ABSTRACT
Guaranteeing durability, provenance, accessibility, and trust in open datasets can be challenging for researchers and organizations that rely on public repositories of data critical to epidemiology and other health analytics. Not only are the required repositories sometimes difficult to locate, and nearly always require conversion into a compatible format, they may move or change unpredictably. Any single change of the rules in one repository can hinder updating of a public dashboard reliant on pulling data from external sources. These concerns are particularly challenging at the international level, because systems aimed at harmonizing health and related data are typically dictated by national governments to serve their individual needs. In this paper, we introduce a comprehensive public health data platform, the EpiGraphHub, that aims to provide a single interoperable repository for open health and related data, curated by the international research community, which allows secure local integration of sensitive databases whilst facilitating the development of data-driven applications and reports for decision-makers. The platform development is co-funded by the World Health Organization and is fully open-source to maximize its value for large-scale public health studies.
ABSTRACT
During the first wave of the COVID-19 pandemic, sub-Saharan African countries experienced comparatively lower rates of SARS-CoV-2 infections and related deaths than in other parts of the world, the reasons for which remain unclear. Yet, there was also considerable variation between countries. Here, we explored potential drivers of this variation among 46 of the 47 World Health Organization African region member states in a cross-sectional study. We described five indicators of early COVID-19 spread and severity for each country as of 29 November 2020: delay in detection of the first case, length of the early epidemic growth period, cumulative and peak attack rates, and crude case fatality ratio (CFR). We tested the influence of 13 pre-pandemic and pandemic response predictor variables on the country-level variation in the spread and severity indicators using multivariate statistics and regression analysis. We found that wealthier African countries, with larger tourism industries and older populations, had higher peak (p < 0.001) and cumulative (p < 0.001) attack rates, and lower CFRs (p = 0.021). More urbanized countries also had higher attack rates (p < 0.001 for both indicators). Countries applying more stringent early control policies experienced greater delay in detection of the first case (p < 0.001), but the initial propagation of the virus was slower in relatively wealthy, touristic African countries (p = 0.023). Careful and early implementation of strict government policies were likely pivotal to delaying the initial phase of the pandemic, but did not have much impact on other indicators of spread and severity. An over-reliance on disruptive containment measures in more resource-limited contexts is neither effective nor sustainable. We thus urge decision-makers to prioritize the reduction of resource-based health disparities, and surveillance and response capacities in particular, to ensure global resilience against future threats to public health and economic stability. Summary BoxO_ST_ABSWhat is already known on this topic?C_ST_ABSO_LICOVID-19 trajectories varied widely across the world, and within the African continent. C_LIO_LIThere is significant heterogeneity in the surveillance and response capacities among WHO African region member states. C_LI What are the new findings?O_LICumulative and peak attack rates during the first wave of COVID-19 were higher in WHO African region member states with higher per-capita GDP, larger tourism industries, older and more urbanized populations, and higher pandemic preparedness scores. C_LIO_LIAlthough better-resourced African countries documented higher attack rates, they succeeded in limiting rapid early spread and mortalities due to COVID-19 infection. C_LIO_LIAfrican countries that had more stringent early COVID-19 response policies managed to delay the onset of the outbreak at the national level. However, this phenomenon is partially explained by a lack of detection capacity, captured in low pandemic preparedness scores, and subsequent initial epidemic growth rates were slower in relatively well-resourced countries. C_LI What do the new findings imply?Careful implementation of strict government policies can aid in delaying an epidemic, but investments in public health infrastructure and pandemic preparedness are needed to better mitigate its impact on the population as a whole.
ABSTRACT
ObjectiveTo investigate differences of COVID-19 related mortality among women and men across sub-Saharan Africa (SSA) from the beginning of the pandemic. DesignA cross sectional study. SettingData from 20 member nations of the WHO African region until September 1, 2020. Participants69,580 cases of COVID-19, stratified by sex (men, n=43071; women, n=26509) and age (0-39 years, n=41682; 40-59 years, n=20757; 60+ years, n=7141). Main outcome measuresWe computed the SSA- and country-specific case fatality rates (CFRs) and sex-specific CFR differences across various age groups, using a Bayesian approach. ResultsA total of 1,656 (2.4% of total cases reported; 1656/69580) deaths were reported, with men accounting for 1168/1656 (70.5%) of total deaths. In SSA, women had a lower CFR than men (mean CFRdiff = -0.9%; 95% credible intervals -1.1% to -0.6%). The mean CFR estimates increased with age, with the sex-specific CFR differences being significant among those aged 40 or more (40-59 age-group: mean CFRdiff = -0.7%; 95% credible intervals -1.1% to -0.2%; 60+ age-group: mean CFRdiff = -3.9%; 95% credible intervals -5.3% to -2.4%). At the country level, seven of the twenty SSA countries reported significantly lower CFRs among women than men overall. Moreover, corresponding to the age-specific datasets, significantly lower CFRs in women than men were observed in the 60+ age-group in seven countries and 40-59 age-group in one country. Conclusions>Sex and age are important predictors of COVID-19 mortality. Countries should prioritize the collection and use of sex-disaggregated data to understand the evolution of the pandemic. This is essential to design public health interventions and ensure that policies promote a gender sensitive public health response. Summary BoxO_ST_ABSWhat is already known on this topicC_ST_ABSO_LILittle is known on the impact of COVID-19 among different sexes and age-groups in sub-Saharan Africa (SSA). C_LIO_LIThe availability of data on COVID-19 cases and deaths, disaggregated by both age and sex from the WHO African region has been scarce. C_LIO_LIIn most of the non-African countries, sex-specific COVID-19 severity and mortality were substantially worse for men than for women, during the first wave of the novel coronavirus (COVID-19) pandemic. C_LI What this study addsO_LITo the best of our knowledge, this is the largest study focussing on the COVID-19 related fatalities among men and women in SSA, and it confirmed that both sex and age are important predictors of COVID-19 mortality in SSA, similar to other regions. C_LIO_LIIn SSA, overall, men had a higher case fatality rate (CFR) than women. When disaggregated by age, this difference persisted only in individuals aged 40 or more. 7 among the 20 SSA countries included in this study also reported significantly higher CFRs in men than women for the age-aggregated dataset. C_LIO_LIPublic health prevention activities and responses should take into account gender differences in terms of disease severity and mortality, especially among men aged 40 or more in SSA. C_LI
