NEW YORK — Less than 1% of the research published on Ebola and Zika at the time of the outbreaks explored their gendered impacts. There has been a concerted push to avoid the same mistakes with the coronavirus pandemic and to collect more quality data disaggregated by sex, gender, and age.
But ongoing data collection work on COVID-19 has some experts, like Plan International USA CEO Tessie San Martin, wondering about new, widening information gaps — and how to create a more accurate picture of the virus’s impact on all people.
UN Women rolled out surveys in multiple countries in Asia and the Pacific just weeks after the pandemic was declared. Statistics specialist Sara Duerto Valero explains how the agency was able to act so quickly, and what the data reveals so far about the impacts of the crisis on men and women.
“We usually talk about making sure that we’re collecting data that has been disaggregated by age and gender, and that’s all well and good. My question is whether that was enough,” San Martin told Devex.
Organizations must recognize and account for bias in research design and collection, San Martin said. Bias in research can manifest when men are the only ones tasked with conducting consultations with women, for example, and do not ask questions that speak to women’s particular experiences. This can result in women and girls being excluded from in-person consultations where data and anecdotal experiences are collected.
Ensuring women’s participation and voices in consultations, and acknowledging different cultural contexts — in which women and girls are not always consulted or allowed to drive data collection processes — can lead to more inclusive approaches, San Martin said.
COVID-19 gender data remains ‘incomplete’
Accurate gender data is considered necessary for a gender-sensitive response to COVID-19. But an ongoing joint review from Data2X and Open Data Watch shows that data on primary health effects by sex — whether on confirmed coronavirus infections or deaths — is “incomplete for the majority of the global population.” For low-income countries, this data is “non-existent,” according to the review.
“The challenge is not that people are not collecting gender data; it is that they are not uniformly collecting it,” said Andrea Ulrich, deputy director of operations at Development Gateway. She recently published an article on how coronavirus data is not gender-neutral, writing that “there is always inherent bias involved in collecting and analyzing quantitative evidence – it is often anything but ‘objective.’”
Johns Hopkins University’s COVID-19 data dashboard and map, for example, do not disaggregate their numbers by sex or gender. And many local counties across the U.S. do not collect gender data on the coronavirus, making it difficult to aggregate comprehensive gender data from across the country.
“When you do not have that requirement, you lose the power to aggregate analysis, whether we are talking about the U.S., in terms of county reports, or uniform gender data reporting. That is one of the issues,” Ulrich said.
“Let’s take a step back to see how we can ensure we are collecting unbiased, gender-disaggregated, age-disaggregated, timely, quality data.”— Damien Queally, executive director of program operations, Plan International
Another emerging issue is that the pandemic is widening a digital gender divide already felt worldwide. Women and girls are less likely than men and boys to have access to the internet and mobile phones and can be excluded from routine data collection exercises as a result.
Some development organizations have responded during the pandemic, offering new solutions on collecting gender data. UN Women, for example, has created a resource for updated data on COVID-19 cases by age and gender. Open Data Watch has also released new guidelines on collecting gender-sensitive data during the pandemic.
“The concern is that the digital divide would exacerbate these inequities and inequalities. It is relevant when it comes to gender data. Positive examples and success stories plant a strong way forward for institutions and individuals who want to be sure they are looking at these different factors to account for that appropriately,” Ulrich said.
Removing ‘blinders’ in gender data collection
A simple solution for addressing these issues does not exist, according to San Martin. But Plan International is reflecting on its organizational culture, considering what changes are necessary for raising awareness during the pandemic, and “creating a safe space for conversations about issues that people would rather not be talking about,” San Martin said.
“Responders themselves are usually blind or have blinders on in terms of some of these cultural issues. We've been doing a lot of work internally on diversity, equity, and inclusion in our own organization and in every aspect of our operations,” San Martin said.
“Organizational cultural blinders that exist may mean that how we're designing programs, how we're designing research, is not fully taking into account some of these embedded gender norms,” San Martin continued.
Plan International conducted a rapid survey of girls in its networks in Zimbabwe and Senegal to directly ask them what they most needed in terms of support. The organization has also set up a new committee to work with a diversity, equity, and inclusion consultant on implementing a new strategy aimed at improving its hiring practices, internal policies, and programming work.
There is also a need to think outside of traditional data collection mechanisms and to rely more on community engagement, according to Damien Queally, executive director of program operations at Plan International.
“I don’t want to say that just data is important, but to invest in training people on how to collect quality data, how to ask the right questions, and not to be leading in your responses is also key,” Queally said.
The organization is working toward directly engaging more local community members and youths who are “trusted and respected” and can also be trained to collect data, Queally said.
“The power dynamic is more equal, and that can help us get better information. Nobody's going to want to tell a ministry of health official that they're not happy with what's happening, and no one's going to want to tell UNICEF that their support isn't good enough. That's not what most people want to hear,” Queally said.
“Everybody keeps saying, ‘Data is critical, data is important, we need data.’ Well, then let’s take a step back to see how we can ensure we are collecting unbiased, gender-disaggregated, age-disaggregated, timely, quality data in a way that informs our decisions,” Queally added.
Devex, with support from our partner UN Women, is exploring how data is being used to inform policy and advocacy to advance gender equality. Gender data is crucial to make every woman and girl count. Visit the Focus on: Gender Data page for more. Disclaimer: The views in this article do not necessarily represent the views of UN Women.