Updated 20 March 2020: This is a list of resources and current reporting on how gender and gender data influence the preparedness and response efforts for COVID19 around the world, and the current and anticipated impacts of the pandemic.
This is a public resource for all to use. What is missing? Please add in comments below to share additional analysis, resources, policy responses or suggestions.
Preparedness: WHO Strategic Preparedness and Response (February 2020) — no gender strategy
The Lancet: COVID-19: The Gendered Impacts of the Outbreak
Comment| Volume 395, Issue 10227, P846–848, MARCH 14, 2020
By Clare Wenham, Julia Smith, Rosemary Morgan, on Behalf of the Lancet Gender & COVID-19 Working Group
“Policies and public health efforts have not addressed the gendered impacts of disease outbreaks. The response to coronavirus disease 2019 (COVID-19) appears no different. We are not aware of any gender analysis of the outbreak by global health institutions or governments in affected countries or in preparedness phases. Recognising the extent to which disease outbreaks affect women and men differently is a fundamental step to understanding the primary and secondary effects of a health emergency on different individuals and communities, and for creating effective, equitable policies and interventions.”
- Although sex-disaggregated data for COVID-19 show equal numbers of cases between men and women so far, there seem to be sex differences in mortality and vulnerability to the disease.
- Emerging evidence suggests that more men than women are dying, potentially due to sex-based immunological or gendered differences, such as patterns and prevalence of smoking.
- However, current sex-disaggregated data are incomplete, cautioning against early assumptions. Simultaneously, data from the State Council Information Office in China suggest that more than 90% of health-care workers in Hubei province are women, emphasising the gendered nature of the health workforce and the risk that predominantly female health workers incur.”
Ggender on blind responses to COVID19
Impact of COVID19 on care and domestic work and women’s time use
Economic impact of COVID19 on women’s employment
The need for disaggregated data
Gendered health workforce
Women’s leadership in pandemic response
In failing to give women a seat at the decision-making table, governments and international agencies trying to solve crises like COVID-19:
1) miss out on critical expertise because they aren’t leveraging the entire global health security talent pool
2) miss out on the gender dimensions of health emergencies, including the role of women in health care provision, the differences in disease transmission and outcomes between the sexes, and gender-based disparities in the way the sick seek medical care
3) are more likely to overlook the wider consequences of epidemics on reproductive, maternal and child health, such as lack of access to maternal and neonatal care, feminine hygiene products and contraception products
4) miss out on leveraging the vast networks of women in affected countries who are part of the solution to containing the virus.
Impact of COVID19 on violence against women
CARE: Gender Implications of COVID-19 Outbreaks in Development and Humanitarian Settings — Full report:
Until recently, the transmission of COVID-19 to developing countries or those experiencing ongoing humanitarian emergencies had been limited, but such transmission is now occurring. Development and humanitarian settings pose particular challenges for infectious disease prevention and control. Access constraints and poor health and sanitation infrastructure are obstacles to disease prevention and treatment under the best of circumstances; when coupled with gender inequality and, in some cases, insecurity, public health responses become immeasurably more complex.
Informed by lessons learned from past public health emergencies, CARE’s analysis shows that COVID-19 outbreaks in development or humanitarian contexts could disproportionately affect women and girls in a number of ways, including adverse effects on their education, food security and nutrition, health, livelihoods, and protection.Even after the outbreak has been contained, women and girls may continue to suffer from ill-effects for years to come.
Advocacy Brief: Gender and COVID-19: Key issues from the Asia and Pacific
COVID19, maternal health and pregnancy
COVID19 and sexual and reproductive health and rights
Gender, health and hygiene
NYT In Her Words: Clean Hands?
Gender and pandemic preparedness — the research
- These results suggest an inherent difference in how men and women respond to epidemic and pandemic respiratory infectious diseases.
Children and youth
Widening inequality
Training materials - Gender and Infectious Disease (One Health Central and Eastern Africa network/USAID)
Background on gender data for health policy and planning
Collecting, analyzing, and using good quality, disaggregated data is necessary to improve people’s health and well-being. In 2019, WHO’s Global Health Statistics were disaggregated by sex for the first time. When data on individuals are broken down by sex, health systems are better able to identify and respond to gender inequalities in health, and allocate resources accordingly. Such data can also show how gender interacts with other drivers of inequalities such as age, ethnicity, sexual orientation, gender identity, poverty level or geographic location to influence health outcomes.
When data on individuals is broken down by sex, health systems can:
- Identify gender inequities in health
- Conduct an intersectional gender analysis to see how gender inequality and restrictive gender norms intersect with other factors to shape men’s, women’s and gender diverse people’s health
- Respond to gender and other inequities by designing gender-responsive and –transformative policies
- Allocate appropriate resources and build capacity to implement equitable health systems
While closing data gaps is necessary, many countries still struggle to provide information disaggregated by sex. Health policy and practice that leads to universal health coverage must be underpinned by robust and reliable data in order to identify where inequities lie and to understand the underlying causes of differential health outcomes, identify what drives people to seek health care, what barriers they face, and see how the system responds.
