WHO Global Situational Alert System: a mixed methods multistage approach to identify country-level COVID-19 alerts.

BACKGROUND: Globally, since 1 January 2020 and as of 24 January 2023, there have been over 664 million cases of COVID-19 and over 6.7 million deaths reported to WHO. WHO developed an evidence-based alert system, assessing public health risk on a weekly basis in 237 countries, territories and areas from May 2021 to June 2022. This aimed to facilitate the early identification of situations where healthcare capacity may become overstretched. METHODS: The process involved a three-stage mixed methods approach. In the first stage, future deaths were predicted from the time series of reported cases and deaths to produce an initial alert level. In the second stage, this alert level was adjusted by incorporating a range of contextual indicators and accounting for the quality of information available using a Bayes classifier. In the third stage, countries with an alert level of 'High' or above were added to an operational watchlist and assistance was deployed as needed. RESULTS: Since June 2021, the system has supported the release of more than US$27 million from WHO emergency funding, over 450 000 rapid antigen diagnostic testing kits and over 6000 oxygen concentrators. Retrospective evaluation indicated that the first two stages were needed to maximise sensitivity, where 44% (IQR 29%-67%) of weekly watchlist alerts would not have been identified using only reported cases and deaths. The alerts were timely and valid in most cases; however, this could only be assessed on a non-representative sample of countries with hospitalisation data available. CONCLUSIONS: The system provided a standardised approach to monitor the pandemic at the country level by incorporating all available data on epidemiological analytics and contextual assessments. While this system was developed for COVID-19, a similar system could be used for future outbreaks and emergencies, with necessary adjustments to parameters and indicators.

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 WHO 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 urbanised 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 prioritise 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.

COVID-19 pandemic in Africa's island nations during the first 9 months: a descriptive study of variation in patterns of infection, severe disease, and response measures.

The geographic and economic characteristics unique to island nations create a different set of conditions for, and responses to, the spread of a pandemic compared with those of mainland countries. Here, we aimed to describe the initial period of the COVID-19 pandemic, along with the potential conditions and responses affecting variation in the burden of infections and severe disease burden, across the six island nations of the WHO's Africa region: Cabo Verde, Comoros, Madagascar, Mauritius, São Tomé e Príncipe and Seychelles. We analysed the publicly available COVID-19 data on confirmed cases and deaths from the beginning of the pandemic through 29 November 2020. To understand variation in the course of the pandemic in these nations, we explored differences in their economic statuses, healthcare expenditures and facilities, age and sex distributions, leading health risk factors, densities of the overall and urban populations and the main industries in these countries. We also reviewed the non-pharmaceutical response measures implemented nationally. We found that the burden of SARS-CoV-2 infection was reduced by strict early limitations on movement and biased towards nations where detection capacity was higher, while the burden of severe COVID-19 was skewed towards countries that invested less in healthcare and those that had older populations and greater prevalence of key underlying health risk factors. These findings highlight the need for Africa's island nations to invest more in healthcare and in local testing capacity to reduce the need for reliance on border closures that have dire consequences for their economies.

COVID-19 mortality in women and men in sub-Saharan Africa: a cross-sectional study.

INTRODUCTION: Since sex-based biological and gender factors influence COVID-19 mortality, we wanted to investigate the difference in mortality rates between women and men in sub-Saharan Africa (SSA). METHOD: We included 69 580 cases of COVID-19, stratified by sex (men: n=43 071; women: n=26 509) and age (0-39 years: n=41 682; 40-59 years: n=20 757; 60+ years: n=7141), from 20 member nations of the WHO African region until 1 September 2020. We computed the SSA-specific and country-specific case fatality rates (CFRs) and sex-specific CFR differences across various age groups, using a Bayesian approach. RESULTS: A total of 1656 deaths (2.4% of total cases reported) were reported, with men accounting for 70.5% of total deaths. In SSA, women had a lower CFR than men (mean [Formula: see text] = -0.9%; 95% credible intervals (CIs) -1.1% to -0.6%). The mean CFR estimates increased with age, with the sex-specific CFR differences being significant among those aged 40 years or more (40-59 age group: mean [Formula: see text] = -0.7%; 95% CI -1.1% to -0.2%; 60+ years age group: mean [Formula: see text] = -3.9%; 95% CI -5.3% to -2.4%). At the country level, 7 of the 20 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+ years age group in seven countries and 40-59 years age group in one country. CONCLUSIONS: Sex and age are important predictors of COVID-19 mortality globally. Countries should prioritise the collection and use of sex-disaggregated data so as to design public health interventions and ensure that policies promote a gender-sensitive public health response.

High prevalence and diversity of hepatitis B and hepatitis delta virus in Gabon.

Although central Africa is classified as having a high endemicity of hepatitis B virus (HBV) and hepatitis D virus (HDV) infection, there is paucity of prevalence studies. For the first time on a country-wide level in Central Africa, we show in Gabon an overall 7.4% prevalence of Hepatitis B surface antigen (HBsAg) and that more than 25% of the HBsAg-positive population are infected by HDV. Although HBV prevalence did not differ significantly between provinces, there is a north-south split in the distribution of HDV seroprevalence, with the highest rates (>66.0%) correlating with the presence of specific ethnic groups in the northeastern provinces. Genotyping revealed high genetic diversity of the HBV and HDV strains circulating in Gabon, including many restricted to this region of the globe. This work confirmed that high exposure to HBV and HDV infection reported in selected regions of Gabon holds true across the whole country.

Might Interspecific Interactions between Pathogens Drive Host Evolution? The Case of Plasmodium Species and Duffy-Negativity in Human Populations.

Malarial infections have long been recognized as a driver of human evolution, as demonstrated by the influence of Plasmodium falciparum on sickle-cell anemia persistence. Duffy-negativity is another blood disorder thought to have been selected because it confers nearly complete resistance against Plasmodium vivax infection. Recent evidence suggests that the benefits of being Duffy-negative cannot be expected to play a strong selective pressure on humans, whereas its costs cannot be considered as negligible. Here, we suggest that the cross-talk between P. falciparum and P. vivax in coinfected children could represent the most parsimonious explanation of the frequency of Duffy-negativity. We discuss how this new hypothesis could be tested and call for a reconsideration of the evolution of the Duffy-negative group.