Gender-affirming care, mental health, and economic stability in the time of COVID-19: a global cross-sectional study of transgender and non-binary people

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Abstract

Background

Transgender and non-binary people are disproportionately burdened by barriers to quality healthcare, mental health challenges, and economic hardship. This study examined the impact of the novel coronavirus disease (COVID-19) pandemic and subsequent control measures on gender-affirming care, mental health, and economic stability among transgender and non-binary people globally.

Methods

We collected global cross-sectional data from 964 transgender and non-binary adult users of the Hornet and Her apps from April to August 2020 to characterize changes in gender-affirming care, mental health, and economic stability as a result of the COVID-19 pandemic. We conducted Poisson regression models to assess if access to gender-affirming care and ability to live according to one’s gender were related to depressive symptoms, anxiety, and changes in suicidal ideation.

Results

Individuals resided in 76 countries, including Turkey (27.4%,n=264/964) and Thailand (20.6%,n=205). A majority were non-binary (66.8%,n=644) or transfeminine (29.4%,n=283). Due to the COVID-19 pandemic, 55.0% (n=320/582) reported reduced access to gender-affirming resources, and 38.0% (n=327/860) reported reduced time lived according to their gender. About half screened positive for depression (50.4%,442/877) and anxiety (45.8%,n=392/856). One in six (17.0%,n=112/659) expected losses of health insurance, and 77.0% (n=724/940) expected income reductions. The prevalence of depressive symptoms, anxiety, and increased suicidal ideation were 1.63 (95% CI: 1.36–1.97), 1.61 (95% CI: 1.31–1.97), and 1.74 (95% CI: 1.07–2.82) times higher for individuals whose access to gender-affirming resources was reduced versus not.

Discussion

The COVID-19 pandemic has reduced access to gender-affirming resources and the ability of transgender and non-binary people to live according to their gender worldwide. These reductions may drive the increased depressive symptoms, anxiety, and suicidal ideation reported in this sample. To improve transgender and non-binary health globally, increased access to gender-affirming resources should be achieved through policies (e.g., digital prescriptions), flexible interventions (e.g., telehealth), and support for existing transgender health initiatives.

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

Ensheng Dong, Hongru Du, Lauren Gardner (2020)

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

Maria R.C. Nicola, Zaid Alsafi, Catrin Sohrabi … (2020)

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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Prevalence of stress, anxiety, depression among the general population during the COVID-19 pandemic: a systematic review and meta-analysis

Nader Salari, Amin Hosseinian-Far, Rostam Jalali … (2020)

Background The COVID-19 pandemic has had a significant impact on public mental health. Therefore, monitoring and oversight of the population mental health during crises such as a panedmic is an immediate priority. The aim of this study is to analyze the existing research works and findings in relation to the prevalence of stress, anxiety and depression in the general population during the COVID-19 pandemic. Method In this systematic review and meta-analysis, articles that have focused on stress and anxiety prevalence among the general population during the COVID-19 pandemic were searched in the Science Direct, Embase, Scopus, PubMed, Web of Science (ISI) and Google Scholar databases, without a lower time limit and until May 2020. In order to perform a meta-analysis of the collected studies, the random effects model was used, and the heterogeneity of studies was investigated using the I2 index. Moreover. data analysis was conducted using the Comprehensive Meta-Analysis (CMA) software. Results The prevalence of stress in 5 studies with a total sample size of 9074 is obtained as 29.6% (95% confidence limit: 24.3–35.4), the prevalence of anxiety in 17 studies with a sample size of 63,439 as 31.9% (95% confidence interval: 27.5–36.7), and the prevalence of depression in 14 studies with a sample size of 44,531 people as 33.7% (95% confidence interval: 27.5–40.6). Conclusion COVID-19 not only causes physical health concerns but also results in a number of psychological disorders. The spread of the new coronavirus can impact the mental health of people in different communities. Thus, it is essential to preserve the mental health of individuals and to develop psychological interventions that can improve the mental health of vulnerable groups during the COVID-19 pandemic.

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Author and article information

Journal

Journal ID (nlm-ta): medRxiv

Journal ID (publisher-id): MEDRXIV

Title: medRxiv

Publisher: Cold Spring Harbor Laboratory

Publication date (Electronic): 04 November 2020

Electronic Location Identifier: 2020.11.02.20224709

Affiliations

[1 ]Department of Epidemiology; Bloomberg School of Public Health, Johns Hopkins University

[2 ]Department of Health Behavior and Biological Sciences; School of Nursing; University of Michigan

[3 ]Department of Health, Policy, and Management; Bloomberg School of Public Health; Johns Hopkins University

[4 ]Hornet; San Francisco, CA, USA

[5 ]Department of Health, Behavior, and Society; Department of International Health; Bloomberg School of Public Health; Johns Hopkins University

Author notes

CORRESPONDENCE: Brooke A. Jarrett: brooke@ 123456jhmi.edu

Article

DOI: 10.1101/2020.11.02.20224709

PMC ID: 7654856

PubMed ID: 33173876

SO-VID: e0375c34-38d3-4285-946a-1180009374bd

License:

It is made available under a CC-BY-NC-ND 4.0 International license.

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Gender-affirming care, mental health, and economic stability in the time of COVID-19: a global cross-sectional study of transgender and non-binary people

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Novel Coronavirus Disease COVID-19

Most cited references 46

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

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

Prevalence of stress, anxiety, depression among the general population during the COVID-19 pandemic: a systematic review and meta-analysis

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