Women, Work and the COVID-19 Pandemic: Paving the Path Forward

This paper focuses on the pandemic's impact on women's participation in the economy. The author outlines the various barriers to the full and equal participation of women in the Indian economy such as the gender division of labour which requires women to shoulder the burden of unpaid domestic work, the occupational segregation of the labour market, gender-blind development policies, regressive social norms and patriarchal attitudes. The challenge facing women only increased with the pandemic which led to large numbers of women dropping out of the workforce. The author suggests that in the immediate future the State has a crucial role in redressing this injustice. In the longer term, she calls for rethinking the dominant models of development that pursue economic growth and rise in GDP as the panacea for all problems. Such models have given rise to the rampant exploitation of labour, among whom women are the most vulnerable. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023.

Sex differences in hospitalized COVID-19 patients

The novel coronavirus disease (COVID-19) affected females less than males, as demonstrated by sex-disaggregated data present in the literature. During the first wave, females hospitalized at San Raffaele Hospital, Milan, Italy were few in number, presented symptoms later and had less critical clinical conditions than males. The present study aimed to evaluate the epidemiological status of the female population during the second wave, which occurred in Autumn 2020 in Italy. This prospective cohort study included all patients, with a positive real-time reverse-transcriptase polymerase chain reaction for COVID-19, who attended the emergency department or were hospitalized in wards and/or intensive care unit (ICU) from 29th September 2020 to 29th November 2020. A total of 1216 COVID-19 patients were included, of whom 459 (37.8%) were females. The percentage of females admitted was 41.3% in the first period and 36.3% in the second period, without significant increase over time (p = 0.3). Females accounted for 25% of all COVID-19 intensive care unit admissions. There was significantly sex-based difference in the overall hospital mortality (4.1% for females and 11.3% for males, p < 0.0001). At San Raffaele Hospital, Milan, Italy during the second wave, female patients were few and affected by a less severe form of COVID-19. An increase over time of females hospitalized patients was not reported, unlike what was previously demonstrated during the first wave. Copyright © 2022 The Author(s). Published by MRE Press.

Sex-disaggregated data matters: tracking the impact of COVID-19 on the health of women and men.

Sex and gender matter to health outcomes, but despite repeated commitments to sex-disaggregate data in health policies and programmes, a persistent and substantial absence of such data remains especially in lower-income countries. This represents a missed opportunity for monitoring and identifying gender-responsive, evidence-informed solutions to address a key driver of the pandemic. In this paper we review the availability of national sex-disaggregated surveillance data on COVID-19 and examine trends on the testing-to-outcome pathway. We further analyse the availability of data according to the economic status of the country and investigate the determinants of sex differences, including the national gender inequality status (according to a global index) in each country. Results are drawn from 18 months of global data collection from over 200 countries. We find differences in COVID-19 prevention behaviours and illness outcomes by sex, with lower uptake of vaccination and testing plus an elevated risk of severe disease and death among men. Supporting and maintaining the collection, collation, interpretation and presentation of sex-disaggregated data requires commitment and resources at subnational, national and global levels, but provides an opportunity for identifying and taking gender-responsive action on health inequities. As a first step the global health community should recognise, value and support the importance of sex-disaggregated data for identifying and tackling an inequitable pandemic.

Food Insecurity, Financial Hardship, and Mental Health Among Multiple Asian American Ethnic Groups: Findings from the 2020 COVID-19 Household Impact Survey.

Background: The COVID-19 pandemic has adversely impacted the financial and mental well-being of U.S. adults, however, Asian American (AA)-specific data are lacking, particularly disaggregated by AA ethnicity. Our objective was to evaluate food insecurity (FI), financial hardship, and mental health among disaggregated AA ethnic groups during the COVID-19 pandemic. Methods: We used data from the COVID-19 Household Impact Survey, a sample of 10,760 U.S. adults weighted to reflect the U.S. population (weighted n: 418,209,893). AA ethnic categories were based on self-report (n=312, 5.1%; weighted n: 21,143,079) and provided as follows: Chinese American, South Asian, Filipino+Vietnamese, and Japanese+Korean. We estimated the prevalence of FI and financial hardship across AA ethnic categories. We estimated the demographic determinants of FI, including financial hardship, among AA adults using multivariable Poisson regression. We calculated the prevalence of mental health symptoms among food-insecure AA adults, as well as among AA adults experiencing both FI and financial hardship. Results: Overall, the prevalence of FI and financial hardship among AA adults was highest among Filipino+Vietnamese adults (52.9-24.5%) and lowest among Japanese+Korean adults (13.9-8.6%). Determinants of FI among AA adults included Filipino+Vietnamese ethnicity (adjusted prevalence ratios [aPR]: 2.81, 95% confidence interval [CI]: 1.49-5.29), being widowed/divorced/separated (aPR: 3.14, 95% CI: 1.37-7.23), high school graduate only (aPR: 3.46, 95% CI: 1.96-6.11), having low income <$30,000 (aPR: 2.54, 95% CI: 1.27-5.06), and living in rural areas (aPR: 7.65, 95% CI: 1.17-50.14). Eighty-one percent and 63% of AA adults with anxiety and hopelessness at least 3-7 days/week, respectively, were food insecure and experiencing financial hardship. Conclusion: Disparities exist in FI and financial hardship among AA adults, particularly Filipino+Vietnamese adults, and are associated with increased self-reporting of feelings of anxiety and hopelessness.

Strengthening the Collection and Use of Disaggregated Data to Understand and Monitor the Risk and Burden of COVID-19 Among Racialized Populations.

There is growing evidence that the risk and burden of COVID-19 infections are not equally distributed across population subgroups and that racialized communities are experiencing disproportionately higher morbidity and mortality rates. However, due to the absence of large-scale race-based data, it is impossible to measure the extent to which immigrant and racialized communities are experiencing the pandemic and the impact of measures taken (or not) to mitigate these impacts, especially at a local level. To address this issue, the Ottawa Local Immigration Partnership partnered with the Collaborative Critical Research for Equity and Transformation in Health lab at the University of Ottawa and the Canadians of African Descent Health Organization to implement a project to build local organizational capacities to understand, monitor, and mitigate the impact of the COVID-19 pandemic on immigrant and racialized populations. This research note describes the working framework used for this project, proposed indicators for measuring the determinants of health among immigrant and racialized populations, and the data gaps we encountered. Recommendations are made to policymakers, and community and health stakeholders at all levels on how to collect and use data to address COVID-19 health inequities, including data collection strategies aimed at community engagement in the collection of disaggregated data, improving methods for collecting and analyzing data on immigrants and racialized groups and policies to enable and enhance data disaggregation. Résumé Des plus en plus d'études montrent que le risque et le fardeau des infections à la COVID-19 ne sont pas également répartis dans la population et que les communautés racialisées connaissent des taux de morbidité et de mortalité disproportionnellement plus élevés. Cependant, en raison de l'absence de données ventilés selon le statut ethnique, il est impossible de mesurer comment les communautés immigrantes et racialisées vivent la pandémie et quel est l'impact des mesures prises (ou non) pour atténuer ces effets, surtout à un niveau local. Pour résoudre ce problème, le Partenariat local pour l'immigration d'Ottawa (PLIO) s'est associé au Laboratoire de recherche critique collaborative pour l'équité et la transformation en santé (CO-CREATH) de l'Université d'Ottawa et l'Organisation de la santé des Canadiens d'ascendance africaine (CADHO) aux fins de mettre en œuvre un projet visant à renforcer les capacités organisationnelles locales pour comprendre, surveiller et atténuer l'impact de la pandémie de la COVID-19 sur les populations immigrantes et racialisées. Cette note de recherche décrit le cadre de travail utilisé pour ce projet, les indicateurs proposés pour mesurer les déterminants de la santé chez les populations immigrantes et racialisées, et les lacunes que nous avons identifiés dans les données existants. Des recommandations sont faites aux décideurs politiques et aux acteurs communautaires et de la santé à tous les niveaux sur comment collecter et utiliser les données pour remédier aux inégalités en matière de santé liées à la COVID-19. Ces recommandations font référence aux stratégies de collecte de données visant à impliquer les communautés, à l'amélioration des méthodes de collecte et d'analyse des données sur les immigrants et les groupes racialisés, et aux politiques nécessaires pour permettre et améliorer la désagrégation des données selon le statut ethnique.

COVID-19, sex, and gender in China: a scoping review.

BACKGROUND: During the course of the COVID-19 pandemic, states were called upon by the World Health Organization to introduce and prioritise the collection of sex-disaggregated data. The collection of sex-disaggregated data on COVID-19 testing, infection rates, hospital admissions, and deaths, when available, has informed our understanding of the biology of the infectious disease. The collection of sex-disaggregated data should also better inform our understanding of the gendered impacts that contribute to risk of exposure to COVID-19. In China, the country with the longest history of fighting the COVID-19 infection, what research was available on the gender-differential impacts of COVID-19 in the first 6 months of the COVID-19 pandemic? METHODS: In this scoping review, we examine the first 6 months (January-June 2020) of peer-reviewed publications (n = 451) on sex and gender experiences related to COVID-19 in China. We conducted an exhaustive search of published Chinese and English language research papers on COVID-19 in mainland China. We used a COVID-19 Gender Matrix informed by the JPHIEGO gender analysis toolkit to examine and illuminate research into the gendered impacts of COVID-19 within China. RESULTS: In China, only a small portion of the COVID-19-related research focused on gender experiences and differences. Near the end of the six-month literature review period, a small number of research items emerged on women healthcare workers, women's mental health, and pregnant women's access to care. There was an absence of research on the gendered impact of COVID-19 amongst populations. There was minimal consideration of the economic, social and security factors, including gender stereotypes and expectations, that affected different populations' experiences of infection, treatment, and lockdown during the period of review. CONCLUSION: At the outset of health emergencies in China, gender research needs to be prioritised during the first stage of an outbreak to assist with evaluation of the most effective public health measures, identifying access to healthcare and social welfare barriers amongst priority communities. Gender stereotypes and gendered differences lead to different patterns of exposure and treatment. The exclusion of this knowledge in real time affects the design of effective prevention and recovery.

A downscaling approach to compare COVID-19 count data from databases aggregated at different spatial scales.

As the COVID-19 pandemic continues to threaten various regions around the world, obtaining accurate and reliable COVID-19 data is crucial for governments and local communities aiming at rigorously assessing the extent and magnitude of the virus spread and deploying efficient interventions. Using data reported between January and February 2020 in China, we compared counts of COVID-19 from near-real-time spatially disaggregated data (city level) with fine-spatial scale predictions from a Bayesian downscaling regression model applied to a reference province-level data set. The results highlight discrepancies in the counts of coronavirus-infected cases at the district level and identify districts that may require further investigation.

Gender-related sociocultural differences and COVID-19: what influence on the effects of the pandemic?

In the first stages of the pandemic, the adverse outcomes of COVID-19 were significantly higher in men than in women most likely as the effect of biological, hormonal, metabolic differences between the two sexes. However, gender-related differences in lifestyles and social roles can also greatly influence the course of disease. To fully understand the influence of gender in the COVID-19 outbreak, the collection and dissemination of disaggregated data must be enhanced to allow a better knowledge of the effects of SARS-CoV-2 infection in men and women, not only from a biomedical point of view, but also considering the risk factors associated with the different roles that they play in the society.

Mortality in COVID-19: Further Evidence for a Sex-Based Difference in the OpenSAFELY Study.

Although COVID-19 death rates are lower in women compared to men, it is not clear whether this difference in mortality is due to sex (biological) based factors, comorbidities that differ in men and women, or gender influences. New evidence supports a sex-based difference in COVID-19 mortality. Data from the OpenSAFELY cohort study in 17 million adult patients in England demonstrate that COVID-19-related deaths were associated with male sex (hazard ratio 1.59; 95% confidence interval 1.53-1.65) when fully adjusted for age, low income, smoking, pre-existing diseases, and ethnicity. Women have stronger innate and adaptive responses to infection. It is hypothesized that biological differences in the immune system may have a role in the sex-based difference in mortality from COVID-19. The results of OpenSAFELY demonstrate the importance of collection and analysis of sex-disaggregated data in research and public surveillance.