| Literature DB >> 32654021 |
Glenn-Milo Santos1,2, Benjamin Ackerman3, Amrita Rao4, Sara Wallach4, George Ayala5, Erik Lamontage6,7, Alex Garner8, Ian W Holloway9, Sonya Arreola5, Vince Silenzio10, Susanne Strömdahl11,12, Louis Yu13, Carol Strong14, Tyler Adamson4, Anna Yakusik6, Tran Thu Doan15, Poyao Huang16, Damiano Cerasuolo17, Amie Bishop18, Teymur Noori19, Anastasia Pharris19, Max Aung15, Masoud Dara20, Ssu Yu Chung21, Marguerite Hanley22, Stefan Baral4, Chris Beyrer4, Sean Howell21.
Abstract
There is an urgent need to measure the impacts of COVID-19 among gay men and other men who have sex with men (MSM). We conducted a cross-sectional survey with a global sample of gay men and other MSM (n = 2732) from April 16, 2020 to May 4, 2020, through a social networking app. We characterized the economic, mental health, HIV prevention and HIV treatment impacts of COVID-19 and the COVID-19 response, and examined whether sub-groups of our study population are disproportionately impacted by COVID-19. Many gay men and other MSM not only reported economic and mental health consequences, but also interruptions to HIV prevention and testing, and HIV care and treatment services. These consequences were significantly greater among people living with HIV, racial/ethnic minorities, immigrants, sex workers, and socio-economically disadvantaged groups. These findings highlight the urgent need to mitigate the negative impacts of COVID-19 among gay men and other MSM.Entities:
Keywords: AIDS; COVID-19; Economic impact; Gay; HIV; Men who have sex with men; Mental health
Mesh:
Year: 2021 PMID: 32654021 PMCID: PMC7352092 DOI: 10.1007/s10461-020-02969-0
Source DB: PubMed Journal: AIDS Behav ISSN: 1090-7165
Access to HIV Prevention and HIV Treatment among a Global Sample of Cisgender Gay Men and Other Men who have sex with Men (n = 2732)
| Access to HIV Prevention among HIV-negative participants (n = 2247) | Access to HIV Treatment among HIV-positive participants (n = 473) | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|
| Access to HIV provider | Access to HIV medication | ||||||||||
| Condoms | Onsite HIV test | HIV self-test | PEP☨ | PrEP☨ | Lost provider access | In-person provider access | Tele-medicine Provider access | Can refill/access | Can refill/access with complications | Cannot refill/access | |
| OVERALL | 1459 (65%) | 679 (30%) | 429 (19%) | 381 (17%) | 470 (21%) | 111 (23%) | 204 (43%) | 79 (17%) | 350 (77%) | 64 (14%) | 20 (4%) |
| Stratified by Sub-populations | |||||||||||
| Yes | 248* (62%) | 124 (31%) | 68* (17%) | 66 (17%) | 79 (20%) | 23 (26%) | 32 (36%) | 17 (19%) | 57* (70%) | 13* (16%) | 7* (9%) |
| No | 1088* (68%) | 495 (31%) | 313* (20%) | 278 (17%) | 346 (22%) | 81 (24%) | 148 (43%) | 57 (17%) | 270* (81%) | 41* (12%) | 9* (3%) |
| Don’t know/refuse | 120* (50%) | 60 (25%) | 48* (20%) | 37 (15%) | 44 (18%) | 7 (17%) | 23 (56%) | 5 (12%) | 23* (61%) | 10* (26%) | 4* (11%) |
| Test stat. (p-value) | 37.1*(< 0.01) | 6.1 (0.63) | 16.7*(0.03) | 8.4 (0.39) | 3.6 (0.89) | 4.3 (0.37) | NA* (0.004) | ||||
| Parents native-born | 1047* (67%) | 479 (30%) | 300 (19%) | 274 (17%) | 321 (20%) | 86 (24%) | 159 (45%) | 55 (16%) | 276* (80%) | 44* (13%) | 11* (3%) |
| First generation | 100* (63%) | 42 (26%) | 27 (17%) | 25 (16%) | 41 (26%) | 4 (19%) | 8 (38%) | 6 (29%) | 16* (80%) | 3* (15%) | NA |
| Immigrant | 228* (61%) | 116 (31%) | 78 (21%) | 63 (17%) | 82 (22%) | 16 (22%) | 23 (32%) | 12 (17%) | 42* (63%) | 13* (19%) | 6* (9%) |
| Test stat. (p-value) | 25.7*(0.01) | 5.7 (0.68) | 4.8 (0.78) | 5.8 (0.67) | 3.5 (0.90) | NA (0.48) | NA* (0.02) | ||||
| Government Insurance | 615 (66%) | 274 (30%) | 188 (20%) | 156 (17%) | 192 (21%) | 56* (26%) | 87* (41%) | 34* (16%) | 158 (76%) | 32 (15%) | 9 (4%) |
| No Insurance | 182 (63%) | 85 (30%) | 62 (22%) | 52 (18%) | 57 (20%) | 15* (37%) | 20* (49%) | 2* (5%) | 28 (68%) | 7 (17%) | 5 (12%) |
| Other Insurance | 637 (65%) | 304 (31%) | 171 (17%) | 168 (17%) | 210 (21%) | 38* (19%) | 90* (45%) | 40* (20%) | 155 (79%) | 24 (12%) | 5 (3%) |
| Test stat. (p-value) | 5.7 (0.68) | 8.0 (0.43) | 13.0 (0.11) | 11.0(0.20) | 11.7 (0.17) | 10.1* (0.04) | NA (0.20) | ||||
| Yes | 119* (56%) | 74 (35%) | 47* (22%) | 46 (22%) | 51 (24%) | 24* (39%) | 22* (36%) | 7* (11%) | 40* (71%) | 7* (12%) | 7* (12%) |
| No | 1243* (67%) | 559 (30%) | 356* (19%) | 316 (17%) | 395 (21%) | 84* (23%) | 164* (44%) | 65* (18%) | 286* (79%) | 50* (14%) | 10* (3%) |
| Don’t know/refuse | 54* (61%) | 17 (19%) | 11* (12%) | 13 (15%) | 11 (12%) | NA | 7* (44%) | 3* (19%) | 8* (57%) | 5* (36%) | 1* (7%) |
| Test stat. (p-value) | 15.6*(0.048) | 12.7(0.12) | 18.5*(0.02) | 8.9 (0.35) | 11.9 (0.15) | NA* (0.01) | NA* (0.001) |
Test stat. = Test statistic for Chi-square test if value is provided, and NA for Fisher’s exact test
*Denotes p-value < 0.05 from Chi-Squared or Fisher’s Exact Test
☨Responses denote participant selected they feel that they “Definitely have access” to prevention resource out of a 5-point scale. Statistical testing compares “Definite Yes” response to other possible responses on scale