Paucity and Disparity of Publicly Available Sex-Disaggregated Data for the COVID-19 Epidemic Hamper Evidence-Based Decision-Making

When silence goes viral, Africa sneezes! A perspective on Africa's subdued research response to COVID-19 and a call for local scientific evidence

By mid-September 2020, over 1.33 million confirmed COVID-19 cases and 32 thousand deaths had been reported in Africa. Global research on COVID-19 went 'viral' with a record 3487 research contributions comprising of 2062 journal papers and 1425 preprints published within the first three months following the outbreak of COVID-19. Surprisingly, the silence of the African research community has been unprecedented - contributing a paltry 0.6% (22 contributions), a figure nearly matched by Colombia (18 publications). Until now, a comprehensive perspective on the reasons for this subdued research response, and COVID-19 themes critical to Africa has been missing. We posit that while a milieu of factors accounts for this silence, unprecedented research opportunities exist to support COVID-19 decision and policy formulation in Africa. The subdued response reflects weak research systems, characterized by deep-rooted challenges, including severe lack of research expertise, funding, and infrastructure, coupled with poor working conditions. Hence, Africa's contribution to research on infectious diseases, including COVID-19, remains weak. Perceptions and attitudes among researchers and policy-makers on COVID-19, and the role of science in decision and policy-making also exist. Moreover, COVID-19 and earlier severe acute respiratory syndromes are considered as 'imported diseases' originating from outside Africa. Thus, notions may exist that the control methods will come from outside Africa through 'technology-transfer' or 'capacity-building'. Yet local COVID-19 research is needed to address knowledge gaps, including; (1) potential novel transmission of SARS-CoV-2, (2) adaption of generic COVID-19 control measures to suit African settings, (3) occurrence and persistence of SARS-CoV-2 in solid waste, wastewaters, on-site sanitation systems, and drinking water, and (4) the 'human factor' including the role of gender, perceptions, myths, attitudes, and religious beliefs in the transmission and control of COVID-19. Therefore, there is a need to: (1) strengthen local research capacity and evaluation systems, (2) consider biosafety and ethical issues, (3) initiate cross-disciplinary research and global collaboration on COVID-19, and (4) integrate science communication in COVID-19 programs.

Paucity and Disparity of Publicly Available Sex-Disaggregated Data for the COVID-19 Epidemic Hamper Evidence-Based Decision-Making

COVID-19 has joined the long list of sexually dimorphic human disorders. Higher lethality in men, evident in the first reports from China, was confirmed in the subsequent Italian outbreak. Newspapers and scientific journals commented on this finding and the preexisting conditions, biological processes, and behavioral differences that may underlie it. However, little appeared to be released about sex differences in severity of disease, comorbidities, rate of recovery, length of hospital stay, or number of tests performed. Systematic analysis of official websites for 20 countries and 6 US states revealed a wide disparity in sex-disaggregated data made available to the public and scholars. Only a handful reported cases by sex. None of the other characteristics, including deaths, were stratified by sex at the time. Beyond suboptimal sex disaggregation, we found a paucity of usable raw data sets and a generalized lack of standardization of captured data, making comparisons difficult. A second round of data capture in April found more complete, but even more disparate, information. Our analysis revealed a wide range of sex ratios among confirmed cases. In countries where a male bias was initially reported, the proportion of women dramatically increased in 3 weeks. Analysis also revealed a complex pattern of sex ratio variation with age. Accurate, peer-reviewed, analysis of harmonized, sex-disaggregated data for characteristics of epidemics, such as availability of testing, suspected source of infection, or comorbidities, will be critical to understand where the observed disparities come from and to generate evidence-based recommendations for decision-making by governments.