The World Mortality Dataset: Tracking excess mortality across countries during the COVID-19 pandemic

Conventional and frugal methods of estimating COVID-19-related excess deaths and undercount factors

Across the world, the officially reported number of COVID-19 deaths is likely an undercount. Establishing true mortality is key to improving data transparency and strengthening public health systems to tackle future disease outbreaks. In this study, we estimated excess deaths during the COVID-19 pandemic in the Pune region of India. Excess deaths are defined as the number of additional deaths relative to those expected from pre-COVID-19-pandemic trends. We integrated data from: (a) epidemiological modeling using pre-pandemic all-cause mortality data, (b) discrepancies between media-reported death compensation claims and official reported mortality, and (c) the "wisdom of crowds" public surveying. Our results point to an estimated 14,770 excess deaths [95% CI 9820-22,790] in Pune from March 2020 to December 2021, of which 9093 were officially counted as COVID-19 deaths. We further calculated the undercount factor-the ratio of excess deaths to officially reported COVID-19 deaths. Our results point to an estimated undercount factor of 1.6 [95% CI 1.1-2.5]. Besides providing similar conclusions about excess deaths estimates across different methods, our study demonstrates the utility of frugal methods such as the analysis of death compensation claims and the wisdom of crowds in estimating excess mortality.

Emotional and Financial Stressors in New York City During the COVID-19 Pandemic: A Consecutive Cross-Sectional Analysis

Mental and financial hardship during the COVID-19 pandemic in New York City was severe, but how vulnerable groups have been disproportionately impacted is incompletely understood. In partnership with community stakeholders, we administered a web-based survey to a convenience sample of New York City residents (18 + years) from May 2020 to April 2021 to evaluate their financial and emotional stressors. We analyzed outcomes by race, ethnicity, and education level. A total of 1854 adults completed the survey across three consecutive non-overlapping samples. Fifty-five percent identified other than non-Latinx White. Sixty-four percent reported emotional stress; 38%, 32%, and 32% reported symptoms of anxiety, depression, and post-traumatic stress disorder respectively; and 21% reported a large adverse financial impact. The leading unmet needs were mental health and food services (both 19%), and health services (18%). Need for both resources grew over time. Adverse financial impact directly correlated with presence of all four adverse mental health outcomes above. In multivariate analysis, non-White race and lack of college degree were associated with adverse financial impact, whereas LGBT identity and lack of college degree were associated with mental health impact. Throughout the COVID-19 pandemic, participants in this research demonstrated a large and growing mental and financial strain, disproportionately associated with lower education level, non-White race, and LGBT status. Our findings suggest an urgent need to differentially target COVID-19 mental health and resource support in New York City to persons in these vulnerable communities.

Autopsy findings in cases of fatal COVID-19 vaccine-induced myocarditis

COVID-19 vaccines have been linked to myocarditis, which, in some circumstances, can be fatal. This systematic review aims to investigate potential causal links between COVID-19 vaccines and death from myocarditis using post-mortem analysis. We performed a systematic review of all published autopsy reports involving COVID-19 vaccination-induced myocarditis through 3 July 2023. All autopsy studies that include COVID-19 vaccine-induced myocarditis as a possible cause of death were included. Causality in each case was assessed by three independent physicians with cardiac pathology experience and expertise. We initially identified 1691 studies and, after screening for our inclusion criteria, included 14 papers that contained 28 autopsy cases. The cardiovascular system was the only organ system affected in 26 cases. In two cases, myocarditis was characterized as a consequence from multisystem inflammatory syndrome. The mean age of death was 44.4 years old. The mean and median number of days from last COVID-19 vaccination until death were 6.2 and 3 days, respectively. We established that all 28 deaths were most likely causally linked to COVID-19 vaccination by independent review of the clinical information presented in each paper. The temporal relationship, internal and external consistency seen among cases in this review with known COVID-19 vaccine-induced myocarditis, its pathobiological mechanisms, and related excess death, complemented with autopsy confirmation, independent adjudication, and application of the Bradford Hill criteria to the overall epidemiology of vaccine myocarditis, suggests that there is a high likelihood of a causal link between COVID-19 vaccines and death from myocarditis.

Comorbid Conditions in a Cohort of Inpatients with SARS-CoV-2 and their Association with In-Hospital Mortality During the Early Phases of the Pandemic

Introduction: Studies determined that age and associated comorbidities are associated with worse outcomes for COVID-19 patients. The aim of the present study is to examine previous electronic health records of SARS-CoV-2 patients to identify which chronic conditions are associated with in-hospital mortality in a nationally representative sample. Materials and Methods: The actual study is a cross-sectional analysis of SARS-CoV-2 infected patients who were treated in repurposed hospitals. The study includes a cohort of patients treated from 06-11-2020 to 15-03-2021 for COVID-19 associated pneumonia. To examine the presence of comorbidities, electronic health records were examined and analyzed. Results: A total of 1486 in-patients were treated in the specified period, out of which 1237 met the criteria for case. The median age of the sample was 65 years. The overall in-hospital mortality in the sample was 25.5%, while the median length of stay was 11 days. From whole sample, 16.0% of the patients did not have established diagnoses in their electronic records, while the most prevalent coexisting condition was arterial hypertension (62.7%), followed by diabetes mellitus (27.3%). The factors of age, male gender, and the number of diagnoses showed a statistically significant increase in odds ratio (OR) for in-hospital mortality. The presence of chronic kidney injury was associated with the highest increase of OR (by 3.37) for in-hospital mortality in our sample. Conclusion: The study reaffirms the findings that age, male gender, and the presence of comorbidities are associated with in-hospital mortality in COVID-19 treated and unvaccinated patients. Our study suggests that chronic kidney injury showed strongest association with the outcome, when adjusted for age, gender, and coexisting comorbidities.

A systematic review of excess all-cause mortality estimation studies in India during COVID-19 pandemic

Background

Mortality statistics are fundamental to understand the magnitude of the COVID-19 pandemic. Due to limitation of real-time data availability, researchers had used mathematical models to estimate excess mortality globally during COVID-19 pandemic. As they demonstrated variations in scope, assumptions, estimations, and magnitude of the pandemic, and hence raised a controversy all over the world. This paper aims to review the mathematical models and their estimates of mortality due to COVID-19 in the Indian context.

Methods

The PRISMA and SWiM guidelines were followed to the best possible extent. A two-step search strategy was used to identify studies that estimated excess deaths from January 2020 to December 2021 on Medline, Google Scholar, MedRxiv and BioRxiv available until 0100 h, 16 May 2022 (IST). We selected 13 studies based on a predefined criteria and extracted data on a standardised, pre-piloted form by two investigators, independently. Any discordance was resolved through consensus with a senior investigator. Estimated excess mortality was analysed using statistical software and depicted using appropriate graphs.

Results

Significant variations in scope, population, data sources, time period, and modelling strategies existed across studies along with a high risk of bias. Most of the models were based on Poisson regression. Predicted excess mortality by various models ranged from 1.1 to 9.5 million.

Conclusion

The review presents a summary of all the estimates of excess deaths and is important to understand the different strategies used for estimation, and it highlights the importance of data availability, assumptions, and estimates.

Estimating excess mortalities due to the COVID-19 pandemic in Malaysia between January 2020 and September 2021

Excess mortalities are a more accurate indicator of true COVID-19 disease burden. This study aims to investigate levels of excess all-cause mortality and their geographic, age and sex distributions between January 2020-September 2021. National mortality data between January 2016 and September 2021 from the Department of Statistics Malaysia was utilised. Baseline mortality was estimated using the Farrington algorithm and data between 1 January 2016 and 31 December 2019. The occurrence of excess all-cause mortality by geographic-, age- and sex-stratum was examined from 1 January 2020 to 30 September 2021. A sub-analysis was also conducted for road-traffic accidents, ethnicity and nationality. Malaysia had a 5.5-23.7% reduction in all-cause mortality across 2020. A reversal is observed in 2021, with an excess of 13.0-24.0%. Excess mortality density is highest between July and September 2021. All states and sexes reported excess trends consistent with the national trends. There were reductions in all all-cause mortalities in individuals under the age of 15 (0.4-8.1%) and road traffic accident-related mortalities (36.6-80.5%). These reductions were higher during the first Movement Control Order in 2020. Overall, there appears to be a reduction in all-cause mortality for Malaysia in 2020. This trend is reversed in 2021, with excess mortalities being observed. Surveillance of excess mortalities can allow expedient detection of aberrant events allowing timely health system and public health responses.

Macroeconomic Effects of COVID-19 Across the World Income Distribution

The macroeconomic effects of the COVID-19 pandemic were most severe for emerging market economies, representing the middle of the world income distribution. This paper provides a quantitative economic theory for why emerging markets fared worse, on average, relative to advanced economies and low-income countries. To do so we adapt a workhorse incomplete-markets macro model to include epidemiological dynamics alongside key economic and demographic characteristics that distinguish countries of different income levels. We focus in particular on differences in lockdown stringency, public insurance programs, age distributions, healthcare capacity, and the sectoral composition of employment. The calibrated model correctly predicts the larger output losses and greater fatalities in emerging market economies, matching the data. Quantitatively, emerging markets fared especially poorly due to their high employment share in occupations requiring social interactions and their low level of pubic transfers, which leads economically vulnerable households to continue working in the market rather than sheltering at home. Low-income countries fared relatively better due mainly to their younger populations, whom are less susceptible to disease, and larger agricultural sectors, which require fewer social interactions.

Coronavirus disease 2019 (COVID-19) excess mortality outcomes associated with pandemic effects study (COPES): A systematic review and meta-analysis

Background and aim

With the Coronavirus Disease 2019 (COVID-19) pandemic continuing to impact healthcare systems around the world, healthcare providers are attempting to balance resources devoted to COVID-19 patients while minimizing excess mortality overall (both COVID-19 and non-COVID-19 patients). To this end, we conducted a systematic review (SR) to describe the effect of the COVID-19 pandemic on all-cause excess mortality (COVID-19 and non-COVID-19) during the pandemic timeframe compared to non-pandemic times.

Methods

We searched EMBASE, Cochrane Database of SRs, MEDLINE, Cumulative Index to Nursing and Allied Health Literature (CINAHL) and Cochrane Controlled Trials Register (CENTRAL), from inception (1948) to December 31, 2020. We used a two-stage review process to screen/extract data. We assessed risk of bias using Newcastle-Ottawa Scale (NOS). We used Critical Appraisal and Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology.

Results

Of 11,581 citations, 194 studies met eligibility. Of these studies, 31 had mortality comparisons (n = 433,196,345 participants). Compared to pre-pandemic times, during the COVID-19 pandemic, our meta-analysis demonstrated that COVID-19 mortality had an increased risk difference (RD) of 0.06% (95% CI: 0.06-0.06% p < 0.00001). All-cause mortality also increased [relative risk (RR): 1.53, 95% confidence interval (CI): 1.38-1.70, p < 0.00001] alongside non-COVID-19 mortality (RR: 1.18, 1.07-1.30, p < 0.00001). There was "very low" certainty of evidence through GRADE assessment for all outcomes studied, demonstrating the evidence as uncertain.

Interpretation

The COVID-19 pandemic may have caused significant increases in all-cause excess mortality, greater than those accounted for by increases due to COVID-19 mortality alone, although the evidence is uncertain.

Systematic review registration

[https://www.crd.york.ac.uk/prospero/#recordDetails], identifier [CRD42020201256].

COVID-19 and excess mortality in Russia: Regional estimates of life expectancy losses in 2020 and excess deaths in 2021

Accurately counting the human cost of the COVID-19 at both the national and regional level is a policy priority. The Russian Federation currently reports one of the higher COVID-19 mortality rates in the world; but estimates of mortality differ significantly. Using a statistical method accounting for changes in the population age structure, we present the first national and regional estimates of excess mortality for 2021; calculations of excess mortality by age, gender, and urban/rural status for 2020; and mean remaining years of life expectancy lost at the regional level. We estimate that there were 351,158 excess deaths in 2020 and 678,022 in 2021 in the Russian Federation; and, in 2020, around 2.0 years of life expectancy lost. While the Russian Federation exhibits very high levels of excess mortality compared to other countries, there is a wide degree of regional variation: in 2021, excess deaths expressed as a percentage of expected deaths at the regional level range from 27% to 52%. Life expectancy loss is generally greater for males; while excess mortality is greater in urban areas. For Russia as whole, an average person who died due to the pandemic in 2020 would have otherwise lived for a further 14 more years (and as high as 18 years in some regions), disproving the widely held view that excess mortality during the pandemic period was concentrated among those with few years of life remaining-especially for females. At a regional level, less densely populated, more remote regions, rural regions appear to have fared better regarding excess mortality and life expectancy loss-however, a part of this differential could be owing to measurement issues. The calculations demonstrate more clearly the true degree of the human cost of the pandemic in the Russian Federation.

Salivary Antibody Response of COVID-19 in Vaccinated and Unvaccinated Young Adult Populations

COVID-19 is a terrible pandemic sweeping the whole world with more than 600 million confirmed cases and 6 million recorded deaths. Vaccination was identified as the sole option that could help in combatting the disease. In this study, SARS-CoV-2 antibodies were assessed in the saliva of vaccinated participants (Covaxin and Covishield) through enzyme-linked sorbent assay (ELISA). The IgG antibody titres in females were significantly greater than those of males. The total antibody titres of vaccinated individuals were greater than those of unvaccinated participants, although not statistically significant. Individuals who had completed both doses of vaccination had higher antibody levels than those who had received a single dose. People who had experienced COVID-19 after vaccination had better immunity compared to those who were unvaccinated with COVID-19 history. Thus, SARS-CoV-2 spike-specific antibodies were successfully demonstrated in saliva samples, and knowledge about the immunity triggered by the vaccines can assist in making informed choices.

Excess Mortality during the COVID-19 Pandemic in Cities of Chile: Magnitude, Inequalities, and Urban Determinants

We estimated excess mortality in Chilean cities during the COVID-19 pandemic and its association with city-level factors. We used mortality, and social and built environment data from the SALURBAL study for 21 Chilean cities, composed of 81 municipalities or "comunas", grouped in 4 macroregions. We estimated excess mortality by comparing deaths from January 2020 up to June 2021 vs 2016-2019, using a generalized additive model. We estimated a total of 21,699 (95%CI 21,693 to 21,704) excess deaths across the 21 cities. Overall relative excess mortality was highest in the Metropolitan (Santiago) and the North regions (28.9% and 22.2%, respectively), followed by the South and Center regions (17.6% and 14.1%). At the city-level, the highest relative excess mortality was found in the Northern cities of Calama and Iquique (around 40%). Cities with higher residential overcrowding had higher excess mortality. In Santiago, capital of Chile, municipalities with higher educational attainment had lower relative excess mortality. These results provide insight into the heterogeneous impact of COVID-19 in Chile, which has served as a magnifier of preexisting urban health inequalities, exhibiting different impacts between and within cities. Delving into these findings could help prioritize strategies addressed to prevent deaths in more vulnerable communities.

Leading causes of excess mortality in Mexico during the COVID-19 pandemic 2020-2021: A death certificates study in a middle-income country

Background

The death toll after SARS-CoV-2 emergence includes deaths directly or indirectly associated with COVID-19. Mexico reported 325,415 excess deaths, 34.4% of them not directly related to COVID-19 in 2020. In this work, we aimed to analyse temporal changes in the distribution of the leading causes of mortality produced by COVID-19 pandemic in Mexico to understand excess mortality not directly related to the virus infection.

Methods

We did a longitudinal retrospective study of the leading causes of mortality and their variation with respect to cause-specific expected deaths in Mexico from January 2020 through December 2021 using death certificate information. We fitted a Poisson regression model to predict cause-specific mortality during the pandemic period, based on the 2015–2019 registered mortality. We estimated excess deaths as a weekly difference between expected and observed deaths and added up for the entire period. We expressed all-cause and cause-specific excess mortality as a percentage change with respect to predicted deaths by our model.

Findings

COVID-19 was the leading cause of death in 2020–2021 (439,582 deaths). All-cause total excess mortality was 600,590 deaths (38⋅2% [95% CI: 36·0 to 40·4] over expected). The largest increases in cause-specific mortality, occurred in diabetes (36·8% over expected), respiratory infections (33·3%), ischaemic heart diseases (32·5%) and hypertensive diseases (25·0%). The cause-groups that experienced significant decreases with respect to the expected pre-pandemic mortality were infectious and parasitic diseases (-20·8%), skin diseases (-17·5%), non-traffic related accidents (-16·7%) and malignant neoplasm (-5·3%).

Interpretation

Mortality from COVID-19 became the first cause of death in 2020–2021, the increase in other causes of death may be explained by changes in the health service utilization patterns caused by hospital conversion or fear of the population using them. Cause-misclassification cannot be ruled out.

Funding

This study was funded by Conacyt.

Estimation of Excess Deaths Associated With the COVID-19 Pandemic in Istanbul, Turkey

Background and Objectives

The official number of daily cases and deaths are the most prominent indicators used to plan actions against the COVID-19 pandemic but are insufficient to see the real impact. Official numbers vary due to testing policy, reporting methods, etc. Therefore, critical interventions are likely to lose their effectiveness and better-standardized indicators like excess deaths/mortality are needed. In this study, excess deaths in Istanbul were examined and a web-based monitor was developed.

Methods

Daily all-cause deaths data between January 1, 2015- November 11, 2021 in Istanbul is used to estimate the excess deaths. Compared to the pre-pandemic period, the % increase in the number of deaths was calculated as the ratio of excess deaths to expected deaths (P-Scores). The ratio of excess deaths to official figures (T) was also examined.

Results

The total number of official and excess deaths in Istanbul are 24.218 and 37.514, respectively. The ratio of excess deaths to official deaths is 1.55. During the first three death waves, maximum P-Scores were 71.8, 129.0, and 116.3% respectively.

Conclusion

Excess mortality in Istanbul is close to the peak scores in Europe. 38.47% of total excess deaths could be considered as underreported or indirect deaths. To re-optimize the non-pharmaceutical interventions there is a need to monitor the real impact beyond the official figures. In this study, such a monitoring tool was created for Istanbul. The excess deaths are more reliable than official figures and it can be used as a gold standard to estimate the impact more precisely.

The Global Health Security Index: Another Look

The Global Health Security Index (GHSI) was published in October 2019 (after more than 2 years in preparation); at about the same time that the COVID-19 pandemic (COVID) started. The GHSI was intended to score countries' pandemic preparedness. Within months of the start of the pandemic, articles began to be published that claimed to assess the GHSI's validity. They correlated GHSI scores with countries' COVID per capita death rates. They showed that the better prepared a country, the higher the death rate: a result that was counter to what would have been expected. This article takes another look at the GHSI by exploring the relationship in major European Union countries plus the United Kingdom. The analysis reported here confirms that early on the higher the GHSI score, the higher the COVID per capita death rate (r = 0.52, P < 0.05). But, by the end of 2020, there was no correlation. By July 2021, the correlation was in the expected direction: the higher the GHSI score, the lower the COVID per capita death rate (r = -0.55, P < 0.05); ditto case fatality rate (r = -0.74, P < 0.01). Further, the GHSI was better correlated with excess mortality, the best measure of pandemic impact (r = -0.69, P < 0.01). However, per capita GDP was as good a predictor of excess mortality (r = -0.71, P < 0.01) and the Health System Performance Index of case fatality rate (r = -0.71; P < 0.01). By the end of 2021, the correlation between GHSI scores and COVID per capita death rates had strengthened (r = -0.71; P < 0.01). This exploratory analysis is not intended to produce generalizable conclusions about the effectiveness of countries' COVID pandemic response management, which continues to evolve and hence can only be properly assessed after the pandemic has ended. Nevertheless, the following conclusions would seem to be warranted: 1) there seems to have been a rush to judge, or, at least, to publish, and 2) the validity of any forward looking pandemic preparedness score depends not only on being able to assess countries' capabilities but also being able to forecast what governments will (and will not) do in any given situation, a seemingly quixotic quest.

Heterogeneity in subnational mortality in the context of the COVID-19 pandemic: the case of Belgian districts in 2020

BACKGROUND

The COVID-19 pandemic has led to major shocks in mortality trends in many countries. Yet few studies have evaluated the heterogeneity of the mortality shocks at the sub-national level, rigorously accounting for the different sources of uncertainty.

METHODS

Using death registration data from Belgium, we first assess change in the heterogeneity of districts' standardized mortality ratios in 2020, when compared to previous years. We then measure the shock effect of the pandemic using district-level values of life expectancy, comparing districts' observed and projected life expectancy, accounting for all sources of uncertainty (stemming from life-table construction at district level and from projection methods at country and district levels). Bayesian modelling makes it easy to combine the different sources of uncertainty in the assessment of the shock. This is of particular interest at a finer geographical scale characterized by high stochastic variation in annual death counts.

RESULTS

The heterogeneity in the impact of the pandemic on all-cause mortality across districts is substantial: while some districts barely show any impact, the Bruxelles-Capitale and Mons districts experienced a decrease in life expectancy at birth of 2.24 (95% CI:1.33-3.05) and 2.10 (95% CI:0.86-3.30) years, respectively. The year 2020 was associated with an increase in the heterogeneity of mortality levels at a subnational scale in comparison to past years, measured in terms of both standardized mortality ratios and life expectancies at birth. Decisions on uncertainty thresholds have a large bearing on the interpretation of the results.

CONCLUSION

Developing sub-national mortality estimates taking careful account of uncertainty is key to identifying which areas have been disproportionately affected.

The World Health Organization's Frontline Support to Countries During the COVID-19 Pandemic in 2020

The World Health Organization (WHO) declared the SARS-CoV-2 outbreak a Public Health Emergency of International Concern (PHEIC) on January 30, 2020. WHO rapidly scaled up its response including through its 149 country offices to support Member States prepare for and respond to the COVID-19 pandemic. This article describes the frontline role of the WHO Country Offices (WCOs) and demonstrates that WHO utilized its existing country presence to deliver its global program of work during this unprecedented emergency. Using data collected from the 2020 WHO COVID-19 Strategic Preparedness and Response Plan monitoring and evaluation framework assessments, plus data collected in a quantitative survey completed by 149 WCOs during 2020, this article describes how WHO supported national authorities and partners through leadership, policy dialogue, strategic support, technical assistance, and service delivery, in line with WHO's current 5-year strategic plan, the WHO 13th General Programme of Work 2019–2023. Country level case studies were used to further illustrate actions taken by WCOs. WHO's achievements notwithstanding, the Organization faced several key challenges in the first year of the response. Recommendations to enhance WHO presence in countries for future emergency prevention, preparedness and response, from several independent reviews, were presented to the World Health Assembly in May 2021 and relevant recommendations are presented in this article.

Review on COVID-19 diagnosis models based on machine learning and deep learning approaches

COVID-19 is the disease evoked by a new breed of coronavirus called the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Recently, COVID-19 has become a pandemic by infecting more than 152 million people in over 216 countries and territories. The exponential increase in the number of infections has rendered traditional diagnosis techniques inefficient. Therefore, many researchers have developed several intelligent techniques, such as deep learning (DL) and machine learning (ML), which can assist the healthcare sector in providing quick and precise COVID-19 diagnosis. Therefore, this paper provides a comprehensive review of the most recent DL and ML techniques for COVID-19 diagnosis. The studies are published from December 2019 until April 2021. In general, this paper includes more than 200 studies that have been carefully selected from several publishers, such as IEEE, Springer and Elsevier. We classify the research tracks into two categories: DL and ML and present COVID-19 public datasets established and extracted from different countries. The measures used to evaluate diagnosis methods are comparatively analysed and proper discussion is provided. In conclusion, for COVID-19 diagnosing and outbreak prediction, SVM is the most widely used machine learning mechanism, and CNN is the most widely used deep learning mechanism. Accuracy, sensitivity, and specificity are the most widely used measurements in previous studies. Finally, this review paper will guide the research community on the upcoming development of machine learning for COVID-19 and inspire their works for future development. This review paper will guide the research community on the upcoming development of ML and DL for COVID-19 and inspire their works for future development.

Burden of Covid-19 restrictions: National, regional and global estimates

BACKGROUND

A growing literature has documented the high global morbidity, mortality and mental health burden associated with the current Covid-19 pandemic. In this paper, we aimed to quantify the total utility and quality of life loss resulting from Covid-19-related government restrictions imposed at the national, regional and global levels.

METHODS

We conducted quality of life online surveys in France, India, Italy, UK and the United States of America between June 21st and September 13th 2021, and used regression models to estimate the average quality of life loss due to light and severe restrictions in these countries. We then combined estimated disutility weights from the pooled sample with the latest data on Covid-19 restrictions exposure in each country to estimate the total disutility generated by restrictions at the national, regional and global level. We also embedded a discrete choice experiment (DCE) into the online survey to estimate average willingness to pay to avoid specific restrictions.

FINDINGS

A total of 947 surveys were completed. Thirty-five percent of respondents were female, and 69.5% were between 18 and 39 years old. The weighted average utility weight was 0.71 (95% CIs 0.69-0.74) for light restrictions, and 0.65 (0.63-0.68) for severe restrictions. At the global scale, this implies a total loss of 3259 million QALYs (95% 3021, 3496) as of September 6th, 2021, with the highest burden in lower and upper middle-income countries. Utility losses appear to be particularly large for closures of schools and daycares as well as restaurants and bars, and seem relatively small for wearing masks and travel restrictions.

INTERPRETATION

The results presented here suggest that the QALY losses due to restrictions are substantial. Future mitigation strategies should try to balance potential reductions in disease transmission achievable through specific measures against their respective impact on quality of life. Additional research is needed to determine differences in restriction-specific disutilities across countries, and to determine optimal policy responses to similar future disease threats.

FUNDING

No funding was received for this project.

Do the Benefits of School Closure Outweigh Its Costs?

School closure has been a common response to COVID-19. Yet, its implementation has hardly ever been based on rigorous analysis of its costs and benefits. We aim to first illustrate the unintended consequences and side effects of school closure, and then discuss the policy and research implications. This commentary frames evidence from the most recent papers on the topic from a public-health epidemiology and disaster risk reduction perspective. In particular, we argue that the benefits of school closure in terms of reduced infection rates should be better compared with its costs in terms of both short- and long-term damage on the physical, mental, and social well-being of children and society at large.

The use of cremation data for timely mortality surveillance: the example of the COVID-19 pandemic in Ontario, Canada

Background

Early estimates of excess mortality are crucial for understanding the impact of COVID-19. However, there is a lag of several months in the reporting of vital statistics mortality data for many jurisdictions, including across Canada. In Ontario, a Canadian province, certification by a coroner is required before cremation can occur, creating real-time mortality data that encompasses the majority of deaths within the province.

Objective

This study aimed to validate the use of cremation data as a timely surveillance tool for all-cause mortality during a public health emergency in a jurisdiction with delays in vital statistics data. Specifically, this study aimed to validate this surveillance tool by determining the stability, timeliness, and robustness of its real-time estimation of all-cause mortality.

Methods

Cremation records from January 2020 until April 2021 were compared to the historical records from 2017 to 2019, grouped according to week, age, sex, and whether COVID-19 was the cause of death. Cremation data were compared to Ontario’s provisional vital statistics mortality data released by Statistics Canada. The 2020 and 2021 records were then compared to previous years (2017-2019) to determine whether there was excess mortality within various age groups and whether deaths attributed to COVID-19 accounted for the entirety of the excess mortality.

Results

Between 2017 and 2019, cremations were performed for 67.4% (95% CI 67.3%-67.5%) of deaths. The proportion of cremated deaths remained stable throughout 2020, even within age and sex categories. Cremation records are 99% complete within 3 weeks of the date of death, which precedes the compilation of vital statistics data by several months. Consequently, during the first wave (from April to June 2020), cremation records detected a 16.9% increase (95% CI 14.6%-19.3%) in all-cause mortality, a finding that was confirmed several months later with cremation data.

Conclusions

The percentage of Ontarians cremated and the completion of cremation data several months before vital statistics did not change meaningfully during the COVID-19 pandemic period, establishing that the pandemic did not significantly alter cremation practices. Cremation data can be used to accurately estimate all-cause mortality in near real-time, particularly when real-time mortality estimates are needed to inform policy decisions for public health measures. The accuracy of this excess mortality estimation was confirmed by comparing it with official vital statistics data. These findings demonstrate the utility of cremation data as a complementary data source for timely mortality information during public health emergencies.

Estimating the SARS-CoV2 infections detection rate and cumulative incidence in the World Health Organization African Region ten months into the pandemic

As of 03 January 2021, the WHO African region is the least affected by the coronavirus disease-2019 (COVID-19) pandemic, accounting for only 2.4% of cases and deaths reported globally. However, concerns abound about whether the number of cases and deaths reported from the region reflect the true burden of the disease and how the monitoring of the pandemic trajectory can inform response measures.

We retrospectively estimated four key epidemiological parameters (the total number of cases, the number of missed cases, the detection rate and the cumulative incidence) using the COVID-19 prevalence calculator tool developed by Resolve to Save Lives. We used cumulative cases and deaths reported during the period 25 February to 31 December 2020 for each WHO Member State in the region as well as population data to estimate the four parameters of interest. The estimated number of confirmed cases in 42 countries out of 47 of the WHO African region included in this study was 13 947 631 [95% confidence interval (CI): 13 334 620–14 635 502] against 1 889 512 cases reported, representing 13.5% of overall detection rate (range: 4.2% in Chad, 43.9% in Guinea). The cumulative incidence of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) was estimated at 1.38% (95% CI: 1.31%–1.44%), with South Africa the highest [14.5% (95% CI: 13.9%–15.2%)] and Mauritius [0.1% (95% CI: 0.099%–0.11%)] the lowest. The low detection rate found in most countries of the WHO African region suggests the need to strengthen SARS-CoV-2 testing capacities and adjusting testing strategies.

Investigating regional excess mortality during 2020 COVID-19 pandemic in selected Latin American countries

In this paper, we measure the effect of the 2020 COVID-19 pandemic wave at the national and subnational levels in selected Latin American countries that were most affected: Brazil, Chile, Ecuador, Guatemala, Mexico, and Peru. We used publicly available monthly mortality data to measure the impacts of the pandemic using excess mortality for each country and its regions. We compare the mortality, at national and regional levels, in 2020 to the mortality levels of recent trends and provide estimates of the impact of mortality on life expectancy at birth. Our findings indicate that from April 2020 on, mortality exceeded its usual monthly levels in multiple areas of each country. In Mexico and Peru, excess mortality was spreading through many areas by the end of the second half of 2020. To a lesser extent, we observed a similar pattern in Brazil, Chile, and Ecuador. We also found that as the pandemic progressed, excess mortality became more visible in areas with poorer socioeconomic and sanitary conditions. This excess mortality has reduced life expectancy across these countries by 2-10 years. Despite the lack of reliable information on COVID-19 mortality, excess mortality is a useful indicator for measuring the effects of the coronavirus pandemic, especially in the context of Latin American countries, where there is still a lack of good information on causes of death in their vital registration systems.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1186/s41118-021-00139-1.

What Could Explain the Lower COVID-19 Burden in Africa despite Considerable Circulation of the SARS-CoV-2 Virus?

The differential spread and impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), causing Coronavirus Disease 2019 (COVID-19), across regions is a major focus for researchers and policy makers. Africa has attracted tremendous attention, due to predictions of catastrophic impacts that have not yet materialized. Early in the pandemic, the seemingly low African case count was largely attributed to low testing and case reporting. However, there is reason to consider that many African countries attenuated the spread and impacts early on. Factors explaining low spread include early government community-wide actions, population distribution, social contacts, and ecology of human habitation. While recent data from seroprevalence studies posit more extensive circulation of the virus, continuing low COVID-19 burden may be explained by the demographic pyramid, prevalence of pre-existing conditions, trained immunity, genetics, and broader sociocultural dynamics. Though all these prongs contribute to the observed profile of COVID-19 in Africa, some provide stronger evidence than others. This review is important to expand what is known about the differential impacts of pandemics, enhancing scientific understanding and gearing appropriate public health responses. Furthermore, it highlights potential lessons to draw from Africa for global health on assumptions regarding deadly viral pandemics, given its long experience with infectious diseases.

Covid-19, non-Covid-19 and excess mortality rates not comparable across countries

Evidence that more people in some countries and fewer in others are dying because of the pandemic, than is reflected by reported coronavirus disease 2019 (Covid-19) mortality rates, is derived from mortality data. Using publicly available databases, deaths attributed to Covid-19 in 2020 and all deaths for the years 2015–2020 were tabulated for 35 countries together with economic, health, demographic and government response stringency index variables. Residual mortality rates (RMR) in 2020 were calculated as excess mortality minus reported mortality rates due to Covid-19 where excess deaths were observed deaths in 2020 minus the average for 2015–2019. Differences in RMR are differences not attributed to reported Covid-19. For about half the countries, RMR's were negative and for half, positive. The absolute rates in some countries were double those in others. In a regression analysis, population density and proportion of female smokers were positively associated with both Covid-19 and excess mortality while the human development index and proportion of male smokers were negatively associated with both. RMR was not associated with any of the investigated variables. The results show that published data on mortality from Covid-19 cannot be directly comparable across countries. This may be due to differences in Covid-19 death reporting and in addition, the unprecedented public health measures implemented to control the pandemic may have produced either increased or reduced excess deaths due to other diseases. Further data on cause-specific mortality is required to determine the extent to which residual mortality represents non-Covid-19 deaths and to explain differences between countries.

Excess deaths associated with covid-19 pandemic in 2020: age and sex disaggregated time series analysis in 29 high income countries

OBJECTIVE

To estimate the direct and indirect effects of the covid-19 pandemic on mortality in 2020 in 29 high income countries with reliable and complete age and sex disaggregated mortality data.

DESIGN

Time series study of high income countries.

SETTING

Austria, Belgium, Czech Republic, Denmark, England and Wales, Estonia, Finland, France, Germany, Greece, Hungary, Israel, Italy, Latvia, Lithuania, the Netherlands, New Zealand, Northern Ireland, Norway, Poland, Portugal, Scotland, Slovakia, Slovenia, South Korea, Spain, Sweden, Switzerland, and United States.

PARTICIPANTS

Mortality data from the Short-term Mortality Fluctuations data series of the Human Mortality Database for 2016-20, harmonised and disaggregated by age and sex.

INTERVENTIONS

Covid-19 pandemic and associated policy measures.

MAIN OUTCOME MEASURES

Weekly excess deaths (observed deaths versus expected deaths predicted by model) in 2020, by sex and age (0-14, 15-64, 65-74, 75-84, and ≥85 years), estimated using an over-dispersed Poisson regression model that accounts for temporal trends and seasonal variability in mortality.

RESULTS

An estimated 979 000 (95% confidence interval 954 000 to 1 001 000) excess deaths occurred in 2020 in the 29 high income countries analysed. All countries had excess deaths in 2020, except New Zealand, Norway, and Denmark. The five countries with the highest absolute number of excess deaths were the US (458 000, 454 000 to 461 000), Italy (89 100, 87 500 to 90 700), England and Wales (85 400, 83 900 to 86 800), Spain (84 100, 82 800 to 85 300), and Poland (60 100, 58 800 to 61 300). New Zealand had lower overall mortality than expected (-2500, -2900 to -2100). In many countries, the estimated number of excess deaths substantially exceeded the number of reported deaths from covid-19. The highest excess death rates (per 100 000) in men were in Lithuania (285, 259 to 311), Poland (191, 184 to 197), Spain (179, 174 to 184), Hungary (174, 161 to 188), and Italy (168, 163 to 173); the highest rates in women were in Lithuania (210, 185 to 234), Spain (180, 175 to 185), Hungary (169, 156 to 182), Slovenia (158, 132 to 184), and Belgium (151, 141 to 162). Little evidence was found of subsequent compensatory reductions following excess mortality.

CONCLUSION

Approximately one million excess deaths occurred in 2020 in these 29 high income countries. Age standardised excess death rates were higher in men than women in almost all countries. Excess deaths substantially exceeded reported deaths from covid-19 in many countries, indicating that determining the full impact of the pandemic on mortality requires assessment of excess deaths. Many countries had lower deaths than expected in children <15 years. Sex inequality in mortality widened further in most countries in 2020.

Analysis of Risk Factors in COVID-19 Adult Mortality in Russia

BACKGROUND AND OBJECTIVE

Epidemiological data obtained during the ongoing SARS-CoV-2 pandemic suggests that COVID-19 mortality has specific age and gender associations. However, limited epidemiological studies explored specific populational risk factors, including comorbidities, and patient clinical characteristics. The main aim of our retrospective cohort study was to analyze associations between age, gender, and comorbidities in deceased COVID-19 patients.

MATERIALS AND METHODS

A retrospective cohort analysis was performed to assess significant risk factors in adult patients deceased from COVID-19 infection by evaluating Electronic Medical Records and post-mortem analysis in COVID-19 patients deceased between April 2020 to October 2020. All patients underwent post-mortem evaluation along with medical history analysis, including data on disease duration, hospitalization, and clinical peculiarities.

RESULTS

Medical records of 1487 COVID-19 patients revealed that the prevalence of males was higher (by 23%) than females; the median age for males was 71 years of age whereas for females it was 78. The most prevalent comorbid pathologies were: hypertension, obesity, diabetes, and cancer. Males are at significantly increased risk of lethal outcome, even in younger age groups, with comorbid conditions.

CONCLUSION

The study concluded that comorbidities, such as hypertension, obesity, diabetes, cancer are the most important risk factors for comorbid mortality in COVID-19 patients. In addition to lung damage, multiple organ dysfunctions may be a crucial reason for COVID-19 induced death. Special precautions, such as early hospitalization, increased monitoring, and preventative tactics should be taken for at-risk patients.