website-based interventions, and gamification had no pooled estimates of effect due to heterogeneity in interventions or lack of a control group without some version of the intervention.

Our findings are similar to other systematic reviews of demand creation interventions for VMMC and family planning, supporting the use of incentives, mobilization, and interpersonal communication with or without peer involvement. One systematic review of demand generation strategies for VMMC highlighted that financial incentives produced the largest relative improvements and were most acceptable, followed by multicomponent mobilization efforts including education, counseling, and influencers [133]. A separate systematic review delving into different types of incentives for VMMC identified that fixed-value financial incentives were effective, while lottery-based incentives were not [134]. A third recent review echoed the prior findings, noting that conditional cash incentives and food or transport vouchers were especially effective and acceptable and that lottery incentives and gifts and subsidies were not effective for VMMC [135]. A systematic review of demand generation strategies for family planning and contraception observed that demand generation activities—including community- and facility-based interventions, financial incentives, and mass media—were associated with increased uptake of family planning; they noted that financial incentives in particular were effective [136]. A separate systematic review of family planning strategies observed that demand generation interventions like mass media and interpersonal communication, peer-led interpersonal communication, incentives, and savings groups increased utilization of family planning services [137]. Similar to family planning, demand creation may be especially important for HTS when new products are introduced in a particular setting, such as the introduction of HIV self-tests [138].

We found that mobilization efforts increase HTS uptake. Mobilization may be particularly well suited to settings and time periods where overall coverage of HTS is lower, motivating large groups within a community to take up testing by shifting the acceptability of HTS. However, as different settings approach the first 95 of the UNAIDS 95-95-95 goals in a particular population, the remaining untested individuals will be systematically different from those tested previously. Interventions that have been previously successful to motivate testing early in a population—such as mobilization—may have diminishing returns over time. This may require either tailoring to subpopulations—including key populations and their partners—or replacement with other targeted demand creation interventions. Pairing demand creation models with additional theoretical insights—such as those from the diffusion of innovations theory—may allow for more thoughtful and effective tailoring of demand creation strategies as HIV testing approaches saturation in a given population. For example, peer-led interventions had an important and significant pooled effect and most of the individual trials focused on transgender populations and men who have sex with men. This is an area for prioritization that serves priority populations and may be a focused alternative to broad and unfocused mobilization.

Provision of information and counseling messages continue to be important; we found evidence that couples counseling and motivation-oriented counseling approaches are effective. Couples counseling is effective and widespread in many contexts [139]; motivation-oriented counseling is less broadly scaled and may merit further expansion; economic empowerment interventions may have broad reaching effects beyond HTS [140]. However, individualized messaging—both personalized messages and personal invitation letters—had minimal impact on uptake of HTS and may be considered for de-prioritization.

While incentives were found to be effective in our review and others, and acceptable to end users and health care workers [141,142], acceptability to policymakers and implementers may be limited based on affordability and concerns related to longer-term sustainability. Concerns exist about erosion of intrinsic motivation for testing, although the limited data that exist do not support this concern [143].

This review highlighted a wide range of digital interventions, with substantial heterogeneity in both intervention design, impact, and gaps in the evidence related to effectiveness. Generally, older technology—such as videos and SMS—had more available evidence supporting effectiveness, while newer technology—including websites and social media and gamification—had less available evidence. This review included individual studies about social media and website-based interventions; however, we were unable to pool results due to the small number of studies with an adequate control for comparison. A 2018 review of digital interventions explored multiple attributes of digital interventions—including modality, directionality, tailoring, phrasing, and schedule—to identify what makes a digital intervention work [144].

SMS was effective for enhancing uptake of HTS in this review; a related systematic review of strategies to promote frequent HIV retesting demonstrated that SMS was effective [145]. Like other digital platforms, SMS in and of itself is less characteristic of an intervention and more a platform to deliver information or an intervention. mHealth and eHealth literature has demonstrated that reminder SMS messages are relatively ineffective, but SMS that deliver motivational or informational content or theory-informed content is more effective, particularly SMS platforms that offer interactive instead of one-way communication [146,147]. In this review, included studies ranged in their content and format; de Tolly and colleagues tested different numbers of messages and either motivational or informational content, Nuwamanya and colleagues tested an interactive mobile phone app and Yun and colleagues linked to interactive content on a website through text messages, Salvadori and colleagues sent appointment reminders, and several studies tested informational messages without interaction, which the literature suggests are least likely to produce a desired health action.

This review offered 2 opportunities for enhancing the efficiency of HTS in the face of limited resources while maintaining uptake. We did not detect any differences in the effectiveness of shorter versus longer counseling sessions; additionally, video-based information was as effective (and possibly more effective based on effect size) than in-person counseling sessions. Creation of videos may be expensive, but the one-time costs of creating a video are borne upfront with limited costs for continued use; additionally, crowdsourcing development of messaging could increase affordability. Videos offer a range of benefits for resource-limited settings: videos can be displayed in waiting rooms or on individual tablets, accommodating a range of existing infrastructure contexts; videos can be translated to different languages; offer consistent and accurate information; can be updated more rapidly than large numbers of health care workers can be trained; and can be time-saving for health care workers to shift from providing standardized pre-test information to providing individualized post-test counseling. In the era of Coronavirus Disease 2019 (COVID-19), video-based services have increased in prevalence and reach. Reducing length and intensity of counseling or shifting to a video format may make HTS implementation more feasible in many settings, particularly in contexts with flat or decreasing budgets for HTS.

This review is the largest and most comprehensive systematic review of demand creation for HTS. Its interim findings were used to inform the WHO 2019 HTS guidelines to direct global policy and this updated review was utilized in the 2023 HTS guidelines to provide better guidance on best practices. This large body of literature from the field of HIV may also be applicable to generating demand for testing services for other disease areas, serving as indirect evidence in guideline development [148].

This review was limited in several ways. It is possible that with a strict RCT string present in the search strategy, we missed some relevant RCTs; however, this Cochrane string has been well validated, and the number of citations identified without this string would have been unfeasible to manage with consistent accuracy. By restricting to RCTs, we excluded potentially informative studies that utilize non-randomized study designs; often, these designs have higher external validity than RCTs, which can provide a more accurate understanding of real world effectiveness outside of ideal trial conditions. It was not feasible to include non-randomized designs in a review of this breadth, but future research on specific types of demand creation interventions should consider including non-randomized designs. Key populations may be underrepresented in this review. We restricted our meta-analysis and pooling to studies that were randomized trials and that had the intervention tested against a standard of care that did not include the intervention. This type of evidence may be systematically less readily available for key populations; for example, studies that utilized a digital component were more likely to be unpoolable because there was a digital intervention both in the intervention and control arms and digital interventions were also more likely to focus on transgender populations and men who have sex with men. Future reviews focusing on key populations and demand creation should consider including study designs beyond randomized trials and to include gray literature. Finally, a substantial number of meta-analyses demonstrated evidence of publication bias, including 3 interventions we concluded had both an important and significant impact on HTS, including mobilization, couples counseling, and SMS. It is possible that if publication bias were not present, these interventions would not be concluded as impactful and recommended in this review.

Our meta-analyses pooled approximately half of studies included in this systematic review; categories of demand creation interventions represented by a single study were included and reported in this review, but not compared directly to the pooled estimates, nor categorized by effect size or statistical significance. Additionally, many studies tested multicomponent interventions, which are not reflected well in this type of meta-analysis; we aimed to identify the largest component of each intervention and group the trials accordingly. Review platforms that intentionally enumerate all components of an intervention or strategy and pool accordingly may reflect this nuance more precisely [149]. The quantitative pooling approach of a meta-analysis using relative risks, a relative measure, and pooled risk differences that are agnostic to HTS coverage in control groups makes it less possible to assess how the impact of interventions varies across settings with differing coverage of HTS among populations and regions. Similarly, statistical heterogeneity of effect and heterogeneity of intervention were both strongly present in this review across many intervention areas. We have provided estimates of statistical heterogeneity of effect, which appeared predominantly due to heterogeneity of setting and with context-specific details provided in data tables. This heterogeneity may make it more challenging for implementers to select context-relevant evidence; future reviews may consider making use of context heterogeneity present across trials to be informative using transportability principles [150].

Estimates of yield of testing can be considered either among the full denominator randomized or those tested. Using the full denominator randomized preserves the benefits of randomization but may combine the mixed effect of uptake and underlying prevalence; using the denominator of those tested loses the benefits of randomization but isolates the effect of prevalence among the tested population. We presented results using the full randomized denominators to preserve the benefits of randomization. Finally, the risk of bias across the included trials was medium, which weakens the strength of inference drawn. All trials were marked down in alignment with Cochrane guidance for lack of blinding of participants to their intervention arm; however, this is necessary for any demand creation intervention to have an effect and may be an artificially large mark down for this body of literature.

This large systematic review and meta-analysis provides evidence for several demand creation strategies to increase uptake of HTS. Conditional fixed value incentives, mobilization, couple-oriented counseling, motivation-oriented counseling, and SMS all significantly and importantly (≥50% increase) increased HTS uptake. Reduced duration counseling and video-based counseling can increase efficiency without reducing uptake. These specific demand creation interventions should be prioritized for programmatic consideration alongside important risks and benefits, as well as context-specific factors.

Supporting information

S1 PRISMA checklist. Prisma checklist.

https://doi.org/10.1371/journal.pmed.1004169.s001

(DOCX)

S1 Appendix. Full search strategy in PubMed format.

https://doi.org/10.1371/journal.pmed.1004169.s002

(DOCX)

S2 Appendix. Meta-analysis methods.

https://doi.org/10.1371/journal.pmed.1004169.s003

(DOCX)

S3 Appendix. Geographic distribution of included trials.

Key and bar chart identify the total number of trials included from each country on the map. The rworldmap [cran.r-project.org] package in R was used to obtain the publicly available map (South A (2011). “rworldmap: A New R package for Mapping Global Data.” The R Journal, 3(1), 35–43. ISSN 2073-4859); the base layer map file can be found: https://code.google.com/archive/p/rworld/source/default/source.

https://doi.org/10.1371/journal.pmed.1004169.s004

(DOCX)

S4 Appendix. Subgroup analyses for meta-analyses with high statistical heterogeneity.

https://doi.org/10.1371/journal.pmed.1004169.s005

(DOCX)

S5 Appendix. Funnel plots and Egger’s tests to assess publication bias.

https://doi.org/10.1371/journal.pmed.1004169.s006

(DOCX)

S6 Appendix. Trim-and-fill adjusted estimates of uptake and yield.

https://doi.org/10.1371/journal.pmed.1004169.s007

(DOCX)

S7 Appendix. Risk difference plots.

https://doi.org/10.1371/journal.pmed.1004169.s008

(DOCX)

Acknowledgments

We thank the members of the WHO Guideline Development Group for their valuable input and insights during the process of developing this review. We thank Dr. Nandi Siegfried, independent methodologist, for her tremendous support and assistance in the completion of this review.

The views contained in this article are those of the authors and do not necessarily reflect the official views of the WHO, the US President’s Emergency Plan for AIDS Relief, the US Agency for International Development, or the US Government.

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