Does the data tell the true story? A modelling assessment of early COVID-19 pandemic suppression and mitigation strategies in Ghana

Excess mortality during the COVID-19 pandemic in low-and lower-middle-income countries: a systematic review and meta-analysis

BACKGROUND

Although the COVID-19 pandemic claimed a great deal of lives, it is still unclear how it affected mortality in low- and lower-middle-income countries (LLMICs). This review summarized the available literature on excess mortality during the COVID-19 pandemic in LLMICs, including methods, sources of data, and potential contributing factors that might have influenced excess mortality.

METHODS

We conducted a systematic review and meta-analysis on excess mortality during the COVID-19 pandemic in LLMICs in line with the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) 2020 guidelines We searched PubMed, Embase, Web of Science, Cochrane Library, Google Scholar, and Scopus. We included studies published from 2019 onwards with a non-COVID-19 period of at least one year as a comparator. The meta-analysis included studies reporting data on population size, as well as observed and expected deaths. We used the Mantel-Haenszel method to estimate the pooled risk ratio with 95% confidence intervals. The protocol was registered in PROSPERO (ID: CRD42022378267).

RESULTS

The review covered 29 countries, with 10 countries included in the meta-analysis. The pooled meta-analysis included 1,405,128,717 individuals, for which 2,152,474 deaths were expected, and 3,555,880 deaths were reported. Calculated excess mortality was 100.3 deaths per 100,000 population per year, with an excess risk of death of 1.65 (95% CI: 1.649, 1.655, p < 0.001). The data sources used in the studies included civil registration systems, surveys, public cemeteries, funeral counts, obituary notifications, burial site imaging, and demographic surveillance systems. The primary techniques used to estimate excess mortality were statistical forecast modelling and geospatial analysis. One out of the 24 studies found higher excess mortality in urban settings.

CONCLUSION

Our findings demonstrate that excess mortality in LLMICs during the pandemic was substantial. However, estimates of excess mortality are uncertain due to relatively poor data. Understanding the drivers of excess mortality, will require more research using various techniques and data sources.

Decreased influenza activity during the COVID-19 pandemic in Ghana, 2020

Introduction

The COVID-19 pandemic had a significant effect on influenza activity globally. In this study, we analyzed trends of influenza activity in 2020 during the COVID-19 pandemic in Ghana.

Methods

This was a cross-sectional study using active prospective influenza surveillance data from 29 sentinel sites. At the sentinel sites, we enrolled patients presenting with symptoms based on the WHO case definition for influenza-like illness (ILI) and severe acute respiratory illness (SARI). Oro and nasopharyngeal swabs were collected from patients and tested for the presence of influenza viruses using specific primers and probes described by the US-CDC. The percentage of positivity for influenza between 2017-2019 and 2021 was compared to 2020. Using the test for proportions in STATA 17.0 we estimated the difference in influenza activities between two periods.

Results and discussion

Influenza activity occurred in a single wave during the 2020 surveillance season into 2021, September 28 2020-March 7 2021 (week 40, 2020-week 9, 2021). Influenza activity in 2020 was significantly lower compared to previous years (2017- 2019, 2021). Influenza A (H3) was more commonly detected during the early part of the year (December 30, 2019-March 8, 2020), while influenza B Victoria was more commonly detected toward the end of the year (September 28-December 28). In Ghana, adherence to the community mitigation strategies introduced to reduce transmission of SARS-CoV-2, which affected the transmission of other infectious diseases, may have also impacted the transmission of influenza. To the best of our knowledge, this is the first study in Ghana to describe the effect of the COVID-19 pandemic on influenza activity. The continuation and strict adherence to the non-pharmaceutical interventions at the community level can help reduce influenza transmission in subsequent seasons.

Excess mortality during the COVID-19 pandemic in low-income and lower middle-income countries: protocol for a systematic review and meta-analysis

INTRODUCTION

The COVID-19 pandemic has been marked by a massive death toll. However, the overall effect of the pandemic, including potential unintended negative impacts of some control measures, on mortality remains poorly understood in low-income and lower middle-income countries (LLMICs). This review aims to summarise the available literature on excess mortality in LLMICs, focusing on the methods and data sources used in estimating excess mortality and the drivers of excess mortality.

METHODS AND ANALYSIS

We will review the available literature and report results in line with the Preferred Reporting Items for Systematic Review and Meta-Analysis. Searches will be conducted in PubMed, Embase, Web of Science, Cochrane Library, Google Scholar and Scopus. All published studies that report on the estimates of excess mortality in populations of LLMICs will be included. This will include those with a publication date from 2019 onwards and those with at least a 1-year non-COVID-19 period as the comparator in the estimation of excess mortality during the pandemic. There will be no language restrictions on the search. The meta-analysis will include studies with extractable data on excess mortality, methods, population size, and observed and expected deaths. We will use the Mantel-Haenszel method to estimate the pooled risk ratio with 95% CIs.

ETHICS AND DISSEMINATION

As there is no primary data collection, there is no requirement for ethical review. The results will be disseminated through peer-reviewed journal publication and conference presentations.

PROSPERO REGISTRATION NUMBER

CRD42022378267.

Impact of economic policy uncertainty, energy intensity, technological innovation and R&D on CO2 emissions: evidence from a panel of 18 developed economies

This study examines the impact of economic policy uncertainty (EPU) and ecological innovation on carbon (CO₂) emissions in a panel of 18 developed countries from 2005 to 2018 using second-generation time-series panel data techniques. We use three robust long-run estimators, namely two-stage least squares (2SLS), panel generalised method of moments (GMM) and generalised least squares (GLS), to resolve heterogeneity, endogeneity and simultaneity in the panels. We further performed causality tests to ascertain the direction of causality between the variables. Our estimations suggest three innovative findings. First, economic growth contributes significantly and positively to CO₂ emissions; however, this happens at an optimal level of growth after which carbon emission reduces, indicating that our sample exhibits an inverted U-shaped environmental Kuznets curve (EKC) relationship. Second, the impact of EPU on CO₂ emissions is diverse: high levels of EPU have a significant influence on CO₂ emissions only in high-polluting countries but not in low-polluting ones. Thirdly, research and development (R&D), foreign direct investment (FDI), urbanisation and renewable energy (RE) usage were also found to have varying effects on CO₂ emissions. These findings highlight the heterogeneous relationship between carbon emissions and economic indicators even in advanced economies, as the pollution haven hypothesis (PHH) holds true in high-pollution countries while the pollution halo effect holds for low-pollution ones. A key policy implication of this work is that the quest to mitigate emissions should not be a one-size-fits-all approach because not every country's urbanisation rate, FDI inflows, R&D and renewable energy consumption directly affect CO₂ emissions in the face of economic policy uncertainties.

High seroprevalence of SARS-CoV-2 in Burkina-Faso, Ghana and Madagascar in 2021: a population-based study

BACKGROUND

The current COVID-19 pandemic affects the entire world population and has serious health, economic and social consequences. Assessing the prevalence of COVID-19 through population-based serological surveys is essential to monitor the progression of the epidemic, especially in African countries where the extent of SARS-CoV-2 spread remains unclear.

METHODS

A two-stage cluster population-based SARS-CoV-2 seroprevalence survey was conducted in Bobo-Dioulasso and in Ouagadougou, Burkina Faso, Fianarantsoa, Madagascar and Kumasi, Ghana between February and June 2021. IgG seropositivity was determined in 2,163 households with a specificity improved SARS-CoV-2 Enzyme-linked Immunosorbent Assay. Population seroprevalence was evaluated using a Bayesian logistic regression model that accounted for test performance and age, sex and neighbourhood of the participants.

RESULTS

Seroprevalence adjusted for test performance and population characteristics were 55.7% [95% Credible Interval (CrI) 49·0; 62·8] in Bobo-Dioulasso, 37·4% [95% CrI 31·3; 43·5] in Ouagadougou, 41·5% [95% CrI 36·5; 47·2] in Fianarantsoa, and 41·2% [95% CrI 34·5; 49·0] in Kumasi. Within the study population, less than 6% of participants performed a test for acute SARS-CoV-2 infection since the onset of the pandemic.

CONCLUSIONS

High exposure to SARS-CoV-2 was found in the surveyed regions albeit below the herd immunity threshold and with a low rate of previous testing for acute infections. Despite the high seroprevalence in our study population, the duration of protection from naturally acquired immunity remains unclear and new virus variants continue to emerge. This highlights the importance of vaccine deployment and continued preventive measures to protect the population at risk.