The Covid-19 pandemic affects men and women differently, which is why it is so crucial to respond to the crisis using gender data to inform evidence-based solutions, says a report on Tuesday.
Since the outbreak, a larger share of women (53 percent, compared to 31 percent of men) in formal employment has seen their paid work hours reduced.

Within a week of the pandemic being declared, UN Women engaged with national governments and mobile network operators to roll out a series of rapid assessment surveys in 11 Asia-Pacific countries.

The countries are Afghanistan, Bangladesh, Cambodia, Indonesia, Nepal, Maldives, Pakistan, Philippines, Samoa, Solomon Islands and Thailand.

The report, titled "Unlocking the Lockdown: The Gendered Effects of Covid-19 on Achieving the SDGs in Asia and the Pacific," revealed how Covid-19 may be reversing the hard-won gains Asia-Pacific has made in achieving the Sustainable Development Goals (SDGs).

The lockdowns have made unpaid domestic work an essential service, but women have shouldered most of the burden: 63 percent of women saw increases in their time spent doing this work, compared to 55 percent of men, according to the report released from Bangkok.

Covid-19 is hitting women's income from savings, investments and properties the hardest, with 66 percent of women seeing decreases compared to 54 percent of men.

The report also clearly demonstrates how Covid-19 is triggering a mental health crisis in the region, as the emotional impact of the pandemic unduly falls on women's shoulders in most countries.

Increases in unpaid work, job and income loss, and the effects of the lockdown on gender-based violence are among the factors that may be contributing to higher rates of stress and anxiety among women.

Younger women (10–24 years old) in particular have seen their mental health disproportionately affected.

'Innovative solutions for data collection'

While social distancing has made traditional, face-to-face data collection nearly impossible, UN Women's Regional Office for Asia and Pacific turned to innovative solutions for data collection by using public-private partnerships, working with governments and mobile network operators to execute rapid assessment surveys in 11 countries in the region.

"As the Covid-19 crisis unfolded, we saw time and again news stories about contagion and death rates," says Mohammad Naciri, UN Women Regional Director for Asia and the Pacific.

"Data from UN Women's rapid assessment surveys, however, showcases that the consequences of Covid-19 expand well beyond physical health. More women are seeing their mental health affected and are having more trouble seeking medical care and accessing medical supplies. Having this data is critical to inform emergency responses. Otherwise, we are making our decisions blindfolded."

The wide-ranging survey, which combined SMS-based data collection with the deployment of enumerators working in remote areas, covered a large sample size. In nearly every country involved, the survey included thousands of participants.

In smaller countries like Samoa, where data is expensive and access to technology is not evenly distributed, government and telecom partners worked meticulously to ensure minimum sample sizes were met.

"The Covid-19 pandemic has caught many off-guard and collecting this invaluable data is key to not only designing interventions that work, but to provide meaningful support in a reasonable timeframe," says Mele Maualaivao, Country Programme Coordinator for UN Women in Samoa.

"Having such a rapid response is so valuable in light of Covid-19 and how information must be shared now."

The results of the survey are already having direct impacts in the surveyed regions. For instance, in Maldives, where the National Bureau of Statistics worked with UN Women to poll more than 5,000 citizens, the government is now using the findings to design its response to the crisis.

Other countries, such as Philippines and Bangladesh, have asked for a second round of surveys to evaluate how things have changed since the outbreak began.