Carinne says:
“The stress of contracting the disease prevented me from visiting family. So I stayed at home... I was ill for two weeks [but] I was afraid to go to the hospital... It is not known which patient or doctor is the carrier of the disease. Which stressed me.”
Carinne’s story is more than just stress — she also talks about what it’s like to lead in the pandemic:
“I am part of an association called Sayap Africa which distributed donations during the COVID-19 period... Sayap Africa has taken the initiative to distribute food to families with at least six children. We bring them rice, sardines, soap, tomatoes, so that these families no longer have to travel and limit the contamination and spread of the virus. We distributed to 114 families in total.”
This is the kind of story we’ve been hearing all over the world. Stories are incredibly powerful, and when we start adding them together we can hear how powerful women really are — especially when they work together.
The report looks at women’s own stories and concerns in nearly 40 countries, representing the opinions of more than 6,000 women and 4,000 men. Drawing from 38 Rapid Gender Analyses and 15 needs assessments, CARE is the first organisation to provide a multi-country look at what women themselves are prioritising in the COVID-19 pandemic.
What are women experiencing?
Livelihoods are shrinking faster for women
55% of the women CARE spoke to reported that income loss was one of the biggest impacts COVID-19 had for them, compared to only 34% of men. Women are also having a harder time accessing safety nets when they lose their jobs.
Women prioritise food security
41% of women and 30% of men reported lack of food was a key impact COVID-19 had on their lives. This difference reflects deeply entrenched gender inequalities in local and global food systems.
Mental health is a major concern for women
Women are nearly three times more likely to report mental health as a priority impact than men are. 27% of women reported this was a key impact of COVID-19 — compared to only 10% of men. Women especially point to skyrocketing unpaid care burdens as a source of this stress, in addition to worries about livelihoods, food, and health care.
Current responses are falling short
Inequalities are growing. Policymakers and service providers are still using a one-size fits all approach because they are not asking women what they need, or looking at the differences between men and women. The current responses are failing to stem economic crises, hunger, and social turmoil.
What do we need to do now?
Get women and girls what they need
All actors providing support during COVID-19 — either through existing safety net programmes, special COVID-19 relief programmes, or humanitarian aid — should focus on the areas women are prioritising: livelihoods, food, mental health, and gender-based violence services. Programmes should deliberately target female recipients to ensure that support effectively meets the needs of both men and women.
Invest in women leaders
COVID-19 coordination and planning platforms are most effective when they are diverse and gender-balanced. All COVID-19 leadership committees and task forces should include at least 50% women and prioritise partnering with women’s rights organisations.
Fill the data gap
This report shows the power of listening to women and girls, and how the stories they tell are different from what aggregate data shows us. It also shows that it is possible to fill the data gap to design more effective responses. If CARE can do it, so can others. We can share CARE’s analysis and push for others to start filling the gender data gap.
Be accountable for equality
It’s past time to move from planning to adaptation and accountability. Every actor delivering COVID-19 responses should publish a status report on their activities to date and actions they have taken to listen to women’s experiences, uphold women’s rights, and ensure that women and girls have equal access to relief and recovery efforts.
- Want to learn more? Read the full report: She Told Us So: Filling the Data Gap to Build Back Equal
