Towards the real-time inclusion of sex- and age-disaggregated data in pandemic responses

While data and research on COVID-19 are being produced at unprecedented speed, reporting of the data disaggregated by sex—let alone by sex and age—remains rare.4 Growing numbers of countries have begun to report their confirmed cases and deaths by sex and sometimes by sex and age.5 However, according to WHO, as of 22 September 2020, only 27% of 31 038 914 confirmed cases of COVID-19 had been reported to the Organization with data on sex and age.6 7 While the reporting form for confirmed COVID-19 cases captures8 this information, because relatively few countries report the case data to the WHO, these data do not provide the full picture. Because sex-disaggregated data are scant across age groups on comorbidities or other risk factors, as well as on testing, symptoms, hospitalisation and intensive care (including criteria), discharge and recovery—or even excess mortality9—we are left in the dark about how the pandemic affects women and men across different age groups in different countries. Finland and Pakistan report a slightly higher case fatality rate for women compared with men.17 These variances are probably due to a combination of factors, including transmission patterns, immunological differences, variability in prevalence of comorbidities or other risk factors (such as smoking and exposure to higher levels of air or household pollution), frequency of exposure and the viral load—but also the rate of and access to testing and case detection. Evidence from Spain also shows that women are more exposed through contact with COVID-19-infected persons or by visiting health centres, resulting from their excessive caregiving responsibilities or as a result of being healthcare workers. Since the start of the outbreak in Spain, 35 548 cases of COVID-19 were confirmed in health workers by 7 May, of which 76% were women with median age of 46 years.19 The heightened vulnerability of women on the frontlines has been underscored by reports of gender blindness and bias in health systems—such as ill-fitting personal protective equipment designed for the male anatomy.20 We also have insufficient public data to rule out potential differences in symptoms and in the presentation of disease in women and men which may result in potential underdiagnosis or misdiagnosis. While the data are too limited to draw any meaningful conclusions, there is a need for better gender analysis in order to have a more accurate understanding of clinical features, severity of disease, risk fact