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      HIV treatment engagement in the context of COVID-19: an observational global sample of transgender and nonbinary people living with HIV

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          Abstract

          Background

          HIV services, like many medical services, have been disrupted by the COVID-19 pandemic. However, there are limited data on the impacts of the COVID-19 pandemic on HIV treatment engagement outcomes among transgender (trans) and nonbinary people. This study addresses a pressing knowledge gap and is important in its global scope, its use of technology for recruitment, and focus on transgender people living with HIV. The objective of this study is to examine correlates of HIV infection and HIV treatment engagement outcomes (i.e., currently on ART, having an HIV provider, having access to HIV treatment without burden, and remote refills) since the COVID-19 pandemic began.

          Methods

          We utilized observational data from the Global COVID-19 Disparities Survey 2020, an online study that globally sampled trans and nonbinary people ( n = 902) between April and August 2020. We conducted a series of multivariable logistic regressions with lasso selection to explore correlates of HIV treatment engagement outcomes in the context of COVID-19.

          Results

          Of the 120 (13.3%) trans and nonbinary people living with HIV in this survey, the majority (85.8%) were currently on HIV treatment. A smaller proportion (69.2%) reported having access to an HIV provider since COVID-19 control measures were implemented. Less than half reported being able to access treatment without burdens related to COVID-19 (48.3%) and having the ability to remotely refill HIV prescription (44.2%). After adjusting for gender in the multivariable models, younger age and anticipated job loss were significantly associated with not having access to HIV treatment without burden. Outcomes also significantly varied by geographic region, with respondents reporting less access to an HIV provider in nearly every region outside of South-East Asia.

          Conclusion

          Our results suggest that currently taking ART, having access to an HIV provider, and being able to access HIV treatment without burden and remotely refill HIV medication are suboptimal among trans and nonbinary people living with HIV across the world. Strengthening support for HIV programs that are well-connected to trans and nonbinary communities, increasing remote access to HIV providers and prescription refills, and providing socioeconomic support could significantly improve HIV engagement in trans and nonbinary communities.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12889-021-10977-5.

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          Most cited references26

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          An interactive web-based dashboard to track COVID-19 in real time

          In December, 2019, a local outbreak of pneumonia of initially unknown cause was detected in Wuhan (Hubei, China), and was quickly determined to be caused by a novel coronavirus, 1 namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The outbreak has since spread to every province of mainland China as well as 27 other countries and regions, with more than 70 000 confirmed cases as of Feb 17, 2020. 2 In response to this ongoing public health emergency, we developed an online interactive dashboard, hosted by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, Baltimore, MD, USA, to visualise and track reported cases of coronavirus disease 2019 (COVID-19) in real time. The dashboard, first shared publicly on Jan 22, illustrates the location and number of confirmed COVID-19 cases, deaths, and recoveries for all affected countries. It was developed to provide researchers, public health authorities, and the general public with a user-friendly tool to track the outbreak as it unfolds. All data collected and displayed are made freely available, initially through Google Sheets and now through a GitHub repository, along with the feature layers of the dashboard, which are now included in the Esri Living Atlas. The dashboard reports cases at the province level in China; at the city level in the USA, Australia, and Canada; and at the country level otherwise. During Jan 22–31, all data collection and processing were done manually, and updates were typically done twice a day, morning and night (US Eastern Time). As the outbreak evolved, the manual reporting process became unsustainable; therefore, on Feb 1, we adopted a semi-automated living data stream strategy. Our primary data source is DXY, an online platform run by members of the Chinese medical community, which aggregates local media and government reports to provide cumulative totals of COVID-19 cases in near real time at the province level in China and at the country level otherwise. Every 15 min, the cumulative case counts are updated from DXY for all provinces in China and for other affected countries and regions. For countries and regions outside mainland China (including Hong Kong, Macau, and Taiwan), we found DXY cumulative case counts to frequently lag behind other sources; we therefore manually update these case numbers throughout the day when new cases are identified. To identify new cases, we monitor various Twitter feeds, online news services, and direct communication sent through the dashboard. Before manually updating the dashboard, we confirm the case numbers with regional and local health departments, including the respective centres for disease control and prevention (CDC) of China, Taiwan, and Europe, the Hong Kong Department of Health, the Macau Government, and WHO, as well as city-level and state-level health authorities. For city-level case reports in the USA, Australia, and Canada, which we began reporting on Feb 1, we rely on the US CDC, the government of Canada, the Australian Government Department of Health, and various state or territory health authorities. All manual updates (for countries and regions outside mainland China) are coordinated by a team at Johns Hopkins University. The case data reported on the dashboard aligns with the daily Chinese CDC 3 and WHO situation reports 2 for within and outside of mainland China, respectively (figure ). Furthermore, the dashboard is particularly effective at capturing the timing of the first reported case of COVID-19 in new countries or regions (appendix). With the exception of Australia, Hong Kong, and Italy, the CSSE at Johns Hopkins University has reported newly infected countries ahead of WHO, with Hong Kong and Italy reported within hours of the corresponding WHO situation report. Figure Comparison of COVID-19 case reporting from different sources Daily cumulative case numbers (starting Jan 22, 2020) reported by the Johns Hopkins University Center for Systems Science and Engineering (CSSE), WHO situation reports, and the Chinese Center for Disease Control and Prevention (Chinese CDC) for within (A) and outside (B) mainland China. Given the popularity and impact of the dashboard to date, we plan to continue hosting and managing the tool throughout the entirety of the COVID-19 outbreak and to build out its capabilities to establish a standing tool to monitor and report on future outbreaks. We believe our efforts are crucial to help inform modelling efforts and control measures during the earliest stages of the outbreak.
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            Regression Shrinkage and Selection Via the Lasso

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              The Socio-Economic Implications of the Coronavirus and COVID-19 Pandemic: A Review

              The COVID-19 pandemic has resulted in over 1.4 million confirmed cases and over 83,000 deaths globally. It has also sparked fears of an impending economic crisis and recession. Social distancing, self-isolation and travel restrictions forced a decrease in the workforce across all economic sectors and caused many jobs to be lost. Schools have closed down, and the need of commodities and manufactured products has decreased. In contrast, the need for medical supplies has significantly increased. The food sector has also seen a great demand due to panic-buying and stockpiling of food products. In response to this global outbreak, we summarise the socio-economic effects of COVID-19 on individual aspects of the world economy.
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                Author and article information

                Contributors
                arestar1@jhmi.edu
                Journal
                BMC Public Health
                BMC Public Health
                BMC Public Health
                BioMed Central (London )
                1471-2458
                12 May 2021
                12 May 2021
                2021
                : 21
                : 901
                Affiliations
                [1 ]GRID grid.21107.35, ISNI 0000 0001 2171 9311, Department of Epidemiology, , Johns Hopkins School of Public Health, ; 615 N Wolfe St, Baltimore, MD 21205 USA
                [2 ]GRID grid.21107.35, ISNI 0000 0001 2171 9311, Department of Health, Policy, and Management, , Johns Hopkins School of Public Health, ; Baltimore, MD USA
                [3 ]GRID grid.261112.7, ISNI 0000 0001 2173 3359, School of Law and School of Criminology and Criminal Justice, , Northeastern University, ; Boston, MA USA
                [4 ]GRID grid.453330.2, ISNI 0000 0004 0421 2203, amfAR, The Foundation of AIDS Research, ; Washington, DC USA
                [5 ]Hornet, San Francisco, CA USA
                [6 ]GRID grid.21107.35, ISNI 0000 0001 2171 9311, Department of Health, Behavior, and Society, , Johns Hopkins School of Public Health, ; Baltimore, MD USA
                [7 ]GRID grid.21107.35, ISNI 0000 0001 2171 9311, Department of International Health, , Johns Hopkins School of Public Health, ; Baltimore, MD USA
                Article
                10977
                10.1186/s12889-021-10977-5
                8114659
                33388037
                1f14bdf2-1185-4739-a870-ee45f0aa5fdc
                © The Author(s) 2021

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 8 January 2021
                : 29 April 2021
                Categories
                Research
                Custom metadata
                © The Author(s) 2021

                Public health
                coronavirus,covid-19,transgender people living with hiv,hiv
                Public health
                coronavirus, covid-19, transgender people living with hiv, hiv

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