Migration from Epi Info to District Health Information Software 2 for Vaccine-Preventable Disease Surveillance - World Health Organization African Region, 2019-2023.

High-quality vaccine-preventable disease (VPD) surveillance data are critical for timely outbreak detection and response. In 2019, the World Health Organization (WHO) African Regional Office (AFRO) began transitioning from Epi Info, a free, CDC-developed statistical software package with limited capability to integrate with other information systems, affecting reporting timeliness and data use, to District Health Information Software 2 (DHIS2). DHIS2 is a free and open-source software platform for electronic aggregate Integrated Disease Surveillance and Response (IDSR) and case-based surveillance reporting. A national-level reporting system, which provided countries with the option to adopt this new system, was introduced. Regionally, the Epi Info database will be replaced with a DHIS2 regional data platform. This report describes the phased implementation from 2019 to the present. Phase one (2019-2021) involved developing IDSR aggregate and case-based surveillance packages, including pilots in the countries of Mali, Rwanda, and Togo. Phase two (2022) expanded national-level implementation to 27 countries and established the WHO AFRO DHIS2 regional data platform. Phase three (from 2023 to the present) activities have been building local capacity and support for country reporting to the regional platform. By February 2024, eight of 47 AFRO countries had adopted both the aggregate IDSR and case-based surveillance packages, and two had successfully transferred VPD surveillance data to the AFRO regional platform. Challenges included limited human and financial resources, the need to establish data-sharing and governance agreements, technical support for data transfer, and building local capacity to report to the regional platform. Despite these challenges, the transition to DHIS2 will support efficient data transmission to strengthen VPD detection, response, and public health emergencies through improved system integration and interoperability.

COVID-19 Mortality in Women and Men in Sub-Saharan Africa: A Cross Sectional Study

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

An in-depth statistical analysis of the COVID-19 pandemic's initial spread in the WHO African region

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.

The toll of COVID-19 on African children: A descriptive analysis on the COVID-19-related morbidity and mortality among the pediatric population in Sub-Saharan Africa

IntroductionSince the beginning of the COVID-19 pandemic, very little data on the epidemiological characteristics among the pediatric population in Africa has been published. This paper examines the age and sex distribution of the morbidity and mortality rate in children with COVID-19 and compares it to the adult population within 15 Sub-Saharan African countries. MethodsA merge line listing dataset using a reverse engineering model shared by countries within the Regional Office for Africa was analyzed. Patients diagnosed within 1 March 2020 and 1 September 2020 with confirmed positive RT-PCR test for SARS-CoV-2 were analyzed. Childrens data were stratified into three age groups: 0-4 years, 5-11 years, and 12-17 years, while adults were combined. The cumulative incidence of cases including its medians and 95% confidence intervals were calculated. Results9% of the total confirmed cases and 2.4% of the reported deaths were pediatric cases. The 12-17 age group in all 15 countries showed the highest cumulative incidence proportion in children. COVID-19 cases in males and females under the age of 18 were evenly distributed. Among adults, a higher case incidence per 100,000 people was observed compared to children. ConclusionThe cases and deaths within the childrens population was smaller than the adult population. These differences can reflect biases in COVID-19 testing protocols and reporting implemented by countries, highlighting the need for more extensive investigation and focus on the effects of COVID-19 in children.