COVID-19 burden, author affiliation and women's well-being: A bibliometric analysis of COVID-19 related publications including focus on low- and middle-income countries.

Background: Published literature documents tremendous gender inequities in the social, economic and health effects of the COVID-19 pandemic, but less evidence has come from low- and middle-income countries (LMICs) and even less from LMIC-based authors. We examine whether a) COVID-19 burden and b) LMIC-based authorship were associated with academic publications related to COVID-19 and women's well-being in LMICs. Methods: We reviewed academic articles on COVID-19 and women's well-being in LMICs published between February 2020 and May 2021 (n=1076 articles), using six electronic databases (PubMed, Web of Science, PsycInfo, EconLit, RePeC, NBER). Multilevel, mixed effects linear regressions assessed the relationships between each of our independent variables - a) COVID-19 burden (cases/100 population, deaths/100 population, deaths/cases) and b) author's country of primary affiliation, with publications related to COVID-19 and women's well-being, both overall and stratified by country income group. Findings: Eight-eight percent of articles had lead and/or senior authors affiliated with in-country institutions. Linear mixed effect models indicate that COVID-19 cases and case fatality ratios in a country were significantly and positively associated with the number of publications related to COVID-19 and women's well-being, though these relationships were significant only in upper-middle income group countries in stratified analyses. LMIC lead and senior authorship were also significantly and positively associated with our outcome, after adjusting for COVID-19 burden. Interpretation: While the majority of COVID-19 research examining women's well-being in LMICs in the first year and a half of the pandemic included country-affiliated author leadership, there were important gaps in representation. Findings highlight the importance of LMIC-based scholars to build local and gendered research in crises. Funding: Bill and Melinda Gates Foundation (INV-018007).

Understanding the impact of the COVID-19 pandemic on refugee communities in San Diego, California: A participatory action research cross-sectional study.

Background: While the COVID-19 pandemic has impacted people worldwide, refugee communities are particularly vulnerable to the pandemic's social, economic and health impacts. This study assessed factors associated with increases in adverse community effects of COVID-19 in a refugee community in California. Methods: This study uses data from a cross-sectional survey developed and administered as part of a participatory action research project by a refugee community organization in San Diego, California. Data was collected between September and November 2020 in a sample of refugee community members (n = 517). Multivariable Poisson regression models measured associations between sociodemographic and acculturation measures with seven adverse community effects overall and stratified by duration of residence in the United States. Adverse community effects included job/wage loss, bank/cash access barriers, food insecurity, school interruptions, household violence, substance misuse and poor mental health. Results: Refugee community members reported an average of 2.1 adverse community effects that worsened during the COVID-19 pandemic, with job/wage loss and poor mental health the most prevalent (84% and 49%). Characteristics associated with reporting increased numbers of adverse community effects included being younger, female, childless, not actively seeking employment, living in the US for six or more years and speaking English at home. Stratified analyses show that these associations were concentrated in refugees who had lived in the US for at least six years. Conclusion: Refugee communities have experienced pervasive job losses and worsening mental health during the COVID-19 pandemic, and these effects are concentrated in respondents who have lived in the US for six or more years. Additional targeted support is needed to ensure that refugees who have lived in the US for longer durations have the financial and social support needed to cope with the unprecedented challenges brought on by the COVID-19 pandemic.

Help seeking behavior by women experiencing intimate partner violence in india: A machine learning approach to identifying risk factors.

BACKGROUND: Despite the low prevalence of help-seeking behavior among victims of intimate partner violence (IPV) in India, quantitative evidence on risk factors, is limited. We use a previously validated exploratory approach, to examine correlates of help-seeking from anyone (e.g. family, friends, police, doctor etc.), as well as help-seeking from any formal sources. METHODS: We used data from a nationally-representative health survey conducted in 2015-16 in India, and included all variables in the dataset (~6000 variables) as independent variables. Two machine learning (ML) models were used- L-1, and L-2 regularized logistic regression models. The results from these models were qualitatively coded by researchers to identify broad themes associated with help-seeking behavior. This process of implementing ML models followed by qualitative coding was repeated until pre-specified criteria were met. RESULTS: Identified themes associated with help-seeking behavior included experience of injury from violence, husband's controlling behavior, husband's consumption of alcohol, and being currently separated from husband. Themes related to women's access to social and economic resources, such as women's employment, and receipt of maternal and reproductive health services were also noted to be related factors. We observed similarity in correlates for seeking help from anyone, vs from formal sources, with a greater focus on women being separated for help-seeking from formal sources. CONCLUSION: Findings highlight the need for community programs to reach out to women trapped in abusive relationships, as well as the importance of women's social and economic connectedness; future work should consider holistic interventions that integrate IPV screening and support services with women's health related services.

COVID-19-Related Financial Hardship, Job Loss, and Mental Health Symptoms: Findings from a Cross-Sectional Study in a Rural Agrarian Community in India.

Several countries, including India, imposed mandatory social distancing, quarantine, and lockdowns to stop the spread of the SARS-CoV-2 virus. Although these measures were effective in curbing the spread of the virus, prolonged social distancing, quarantine, and the resultant economic disruption led to an increase in financial stress and mental health concerns. Prior studies established a link between the first lockdown and an increase in mental health issues. However, few studies investigated the association between post-lockdown financial hardship, job loss, and mental health. In this study, we examined the association between COVID-19-related financial hardship, job loss, and mental health symptoms approximately nine months after the end of the first nationwide lockdown in India. Job loss was associated with higher reporting of mental health symptoms among men (aIRR = 1.16) while financial hardship was associated with poor mental health symptoms among women (aIRR = 1.29). Conversely, social support and government aid were associated with better mental health symptoms among women. Our findings highlight the need for financial assistance and job creation programs to aid families in the recovery process. There is also an urgent need for improving the availability and affordability of mental health services in rural areas.