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Strengthening Gender Measures and Data in the Covid-19 Era: an Urgent Need for Change

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Strengthening Gender Measures and Data in the Covid-19 Era: an Urgent Need for Change STRENGTHENING GENDER MEASURES AND DATA STRENGTHENINGIN THE COVID-19 ERA: AN URGENT NEED FOR CHANGE GENDER MEASURES AND DATA IN THE COVID-19 ERA: AN URGENT NEED FOR CHANGE STRENGTHENING GENDER MEASURES AND DATA IN THE COVID-19 ERA: AN URGENT NEED FOR CHANGE Contributors Acronyms & Key Terms A PMA Resident Enumerator Acronyms administering the women's questionnaire to a resident of the CSOs: Civil Society Organizations Ngilima neighborhood of Kinshasa, CRVS: DRC, during data collection. Civil registration and vital statistics GBV: Gender-based violence Photo credit: Gloria Mbuya, Communications Officer for NSO: National Statistical Office the Kinshasa School of Public NSS: National Statistical System Health, University of Kinshasa. UN: United Nations Authors: Key Terms Center on Gender Equity and Health, UCSD Data infrastructures: Technologies and frameworks for data Lotus McDougal collection and processing, as well as related processes such as institutional set-up, capacity development, data planning, and policy. Anita Raj Jennifer Yore Digital financial inclusion:Digital efforts to offer a range of sustainable financial services that reach populations traditionally Data2X excluded and underserved financially. Sarah Boyd Gender data: Data which includes, but is not limited to, a primary Neeraja Penumetcha focus on sex disaggregation, reflects all peoples’ diverse, gendered, and holistic experiences, explicates drivers of different opportunities Emily Courey Pryor and outcomes between men and women, and accounts for data Bill & Melinda Gates Foundation biases derived from social and cultural norms. Diva Dhar Gender-intentional: An approach in which an understanding of gender roles, inequalities, gaps, and barriers is intentionally Global Center for Gender placed at the forefront of all decisions. Equality at Stanford University Gender measures: Indicators able to measure gender data. Gary Darmstadt Gender responsive: Results that exhibit an understanding of Krishna Jafa gender roles and inequalities and support equal and fair participation and distribution of benefits. Global Health 50/50 Sarah Hawkes Gender statistics: Statistics that measure aspects of the lives of women and men, and of girls and boys. Anna Purdie Sonja Tanaka Intersectionality: The interrelation of social categories (e.g., gender, race) that result in mutual systems of discrimination International Labor Organization or disadvantage. Elisa Benes, Mobile money: Provision of financial services through a mobile device. Kieran Walsh Non-traditional data sources: Data collected outside of typical health and development data generation sources such as PARIS21 administrative, census, and survey data. Data may come from Lauren Harrison diverse sources including the private sector, biometric collection Johannes Jutting mechanisms, social media, official sensor networks, citizen- Archita Misra generated data, spatial data infrastructure, and geospatial observation, and can be quite large (e.g., big data). UN Women Sex disaggregation: Data collected, analyzed, and reported Jessamyn Encarnacion separately for females and males. Papa Seck Traditional data sources: Data collected through government, NSS, and administrative systems, as well as facility or enterprise World Bank data, and public or private sector surveys and registers. Traditional Kathleen Beegle data sources generally rely on established data collection methods, Niklas Buehren and data collection and aggregation often take more time than non-traditional data sources. Isis Gaddis 02 STRENGTHENING GENDER MEASURES AND DATA IN THE COVID-19 ERA: AN URGENT NEED FOR CHANGE Contents Executive summary 04 Introduction 07 Key areas for action 09 Conclusion and Implications 19 Appendix 20 References 22 Endnotes 27 03 STRENGTHENING GENDER MEASURES AND DATA IN THE COVID-19 ERA: AN URGENT NEED FOR CHANGE Executive summary COVID-19 may be gender blind, but it is not and socioeconomic impacts of the pandemic. Only gender neutral. Emerging evidence shows one in three countries reports sex-disaggregated tremendous gender disparities in the health and COVID-19 case and death data, and this trend socioeconomic consequences of the pandemic, is worsening over time; gaps in testing and with a disproportionately negative impact on hospitalization data are even greater. women’s livelihoods, unpaid care work burden, mental health, and subjection to gender-based Key actions: violence. However, a lack of gender data impedes • Design, develop, and support coordinated our ability to measure, preempt, and respond. statistical infrastructures, capacities, and Understanding the extent of these impacts is the practices to consistently sex-disaggregate first step toward reversing course. The pandemic COVID-19 related data, and has exposed and exacerbated existing gender • Normalize and enable regular reporting of data gaps—particularly around health, education, COVID-19 epidemiologic data by sex and other and economic opportunity—that undermine our key sociodemographic characteristics such ability to intentionally craft gender-responsive as age, race, and occupation. policies and programs. Filling these data gaps poses a significant challenge as many data 2. Beyond disaggregation: collection efforts have been disrupted due to Collect standardized, comparable gender COVID-19 control measures, impacting everything data in areas where women’s and girls’ lives from data production to subsequent data are disproportionately affected by COVID-19. management, analysis, use, and communication. Our understanding of the pandemic’s There is no time to waste. Without addressing disproportionate gendered impacts on women these gender data gaps and collection obstacles, and girls was hindered by a lack of gender- we cannot fully understand or mitigate the intentional measures in early waves of data gendered impacts of the pandemic. The collection collection, as well as a delay in pivoting to and use of timely, quality gender data by all data alternative data collection modes when sources, official or non-official, is critical to traditional, in-person modes of data collection recognizing and addressing gender inequalities. stopped. These early gaps are gradually being More and better data is needed to identify the filled. As data collection operations resume, most urgent needs of populations that have been more gender measures are being included in most harmed by the pandemic and to formulate data collection processes and alternative data gender-responsive policies to effectively spur an collection methodologies are being deployed. equitable recovery. By committing to increased Yet available data indicates that the COVID-19 gender data collection and use now, we can build pandemic is exacerbating existing inequalities a foundation that is better prepared for future shocks. through gender unintentional or more gender › This brief calls on National Statistical Systems and survey managers, funders, multilateral agencies, researchers, and policymakers to act in five key areas: 1. Disaggregate all COVID-19 data at a minimum by sex and, ideally, by other key sociodemographic characteristics. This must be done consistently to effectively analyze and address the differential health 04 STRENGTHENING GENDER MEASURES AND DATA IN THE COVID-19 ERA: AN URGENT NEED FOR CHANGE Executive Summary (continued) › restrictive and discriminatory responses toward 4. Rapidly expand COVID-19 related women and girls. Collecting policy data that gender data availability, access, and use. tracks government responses, and the ways in Pandemic policy responses to date have been which they address women, will be crucial. largely gender unintentional. For example, a mere eight percent of social protection and labor Key actions: market measures have directly addressed unpaid • Support the coordinated inclusion and care—the majority of which falls on women. prioritization of standardized, comparable Open-access COVID-19 related data is largely gender measures in all surveys, including limited to surveys; there is a gap in open, regular in surveys to assess COVID-19 impacts; dissemination of administrative and non- • Prioritize the development, validation, traditional gender data. For policy measures to be dissemination, and coordinated use of effective, they must reflect what the data shows, standardized and comparable COVID-19 yet global progress is hindered by data silos and related gender measures on constructs suboptimal, inconsistent data sharing. When and that are not currently being assessed; and, where reliable and timely gender data exists, it • Create survey sampling frames that are should be shared and used. Such a bridge representative of women and girls at between data production and use can improve all privilege, marginalization, and both data responsiveness and build public trust. vulnerability levels. Key actions: 3. Increase the use of non-traditional • Create bidirectional engagement across gender gender data to fill critical gender data gaps. data production and use; Data from non-traditional sources—such as • Expand access to and use of existing social media activity, news media, mobile device- gender data that is not being used to its generated geospatial and other data, internet full potential; and, use, and private sector data—may provide • Mainstream gender data production and complementary and rapid insights alongside, use in national data systems. or in the absence of, traditional data sources. Non-traditional gender data may be harnessed 5. Resource and support
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