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Gay and bisexual men are 26 times more likely to acquire HIV than other adult men and represent nearly 1 in 4 new HIV infections worldwide. There is concern that the COVID-19 pandemic may be complicating efforts to prevent new HIV infections, reduce AIDS-related deaths, and expand access to HIV services. The impact of the COVID-19 pandemic on gay and bisexual men’s ability to access services is not fully understood.
The aim of this study was to understand access to HIV services at the start of the COVID-19 pandemic.
Our study used data collected from two independent global online surveys conducted with convenience samples of gay and bisexual men. Both data sets had common demographic measurements; however, only the COVID-19 Disparities Survey (n=13,562) collected the outcomes of interest (HIV services access at the height of the first COVID-19 wave) and only the Global Men’s Health and Rights Survey 4 (GMHR-4; n=6188) gathered pre-COVID-19 pandemic exposures/covariates of interest (social/structural enablers of and barriers to HIV services access). We used data fusion methods to combine these data sets utilizing overlapping demographic variables and assessed relationships between exposures and outcomes. We hypothesized that engagement with the gay community and comfort with one’s health care provider would be positively associated with HIV services access and negatively associated with poorer mental health and economic instability as the COVID-19 outbreaks took hold. Conversely, we hypothesized that sexual stigma and experiences of discrimination by a health care provider would be negatively associated with HIV services access and positively associated with poorer mental health and economic instability.
With 19,643 observations after combining data sets, our study confirmed hypothesized associations between enablers of and barriers to HIV prevention, care, and treatment. For example, community engagement was positively associated with access to an HIV provider (regression coefficient=0.81, 95% CI 0.75 to 0.86;
HIV services access for gay and bisexual men remained obstructed and perhaps became worse during the first wave of the COVID-19 pandemic. Community-led research that utilizes novel methodological approaches can be helpful in times of crisis to inform urgently needed tailored responses that can be delivered in real time. More research is needed to understand the full impact COVID-19 is having on gay and bisexual men worldwide.
Gay men and other men who have sex with men (MSM; hereafter referred to as gay and bisexual men) [
The world remains off track in meeting global HIV targets, especially for socially marginalized and criminalized groups. For example, surveys from 114 nationally representative data sets in 38 African countries with nearly 1.5 million sexually active adults aged 15-49 years conducted from 2003 to 2018 were examined to estimate trends in annual HIV testing and condom use during the last occurrence of highest-risk sex. These data were used to calculate the probability of reaching key Joint United Nations Programme on HIV/AIDS (UNAIDS) targets. Investigators observed limited progress and little chance of reaching global targets [
More evidence is needed for providing early and potentially critical programmatic and policy-related interventions in the era of COVID-19. This study utilized a statistical matching method that combined data sets (ie, data fusion) from two separate global online cross-sectional surveys to enable drawing inferences about the impact of the COVID-19 pandemic on gay and bisexual men’s ability to access services. Neither data set could address the question individually, as one had only outcomes and demographics and the other only exposures and demographics. Data fusion allowed us to relate outcomes to exposures across the data sets. Specifically, this approach allowed us to explore social and structural enablers of and barriers to HIV service access among gay and bisexual men worldwide during the early days of the COVID-19 pandemic. We hypothesized that engagement with the gay community and comfort with one’s health care provider would be positively associated with HIV services access and negatively associated with poorer mental health and economic instability despite the challenges brought about by COVID-19 outbreaks. Conversely, we hypothesized that sexual stigma and experiences of discrimination by a health care provider would be negatively associated with HIV services access and positively associated with poorer mental health and economic instability.
Our hypotheses are informed by social ecological theory, which suggests that various factors at structural, community, interpersonal, and individual levels facilitate or impede access to resources such as HIV and other health services. Social ecological theory is useful for identifying high-impact leverage points in the successful implementation of health-promoting interventions and for strategic alignment of policy and services across a continuum of population health needs [
Our study used data collected from two independent surveys conducted with gay and bisexual men. The first, Global Men’s Health and Rights Survey 4 (GMHR-4), was designed to explore correlates to HIV services access and utilization. GMHR-4 was launched on September 4, 2019, and closed on March 31, 2020 [
The second survey, COVID-19 Disparities Survey, was administered by Hornet between April 16, 2020, through May 4, 2020 [
Ethical approval for the use of GMHR-4 data was obtained from the Western Institutional Review Board, which determined that GMHR-4 was exempt under 45 CFR 46.104(d)(2) (#1-1174358-1). Study procedures for the COVID-19 Disparities Survey were reviewed by the Johns Hopkins School of Public Health Institutional Review Board, which designated the protocol as exempt under Category 4.
Both surveys included
The COVID-19 Disparities Survey asked participants about the impact COVID-19 was having on their economic situation; mental health; and ability to access HIV testing, prevention, care, and treatment services.
HIV services impact measures asked whether participants experienced changes in
Venn diagram of Global Men’s Health and Rights Survey 4 (GMHR-4) and COVID-19 Disparities survey measures used for data fusion analysis. Demographic measures that overlap between the two studies' samples include: age, country of residence, sexual orientation, gender identity, relationship status, racial/ethnic minority status, ability to meet one’s basic financial needs, health care coverage, and HIV status.
Because we were examining data from two different surveys with only partial variable overlap (demographics in both data sets, exposures in one data set, and outcomes in the other data set), and we were interested in associations between nonoverlapping variables across these questionnaires, we utilized statistical matching (ie, data fusion) methods to combine the data sets [
To make an initial informed estimate of the partial correlations between the outcomes from the COVID-19 Disparities Survey data set and the GMHR-4 predictors in the imputation prediction regression models, we calculated the partial correlations between each of the GMHR-4 predictors with the measure that we believed was the closest proxy to each of the outcomes in the COVID-19 data set, while accounting for the jointly observed demographic characteristics (income, education, relationship status, urbanicity [urban vs rural], racial/ethnic minority status, health insurance, and region [Global North vs Global South]). For example, we calculated the partial correlation between the exposure, community engagement, and access to HIV testing in the GMHR-4 data set, while accounting for the jointly observed demographic variables. We then used this partial correlation value in the prediction model for community engagement and the outcome of access to HIV testing during COVID-19 in the COVID-19 Disparities Survey data set. That is, we assumed that the partial correlation between community engagement and access to HIV testing in GMHR-4 was a reasonable approximation for the partial correlation between community engagement in GMHR-4 and access to HIV testing during COVID-19 in the COVID-19 Disparities Survey data set. The range of partial correlations used in the fusion procedure included this initial informed estimate, ±5%, and ±10%.
For each partial correlation value and resulting fused data set, we then performed linear regressions between the imputed outcomes and exposures [
A total of 19,643 observations from gay and bisexual men were included in this study after combining outcomes from the GMHR-4 (n=6189) with exposures from the COVID-19 Disparities Survey (n=13,454) through overlapping demographics via data fusion (see
Participant demographic characteristics jointly observed across both data sets.
Characteristics | Totala (N=19,643), n (%) | GMHR-4b (n=6189), n (%) | COVID-19 Disparities (n=13,454), n (%) | |
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<20 | 1287 (6.55) | 537 (8.68) | 750 (5.57) |
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20-29 | 7234 (36.83) | 2687 (43.42) | 4547 (33.80) |
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30-49 | 9240 (47.04) | 2528 (40.85) | 6712 (49.89) |
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50+ | 1878 (9.56) | 433 (7.00) | 1445 (10.74) |
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Not able to meet needs well | 11,275 (57.40) | 3982 (64.34) | 7293 (54.21) |
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Able to meet needs well | 8368 (42.60) | 2207 (35.66) | 6161 (45.79) |
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Did not complete college | 9031 (45.98) | 1553 (25.09) | 7478 (55.58) |
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Completed college | 10,612 (54.02) | 4636 (74.91) | 5976 (44.42) |
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In a relationship | 5725 (29.15) | 1673 (27.03) | 4052 (30.12) |
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Not in a relationship | 13,918 (70.85) | 4516 (72.97) | 9402 (69.88) |
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Not in a city/urban area | 4070 (20.72) | 831 (13.43) | 3239 (24.07) |
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Resides in a city/urban area | 15,573 (79.28) | 5358 (86.57) | 10,215 (75.93) |
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Not a racial or ethnic minority | 16,117 (82.05) | 4733 (76.47) | 11,384 (84.61) |
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Racial or ethnic minority | 3526 (17.95) | 1456 (23.53) | 2070 (15.39) |
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No | 5398 (27.48) | 1908 (30.82) | 3490 (25.94) |
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Yes | 14,245 (72.52) | 4281 (69.17) | 9964 (74.06) |
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Global South | 9671 (49.23) | 5563 (89.89) | 4108 (30.53) |
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Global North | 9741 (49.59) | 598 (9.66) | 9143 (67.96) |
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Not living with HIV | 17,194 (87.53) | 5173 (83.58) | 12,021 (89.35) |
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Living with HIV | 2449 (12.47) | 1016 (16.42) | 1433 (10.65) |
aValues may not necessarily add to column totals due to missing responses from participants.
bGMHR-4: Global Men’s Health and Rights Survey 4.
Partial correlations between each GMHR-4 predictor with the measure that we believed represented the closest proxy to each of the outcomes in the COVID-19 data set were calculated and are presented in
Partial correlations between Global Men’s Health and Rights Survey 4 (GMHR-4) predictor and GMHR-4 proxy measures for COVID-19 outcome variablesa.
Predictors | HIV testing | Condoms | PrEPb | Access to HIV provider | Access to ARTc refills | Low income | Poor mental health |
Community engagement | 0.08 | 0.05 | 0.13 | 0.11 | 0.11 | 0.02 | –0.06 |
Comfort with provider | 0.21 | 0.19 | 0.25 | 0.26 | 0.26 | –0.17 | –0.15 |
Sexual stigma | –0.15 | –0.19 | –0.21 | –0.21 | –0.18 | 0.17 | 0.15 |
Provider discrimination | –0.07 | –0.08 | –0.06 | –0.05 | –0.04 | 0.09 | 0.10 |
aValues calculated for partial correlations were used as anchors for the range of partial correlations used in smpc and smmatch, with the range set at ±5% and ±10% of values.
bPrEP: pre-exposure prophylaxis.
cART: antiretroviral therapy.
Although sexual stigma was commonly reported by study participants (mean 3.53, SD 0.61), discrimination from one’s health care provider was low (mean 1.14, SD 0.39). Comfort with one’s provider was also frequently reported (mean 2.98, SD 1.25). Our study found poor community engagement, as evidenced by a low mean score (mean 1.32, SD 0.43).
Study participants reported relatively high access to HIV testing (mean 3.7, SD 0.43) and condoms (mean 4.6, SD 0.9), but suboptimal access to PrEP (mean 3.2, SD 1.4). Our study confirmed hypothesized associations between enablers of and barriers to HIV prevention. Community engagement and comfort with one’s health care provider were positively associated with access to HIV testing, condoms, and PrEP. Conversely, sexual stigma and experiences of provider discrimination were negatively associated with access to the same set of prevention services. Associations were statistically significant (
Associations between hypothesized predictors and access to HIV preventiona.
Predictors | HIV onsite testing access | Condom access | PrEPb access | |||||||
|
Coefc | 95% CI | Coef | 95% CI | Coef | 95% CI | ||||
Community engagement | 1.16 | 1.14 to 1.18 | <.001 | 0.95 | 0.92 to 0.99 | <.001 | 1.23 | 1.16 to 1.30 | <.001 | |
Comfort with provider | 0.78 | 0.77 to 0.79 | <.001 | 0.69 | 0.68 to 0.70 | <.001 | 0.90 | 0.89 to 0.91 | <.001 | |
Sexual stigma | –0.86 | –0.87 to-0.84 | <.001 | –1.05 | –1.08 to –1.02 | <.001 | –1.05 | –1.07 to –1.03 | <.001 | |
Provider discrimination | –0.96 | –1.01 to –0.92 | <.001 | –0.81 | –0.84 to –0.77 | <.001 | –1.17 | –1.19 to –1.14 | <.001 |
aRegression models also adjusted for income, education, relationship status, urbanicity (urban vs rural), racial/ethnic minority status, health insurance, and region (Global North vs Global South) as covariates. In sensitivity analyses omitting urbanicity and region, results were similar with respect to magnitude and level of significance of estimates.
bPrEP: pre-exposure prophylaxis.
cCoeff: regression coefficient.
Our study found access to HIV care (mean 2.4, SD 0.8) and HIV treatment (mean 2.1, SD 1.2) to be low. Enablers of and barriers to HIV care and treatment were significantly associated in the predicted directions. For example, community engagement was positively associated with access to an HIV provider and sexual stigma was negatively associated with access to HIV treatment. A detailed summary of associations is presented in
Associations between hypothesized predictors and access to HIV care and treatmenta.
Predictors | HIV provider access | Access to ARTb refills | ||||
|
Coefc | 95% CI | Coef | 95% CI | ||
Community engagement | 0.81 | 0.75 to 0.86 | <.001 | 1.23 | 1.19 to 1.27 | <.001 |
Comfort with provider | 0.54 | 0.53 to 0.55 | <.001 | 0.79 | 0.78 to 0.80 | <.001 |
Sexual stigma | –0.87 | –0.95 to –0.78 | <.001 | –1.08 | –1.11 to –1.05 | <.001 |
Provider discrimination | –0.77 | –0.81 to –0.73 | <.001 | –1.13 | –1.17 to –1.09 | <.001 |
aRegression models also adjusted for income, education, relationship status, urbanicity (urban vs rural), racial/ethnic minority status, health insurance, and region (Global North vs Global South) as covariates. In sensitivity analyses omitting urbanicity and region, results were similar with respect to magnitude and level of significance of estimates.
bART: antiretroviral therapy.
cCoef: regression coefficient.
The mean PHQ-4 score was 4.7, indicative of prevalent depression and anxiety among respondents who were included in this study. Community engagement and comfort with one’s health care provider were each negatively associated with poorer mental health. However, poorer mental health outcomes were significantly associated with experiences of sexual stigma and provider discrimination (see
Associations between hypothesized predictors and poorer mental healtha.
Predictors | Poorer mental health (PHQ-4b) | ||
|
Coefc | 95% CI | |
Community engagement | –3.03 | –3.19 to –2.87 | <.001 |
Comfort with provider | –2.19 | –2.23 to –2.15 | <.001 |
Sexual stigma | 2.48 | 2.42 to 2.54 | <.001 |
Provider discrimination | 3.15 | 2.94 to 3.35 | <.001 |
aRegression models also adjusted for income, education, relationship status, urbanicity (urban vs rural), racial/ethnic minority status, health insurance, and region (Global North vs Global South) as covariates. In sensitivity analyses omitting urbanicity and region, results were similar with respect to magnitude and level of significance of estimates.
bPHQ-4: Patient Health Questionnaire-4.
cCoef: regression coefficient.
Although the mean score for the question assessing anticipated income reduction was low (2.4), the SD (3.6) suggests broad variability in participant responses. As displayed in
Associations between hypothesized predictors and economic instabilitya.
Predictors | Anticipated income reduction during COVID-19 | ||
|
Coefb | 95% CI | |
Community engagement | 0.84 | 0.74 to 0.93 | <.001 |
Comfort with provider | –0.65 | –0.65 to –0.64 | <.001 |
Sexual stigma | 0.74 | 0.73 to 0.75 | <.001 |
Provider discrimination | 0.89 | 0.85 to 0.92 | <.001 |
aRegression models also adjusted for income, education, relationship status, urbanicity (urban vs rural), racial/ethnic minority status, health insurance, and region (Global North vs Global South) as covariates. In sensitivity analyses omitting urbanicity and region, results were similar with respect to magnitude and level of significance of estimates.
bCoef: regression coefficient.
To our knowledge, this is the first community-led, HIV-related research study to systematically combine data sets via data fusion from two separate online surveys of gay and bisexual men. The strategy enabled us to compare variables that would otherwise not be comparable. Specifically, we could combine outcomes from one data set with exposures from the other data set with a fusion process through the overlap [
Our study suggests that experiences of sexual stigma and provider discrimination continue to be common and likely persist through the COVID-19 pandemic. In addition, despite low overall levels of engagement with the gay community, when reported, community engagement may be moderating the deleterious effects of sexual stigma and provider discrimination on mental health and economic security. This may be because communities are sources of information, safety, support, and affinity [
All exposures or predictors were assessed using scales contained in GMHR-4, based on data collected in the weeks and months prior to the pandemic. All outcomes were measured using items from the COVID-19 Disparities Survey. Although we cannot directly infer causal relationships between predictor and outcome variables, measures utilized asked COVID-19 Disparities Survey participants to consider COVID-19 in their responses, allowing us the unique opportunity to infer associations beyond the time parameters prescribed by GMHR-4. Our findings point to actionable factors that both enable and inhibit access to HIV services for gay and bisexual men in the COVID-19 era.
There are some study limitations that are important to mention. First, both the GMHR-4 and COVID-19 Disparities Survey utilized online convenience samples, recruited through networks of advocates, service providers, and online dating apps. The study is therefore subject to selection bias for gay and bisexual men who are connected through networks and for whom internet-based technologies are more easily available. Study participants may thus have greater access to information and motivation to respond to surveys. Based on the sociodemographic characteristics of the sample, participants may likely have been gay and bisexual men who were less affected by the negative consequences of the COVID-19 pandemic. Consequently, findings reported here may reflect an underestimation of the true magnitude of COVID-19’s impact. In addition, the COVID-19 Disparities Survey was conducted at different stages of the epidemic’s spread and the magnitude of national responses likely varied from country to country. Convenience sampling also violates the assumption of the data fusion method that the two data sets were drawn as simple random samples from the same population [
Despite these limitations, our study underscores the continued need to better understand and address impediments to service access among gay and bisexual men, especially in the context of the COVID-19 pandemic. Key strengths of this study include the range of domains used that can be harnessed for future research related to the HIV and COVID-19 pandemics and their impact on vulnerable populations. These include individual financial security, mental and sexual health, access to services, and program utilization. Moreover, the data sets used include samples from countries hardest hit by COVID-19, including Brazil, France, Mexico, and Russia.
Studies highlighting factors thought to enable access to HIV services are rare among gay and bisexual men [
Community-led research employing novel methodological approaches are paramount during times of crisis. The use of approaches such as data fusion to combine data sets can help to quickly clarify salient enabling factors rapidly and cost-efficiently, as well as expose the economic, mental health, and service impacts of sexual stigma and provider discrimination. Such information can potentially lead to tailored responses delivered in real time, which can be critically important during public health emergencies such as that represented by the COVID-19 pandemic. Community-led, methodologically creative, and cost-efficient approaches should be encouraged and funded, especially during such times.
Our study specifically highlights the importance of reinforcing enablers such as community engagement and comfort with one’s health care provider, while addressing stigma and discrimination as critically and equally central to ensuring equitable HIV services access among gay and bisexual men worldwide. Although not new, the findings reported here suggest that addressing factors that enable and deter access to HIV services may be especially important in buffering against the mental health and economic impacts of new and unrelated pandemics. Moreover, our study raises the question of whether the COVID-19 pandemic has resulted in worsening HIV services access among gay and bisexual men, a question that remains open and ready for further research. Future research is needed, including prospective studies of gay and bisexual men that more deeply examine the associations between exposures and outcomes of interest within the same sample. Future studies should also examine the concerns of gay and bisexual men more comprehensively, beyond those related to HIV, in a world transfixed and transformed by COVID-19.
Global Men’s Health and Rights Survey-4
men who have sex with men
Patient Health Questionnaire-4
pre-exposure prophylaxis
Joint United Nations Programme on HIV/AIDS
The authors deeply appreciate the teams at MPact Global Action for Gay Men's Health and Rights and Hornet. We would especially like to thank the thousands of participants in community-led survey efforts, such as those featured here. Finally, we recognize, with humility, the courage of sexual minority people worldwide, who put their lives and livelihoods on the line every day in their struggles for respect, dignity, and human rights. Human rights include the right to HIV and other sexual health services free from stigma and discrimination.
None declared.