Data Resource Profile: COVerAGE-DB: a global demographic database of COVID-19 cases and deaths

Estimated Deaths Averted in Adults by COVID-19 Vaccination in Select Latin American and Caribbean Countries

Background

The coronavirus disease 2019 (COVID-19) pandemic has had a significant impact on global health, with millions of lives lost worldwide. Vaccination has emerged as a crucial strategy in mitigating the impact of the disease. This study aims to estimate the number of deaths averted through vaccination in Latin America and the Caribbean region (LAC) during the first year and a half of vaccination rollout (January 2021-May 2022).

Methods

Publicly available data on COVID-19 deaths and vaccination rates were used to estimate the total number of deaths averted via vaccination in LAC. Using estimates for number of deaths, number of vaccinated, and vaccine effectiveness, a counterfactual estimated number of deaths observed without vaccination was calculated. Vaccine effectiveness estimates were obtained from published studies. The analysis focused on 17 countries in LAC and considered adults aged 18 years and older.

Results

After accounting for underreporting, the analysis estimated that >1.49 million deaths were caused by COVID-19 in the selected countries during the study period. Without vaccination, the model estimated that between 2.10 and 4.11 million COVID-19 deaths would have occurred. Consequently, vaccination efforts resulted in ∼610 000 to 2.61 million deaths averted.

Conclusions

This study represents the first large-scale, multicenter estimate of population-level vaccine impact on COVID-19 mortality in LAC. The findings underscore the substantial impact of timely and widespread vaccination in averting COVID-19 deaths. These results provide crucial support for vaccination programs aimed at combating epidemic infectious diseases in the region and future pandemics.

Unrecognised COVID-19 deaths in central Europe: The importance of cause-of-death certification for the COVID-19 burden assessment

OBJECTIVE

In Central Europe, the increase in mortality during the COVID-19 pandemic exceeded the number of deaths registered due to coronavirus disease. Excess deaths reported to causes other than COVID-19 may have been due to unrecognised coronavirus disease, the interruptions in care in the overwhelmed health care facilities, or socioeconomic effects of the pandemic and lockdowns. Death certificates provide exhaustive medical information, allowing us to assess the extent of unrecognised COVID-19 deaths.

MATERIALS AND METHODS

Data from 187,300 death certificates with a COVID-19 mention from Austria, Bavaria (Germany), Czechia, Lithuania and Poland, 2020-2021, was used. The two step analysis uses Cause of Death Association Indicators (CDAIs) and Contributing CDAIs to identify and measure the statistical strength of associations between COVID-19 and all other medical mentions.

RESULTS

15,700 deaths were reported with COVID-19 only as a contributing condition (comorbidity). In three cases out of four, a typical, statistically significant coronavirus complication or pre-existing condition was registered as the underlying causes of death. In Austria, Bavaria, Czechia and Lithuania the scale of COVID-19 mortality would have been up to 18-27% higher had COVID-19 been coded as the underlying cause of death. Unrecognised coronavirus deaths were equivalent to the entire surplus of excess mortality beyond registered COVID-19 deaths in Austria and the Czech Republic, and its large proportion (25-31%) in Lithuania and Bavaria.

CONCLUSIONS

Death certificates with typical coronavirus complications or comorbidities as the underlying causes of death and contributing COVID-19 mentions were plausibly unrecognized coronavirus deaths.

Spatial Variation in Excess Mortality Across Europe: A Cross-Sectional Study of 561 Regions in 21 Countries

OBJECTIVE

To measure the burden of the COVID-19 pandemic in 2020 at the subnational level by estimating excess mortality, defined as the increase in all-cause mortality relative to an expected baseline mortality level.

METHODS

Statistical and demographic analyses of regional all-cause mortality data provided by the vital statistics systems of 21 European countries for 561 regions in Central and Western Europe. Life expectancy losses at ages 0 and 60 for males and females were estimated.

RESULTS

We found evidence of a loss in life expectancy in 391 regions, whilst only three regions exhibit notable gains in life expectancy in 2020. For 12 regions, losses of life expectancy amounted to more than 2 years and three regions showed losses greater than 3 years. We highlight geographical clusters of high mortality in Northern Italy, Spain and Poland, whilst clusters of low mortality were found in Western France, Germany/Denmark and Norway/Sweden.

CONCLUSIONS

Regional differences of loss of life expectancy are impressive, ranging from a loss of more than 4 years to a gain of 8 months. These findings provide a strong rationale for regional analysis, as national estimates hide significant regional disparities.

Estimation of standardized real-time fatality rate for ongoing epidemics

BACKGROUND

The fatality rate is a crucial metric for guiding public health policies during an ongoing epidemic. For COVID-19, the age structure of the confirmed cases changes over time, bringing a substantial impact on the real-time estimation of fatality. A 'spurious decrease' in fatality rate can be caused by a shift in confirmed cases towards younger ages even if the fatalities remain unchanged across different ages.

METHODS

To address this issue, we propose a standardized real-time fatality rate estimator. A simulation study is conducted to evaluate the performance of the estimator. The proposed method is applied for real-time fatality rate estimation of COVID-19 in Germany from March 2020 to May 2022.

FINDINGS

The simulation results suggest that the proposed estimator can provide an accurate trend of disease fatality in all cases, while the existing estimator may convey a misleading signal of the actual situation when the changes in temporal age distribution take place. The application to Germany data shows that there was an increment in the fatality rate at the implementation of the 'live with COVID' strategy.

CONCLUSIONS

As many countries have chosen to coexist with the coronavirus, frequent examination of the fatality rate is of paramount importance.

Spatial disparities in the mortality burden of the covid-19 pandemic across 569 European regions (2020-2021)

Since its emergence in December 2019, the COVID-19 pandemic has resulted in a significant increase in deaths worldwide. This article presents a detailed analysis of the mortality burden of the COVID-19 pandemic across 569 regions in 25 European countries. We produce age and sex-specific excess mortality and present our results using Age-Standardised Years of Life Lost in 2020 and 2021, as well as the cumulative impact over the two pandemic years. Employing a forecasting approach based on CP-splines that considers regional diversity and provides confidence intervals, we find notable losses in 362 regions in 2020 (440 regions in 2021). Conversely, only seven regions experienced gains in 2020 (four regions in 2021). We also estimate that eight regions suffered losses exceeding 20 years of life per 1000 population in 2020, whereas this number increased to 75 regions in 2021. The contiguity of the regions investigated in our study also reveals the changing geographical patterns of the pandemic. While the highest excess mortality values were concentrated in the early COVID-19 outbreak areas during the initial pandemic year, a clear East-West gradient appeared in 2021, with regions of Slovakia, Hungary, and Latvia experiencing the highest losses. This research underscores the importance of regional analyses for a nuanced comprehension of the pandemic's impact.

Changes in stillbirths and child and youth mortality in 2020 and 2021 during the COVID-19 pandemic

BACKGROUND

The COVID-19 pandemic has been extensively studied for its impact on mortality, particularly in older age groups. However, the pandemic effects on stillbirths and mortality rates in neonates, infants, children and youth remain poorly understood. This study comprehensively analyses the pandemic influence on young mortality and stillbirths across 112 countries and territories in 2020 and 104 in 2021.

METHODS

Using data from civil registers and vital statistics systems (CRVS) and the Health Management Information System (HMIS), we estimate expected mortality levels in a non-pandemic setting and relative mortality changes (p-scores) through generalized linear models. The analysis focuses on the distribution of country-specific mortality changes and the proportion of countries experiencing deficits, no changes and excess mortality in each age group.

RESULTS

Results show that stillbirths and under-25 mortality were as expected in most countries during 2020 and 2021. However, among countries with changes, more experienced deficits than excess mortality, except for stillbirths, neonates and those aged 10-24 in 2021, where, despite the predominance of no changes, excess mortality prevailed. Notably, a fifth of examined countries saw increases in stillbirths and a quarter in young adult mortality (20-24) in 2021. Our findings are highly consistent between females and males and similar across income levels.

CONCLUSION

Despite global disruptions to essential services, stillbirths and youth mortality were as expected in most observed countries, challenging initial hypotheses. However, the study suggests the possibility of delayed adverse effects that require more time to manifest at the population level. Understanding the lasting impacts of the COVID-19 pandemic requires ongoing, long-term monitoring of health and deaths among children and youth, particularly in low- and lower-middle-income countries.

Cause-of-Death Determinants of Lifespan Inequality

We propose a novel decomposition approach that breaks down the levels and trends of lifespan inequality as the sum of cause-of-death contributions. The suggested method shows whether the levels and changes in lifespan inequality are attributable to the levels and changes in (1) the extent of inequality in the cause-specific age-at-death distribution (the "Inequality" component), (2) the total share of deaths attributable to each cause (the "Proportion" component), or (3) the cause-specific mean age at death (the "Mean" component). This so-called Inequality-Proportion-Mean (or IPM) method is applied to 10 low-mortality countries in Europe. Our findings suggest that the most prevalent causes of death (in our setting, "circulatory system" and "neoplasms") do not necessarily contribute the most to overall levels of lifespan inequality. In fact, "perinatal and congenital" causes are the strongest drivers of lifespan inequality declines. The contribution of the IPM components to changes in lifespan inequality varies considerably across causes, genders, and countries. Among the three components, the Mean one explains the least lifespan inequality dynamics, suggesting that shifts in cause-specific mean ages at death alone contributed little to changes in lifespan inequality.

Case Study of Autopsy Findings in a Population of Post-COVID-19 Vaccination in Thailand

ABSTRACT

Thailand began offering the coronavirus disease 2019 (COVID-19) vaccine nationwide in February 2021, with 1,885 deaths reported by the end of the year. Therefore, it is essential to assess the correlation between vaccination and cause of death from autopsy. This study included 34 autopsies of a deceased within 30 days after COVID-19 vaccination performed in Bangkok under the postmortem inquest service area of Bhumibol Adulyadej Hospital. The autopsies were performed by forensic pathologists. Moreover, detailed information about the deceased was collected, including age, sex, medical records, vaccination history, scene investigation reports, autopsy reports, cause of death, and a probable causal relationship between vaccination and cause of death. There were 24 males (70.59%), and the average age of the deceased was 52.76 years. Of all individuals, 28 (82.36%), 4 (11.76%), and 2 (5.88%) were vaccinated with AstraZeneca, Sinopharm, and SinoVac, respectively. The most common cause of death was ischemic heart disease (n = 17). None of the deceased patients had a causal relationship to the vaccine. Deaths were due to natural causes, as no definitive link between vaccination and cause of death was established in the study.

Standardized Cumulative Metrics of Excess Mortality to Monitor Health System Resilience Throughout COVID-19 and Other Respiratory Virus Resurgences

Monitoring morbidity and mortality in resurgences of respiratory infections poses significant challenges, as shown by coronavirus disease 2019 (COVID-19). For example, case fatality rates and deaths attributed to specific respiratory pathogens are known to suffer from significant biases undermining their comparability through time and space. As a result, it is difficult to evaluate the protective effect of public health interventions or quantify the impact of a resurgence on the general population through direct recording of COVID-19 related deaths. To overcome these limitations, more robust, less-biased metrics, such as all-cause deaths, have been proposed for monitoring the effect of an epidemic over a population and over time. More specifically, metrics of excess mortality over time, which have been used for influenza surveillance in the past, are increasingly considered important for COVID-19 surveillance. Here, we discuss excess mortality surveillance focusing on standardized single-point and standardized cumulative metrics that allow comparability of excess mortality through space and time. We explain why z score allows for comparison of excess mortality between countries and different periods, while cumulative z score allows assessment of excess mortality over long periods. Our commentary reiterates the importance of standardized statistics of excess mortality for COVID-19 surveillance as we move toward a coexistence with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that will allow drawing conclusions from best practices in different health systems and different periods.

Estimating subnational excess mortality in times of pandemic. An application to French départements in 2020

The COVID-19 pandemic's uneven impact on subnational regions highlights the importance of understanding its local-level mortality impact. Vital statistics are available for an increasing number of countries for 2020, 2021, and 2022, facilitating the computation of subnational excess mortality and a more comprehensive assessment of its burden. However, this calculation faces two important methodological challenges: it requires appropriate mortality projection models; and small populations imply considerable, though commonly neglected, uncertainty in the estimates. We address both issues using a method to forecast mortality at the subnational level, which incorporates uncertainty in the computation of mortality measures. We illustrate our approach by examining French départements (NUTS 3 regions, or 95 geographical units), and produce sex-specific estimates for 2020. This approach is highly flexible, allowing one to estimate excess mortality during COVID-19 in most demographic scenarios and for past pandemics.

Years of life lost to COVID-19 in 49 countries: A gender- and life cycle-based analysis of the first two years of the pandemic

Specific mortality rates have been widely used to monitor the main impacts of the COVID-19 pandemic; however, a more meaningful measure is the Years of Life Lost (YLL) due to the disease, considering it takes into account the premature nature of each death. We estimated the YLL due to COVID-19 between January 2020 and December 2021 in 49 countries for which information was available, developing an analytical method that mathematically refines that proposed by the World Health Organization. We then calculated YLL rates overall, as well as by sex and life cycle. Additionally, we estimated the national cost-effective budgets required to manage COVID-19 from a health system perspective. During the two years of analysis, we estimated that 85.6 million years of life were lost due to COVID-19 in the 49 countries studied. However, due to a lack of data, we were unable to analyze the burden of COVID-19 in about 75% of the countries in the world. We found no difference in the magnitude of YLL rates by gender but did find differences according to life cycle, with older adults contributing the greatest burden of YLL. The COVID-19 pandemic has posed a significant burden of disease, which has varied between countries. However, due to the lack of quality and disaggregated data, it has been difficult to monitor and compare the pandemic internationally. Therefore, it is imperative to strengthen health information systems in order to prepare for future pandemics as well as to evaluate their impacts.

Examining the associations between COVID-19 infection and pediatric type 1 diabetes

INTRODUCTION

The COVID-19 pandemic represents an unprecedented challenge for public health worldwide, not only for the very high number of cases and deaths but also due to a wide variety of indirect consequences. Among these, the possible relationship between SARS-CoV-2 infection and type 1 diabetes (T1D) in pediatric age has aroused notable interest in the scientific community.

AREAS COVERED

This perspective article aims to focus on the epidemiological trend of T1D during the pandemic, the diabetogenic role of SARS-CoV-2, and the influence of preexisting T1D on COVID-19 outcomes.

EXPERT OPINION

The incidence of T1D has considerably changed during the COVID-19 pandemic, but any direct role of SARS-CoV-2 is uncertain. It is more likely that SARS-CoV-2 infection acts as an accelerator of pancreatic β-cell immunological destruction, which is activated by known viral triggers whose spread has been abnormal during these pandemic years. Another interesting aspect to consider is the role of immunization as a potential protective factor both for T1D development and the risk of severe outcomes in already diagnosed patients. Future studies are still required to address unmet needs, including the early use of antiviral drugs to reduce the risk of metabolic decompensation in children with T1D.

In silico transcriptional analysis of asymptomatic and severe COVID-19 patients reveals the susceptibility of severe patients to other comorbidities and non-viral pathological conditions

COVID-19 is a severe respiratory disease caused by SARS-CoV-2, a novel human coronavirus. Patients infected with SARS-CoV-2 exhibit heterogeneous symptoms that pose pragmatic hurdles for implementing appropriate therapy and management of the COVID-19 patients and their post-COVID complications. Thus, understanding the impact of infection severity at the molecular level in the host is vital to understand the host response and accordingly it's precise management. In the current study, we performed a comparative transcriptomics analysis of publicly available seven asymptomatic and eight severe COVID-19 patients. Exploratory data analysis employing Principal Component Analysis (PCA) showed the distinct clusters of asymptomatic and severe patients. Subsequently, the differential gene expression analysis using DESeq2 identified 1224 significantly upregulated genes (logFC≥ 1.5, p-adjusted value <0.05) and 268 significantly downregulated genes (logFC≤ −1.5, p-adjusted value <0.05) in severe samples in comparison to asymptomatic samples. Eventually, Gene Set Enrichment Analysis (GSEA) revealed the upregulation of anti-viral and anti-inflammatory pathways, secondary infections, Iron homeostasis, anemia, cardiac-related, etc.; while, downregulation of lipid metabolism, adaptive immune response, translation, recurrent respiratory infections, heme-biosynthetic pathways, etc. Conclusively, these findings provide insight into the enhanced susceptibility of severe COVID-19 patients to other health comorbidities including non-viral pathogenic infections, atherosclerosis, autoinflammatory diseases, anemia, male infertility, etc. owing to the activation of biological processes, pathways and molecular functions associated with them. We anticipate this study will facilitate the researchers in finding efficient therapeutic targets and eventually the clinicians in management of COVID-19 patients and post-COVID-19 effects in them.

Impact of the Euro 2020 championship on the spread of COVID-19

Large-scale events like the UEFA Euro 2020 football (soccer) championship offer a unique opportunity to quantify the impact of gatherings on the spread of COVID-19, as the number and dates of matches played by participating countries resembles a randomized study. Using Bayesian modeling and the gender imbalance in COVID-19 data, we attribute 840,000 (95% CI: [0.39M, 1.26M]) COVID-19 cases across 12 countries to the championship. The impact depends non-linearly on the initial incidence, the reproduction number R, and the number of matches played. The strongest effects are seen in Scotland and England, where as much as 10,000 primary cases per million inhabitants occur from championship-related gatherings. The average match-induced increase in R was 0.46 [0.18, 0.75] on match days, but important matches caused an increase as large as +3. Altogether, our results provide quantitative insights that help judge and mitigate the impact of large-scale events on pandemic spread.

Harmonising electronic health records for reproducible research: challenges, solutions and recommendations from a UK-wide COVID-19 research collaboration

BACKGROUND

The CVD-COVID-UK consortium was formed to understand the relationship between COVID-19 and cardiovascular diseases through analyses of harmonised electronic health records (EHRs) across the four UK nations. Beyond COVID-19, data harmonisation and common approaches enable analysis within and across independent Trusted Research Environments. Here we describe the reproducible harmonisation method developed using large-scale EHRs in Wales to accommodate the fast and efficient implementation of cross-nation analysis in England and Wales as part of the CVD-COVID-UK programme. We characterise current challenges and share lessons learnt.

METHODS

Serving the scope and scalability of multiple study protocols, we used linked, anonymised individual-level EHR, demographic and administrative data held within the SAIL Databank for the population of Wales. The harmonisation method was implemented as a four-layer reproducible process, starting from raw data in the first layer. Then each of the layers two to four is framed by, but not limited to, the characterised challenges and lessons learnt. We achieved curated data as part of our second layer, followed by extracting phenotyped data in the third layer. We captured any project-specific requirements in the fourth layer.

RESULTS

Using the implemented four-layer harmonisation method, we retrieved approximately 100 health-related variables for the 3.2 million individuals in Wales, which are harmonised with corresponding variables for > 56 million individuals in England. We processed 13 data sources into the first layer of our harmonisation method: five of these are updated daily or weekly, and the rest at various frequencies providing sufficient data flow updates for frequent capturing of up-to-date demographic, administrative and clinical information.

CONCLUSIONS

We implemented an efficient, transparent, scalable, and reproducible harmonisation method that enables multi-nation collaborative research. With a current focus on COVID-19 and its relationship with cardiovascular outcomes, the harmonised data has supported a wide range of research activities across the UK.

The WHO estimates of excess mortality associated with the COVID-19 pandemic

The World Health Organization has a mandate to compile and disseminate statistics on mortality, and we have been tracking the progression of the COVID-19 pandemic since the beginning of 2020¹. Reported statistics on COVID-19 mortality are problematic for many countries owing to variations in testing access, differential diagnostic capacity and inconsistent certification of COVID-19 as cause of death. Beyond what is directly attributable to it, the pandemic has caused extensive collateral damage that has led to losses of lives and livelihoods. Here we report a comprehensive and consistent measurement of the impact of the COVID-19 pandemic by estimating excess deaths, by month, for 2020 and 2021. We predict the pandemic period all-cause deaths in locations lacking complete reported data using an overdispersed Poisson count framework that applies Bayesian inference techniques to quantify uncertainty. We estimate 14.83 million excess deaths globally, 2.74 times more deaths than the 5.42 million reported as due to COVID-19 for the period. There are wide variations in the excess death estimates across the six World Health Organization regions. We describe the data and methods used to generate these estimates and highlight the need for better reporting where gaps persist. We discuss various summary measures, and the hazards of ranking countries' epidemic responses.

The role of booster vaccination in decreasing COVID-19 age-adjusted case fatality rate: Evidence from 32 countries

Background

The global COVID-19 pandemic is still ongoing, and cross-country and cross-period variation in COVID-19 age-adjusted case fatality rates (CFRs) has not been clarified. Here, we aimed to identify the country-specific effects of booster vaccination and other features that may affect heterogeneity in age-adjusted CFRs with a worldwide scope, and to predict the benefit of increasing booster vaccination rate on future CFR.

Method

Cross-temporal and cross-country variations in CFR were identified in 32 countries using the latest available database, with multi-feature (vaccination coverage, demographic characteristics, disease burden, behavioral risks, environmental risks, health services and trust) using Extreme Gradient Boosting (XGBoost) algorithm and SHapley Additive exPlanations (SHAP). After that, country-specific risk features that affect age-adjusted CFRs were identified. The benefit of booster on age-adjusted CFR was simulated by increasing booster vaccination by 1-30% in each country.

Results

Overall COVID-19 age-adjusted CFRs across 32 countries ranged from 110 deaths per 100,000 cases to 5,112 deaths per 100,000 cases from February 4, 2020 to Jan 31, 2022, which were divided into countries with age-adjusted CFRs higher than the crude CFRs and countries with age-adjusted CFRs lower than the crude CFRs (n = 9 and n = 23) when compared with the crude CFR. The effect of booster vaccination on age-adjusted CFRs becomes more important from Alpha to Omicron period (importance scores: 0.03-0.23). The Omicron period model showed that the key risk factors for countries with higher age-adjusted CFR than crude CFR are low GDP per capita and low booster vaccination rates, while the key risk factors for countries with higher age-adjusted CFR than crude CFR were high dietary risks and low physical activity. Increasing booster vaccination rates by 7% would reduce CFRs in all countries with age-adjusted CFRs higher than the crude CFRs.

Conclusion

Booster vaccination still plays an important role in reducing age-adjusted CFRs, while there are multidimensional concurrent risk factors and precise joint intervention strategies and preparations based on country-specific risks are also essential.

Adverse reactions in young children receiving the coronavirus disease 2019 vaccine

BACKGROUND

We sought to investigate the occurrence of adverse reactions in Japanese children aged 6 months to 4 years who received the BNT162b2 coronavirus disease 2019 (COVID-19) vaccine, to examine parental considerations, and to evaluate potential risk factors associated with post-vaccination fever.

METHODS

This cross-sectional survey study targeted 1617 children aged 6 months to 4 years who received their primary doses of BNT162b2 from November 10, 2022, to April 30, 2023, in Okayama Prefecture. We surveyed the occurrence of local and systemic reactions within 1 week after vaccination, and described the incidence proportions of adverse reactions for 515 participants overall and by age group. The study also examined the impact of previous COVID-19 infection and co-administration of the seasonal influenza vaccine on post-vaccination fever. A survey also assessed parents' reasons for vaccinating their children and the sources of information they used.

RESULTS

Adverse reactions were infrequent (5.2%, with fever ≥37.5°C; no cases exceeded 39°C) and did not increase with vaccine doses administered. The risk of post-vaccination fever was not statistically associated with a history of COVID-19-the adjusted risk ratio (aRR) was 0.99, and the 95% confidence interval (CI) was 0.41-2.39-but was associated with co-administration of the seasonal influenza vaccine (aRR 3.24, 95% CI 1.14-9.18). Parental decisions regarding vaccination were influenced by official government guidelines and primary care physicians' opinion.

CONCLUSION

This study provides valuable insight into the safety profile of the BNT162b2 vaccine in Japanese children aged 6 months to 4 years. Further research involving larger cohorts and appropriate control groups is needed.

Age-stratified infection fatality rate of COVID-19 in the non-elderly population

The largest burden of COVID-19 is carried by the elderly, and persons living in nursing homes are particularly vulnerable. However, 94% of the global population is younger than 70 years and 86% is younger than 60 years. The objective of this study was to accurately estimate the infection fatality rate (IFR) of COVID-19 among non-elderly people in the absence of vaccination or prior infection. In systematic searches in SeroTracker and PubMed (protocol: https://osf.io/xvupr), we identified 40 eligible national seroprevalence studies covering 38 countries with pre-vaccination seroprevalence data. For 29 countries (24 high-income, 5 others), publicly available age-stratified COVID-19 death data and age-stratified seroprevalence information were available and were included in the primary analysis. The IFRs had a median of 0.034% (interquartile range (IQR) 0.013-0.056%) for the 0-59 years old population, and 0.095% (IQR 0.036-0.119%) for the 0-69 years old. The median IFR was 0.0003% at 0-19 years, 0.002% at 20-29 years, 0.011% at 30-39 years, 0.035% at 40-49 years, 0.123% at 50-59 years, and 0.506% at 60-69 years. IFR increases approximately 4 times every 10 years. Including data from another 9 countries with imputed age distribution of COVID-19 deaths yielded median IFR of 0.025-0.032% for 0-59 years and 0.063-0.082% for 0-69 years. Meta-regression analyses also suggested global IFR of 0.03% and 0.07%, respectively in these age groups. The current analysis suggests a much lower pre-vaccination IFR in non-elderly populations than previously suggested. Large differences did exist between countries and may reflect differences in comorbidities and other factors. These estimates provide a baseline from which to fathom further IFR declines with the widespread use of vaccination, prior infections, and evolution of new variants.

Life expectancy changes since COVID-19

The COVID-19 pandemic triggered an unprecedented rise in mortality that translated into life expectancy losses around the world, with only a few exceptions. We estimate life expectancy changes in 29 countries since 2020 (including most of Europe, the United States and Chile), attribute them to mortality changes by age group and compare them with historic life expectancy shocks. Our results show divergence in mortality impacts of the pandemic in 2021. While countries in western Europe experienced bounce backs from life expectancy losses of 2020, eastern Europe and the United States witnessed sustained and substantial life expectancy deficits. Life expectancy deficits during fall/winter 2021 among people ages 60+ and <60 were negatively correlated with measures of vaccination uptake across countries (r60+ = -0.86; two-tailed P < 0.001; 95% confidence interval, -0.94 to -0.69; r<60 = -0.74; two-tailed P < 0.001; 95% confidence interval, -0.88 to -0.46). In contrast to 2020, the age profile of excess mortality in 2021 was younger, with those in under-80 age groups contributing more to life expectancy losses. However, even in 2021, registered COVID-19 deaths continued to account for most life expectancy losses.

The World Health Organization COVID-19 surveillance database

In January 2020, SARS-CoV-2 virus was identified as a cause of an outbreak in China. The disease quickly spread worldwide, and the World Health Organization (WHO) declared the pandemic in March 2020.From the first notifications of spread of the disease, the WHO's Emergency Programme implemented a global COVID-19 surveillance system in coordination with all WHO regional offices. The system aimed to monitor the spread of the epidemic over countries and across population groups, severity of the disease and risk factors, and the impact of control measures. COVID-19 surveillance data reported to WHO is a combination of case-based data and weekly aggregated data, focusing on a minimum global dataset for cases and deaths including disaggregation by age, sex, occupation as a Health Care Worker, as well as number of cases tested, and number of cases newly admitted for hospitalization. These disaggregations aim to monitor inequities in COVID-19 distribution and risk factors among population groups.SARS-CoV-2 epidemic waves continue to sweep the world; as of March 2022, over 445 million cases and 6 million deaths have been reported worldwide. Of these, over 327 million cases (74%) have been reported in the WHO surveillance database, of which 255 million cases (57%) are disaggregated by age and sex. A public dashboard has been made available to visualize trends, age distributions, sex ratios, along with testing and hospitalization rates. It includes a feature to download the underlying dataset.This paper will describe the data flows, database, and frontend public dashboard, as well as the challenges experienced in data acquisition, curation and compilation and the lessons learnt in overcoming these. Two years after the pandemic was declared, COVID-19 continues to spread and is still considered a Public Health Emergency of International Concern (PHEIC). While WHO regional and country offices have demonstrated tremendous adaptability and commitment to process COVID-19 surveillance data, lessons learnt from this major event will serve to enhance capacity and preparedness at every level, as well as institutional empowerment that may lead to greater sharing of public health evidence during a PHEIC, with a focus on equity.

Are COVID-19 age-mortality curves for 2020 flatter in developing countries? Evidence from a cross-sectional observational study of population-level official death counts and excess deaths estimates

OBJECTIVES

Previous studies have found a pattern of flatter COVID-19 age-mortality curves among low-income and middle-income countries (LMICs) using only official COVID-19 death counts. This study examines this question by comparing the age gradient of COVID-19 mortality in a broad set of countries using both official COVID-19 death counts and excess mortality estimates for 2020.

DESIGN

This observational study uses official COVID-19 death counts for 76 countries and excess death estimates for 42 countries. A standardised population analysis was conducted to assess the extent to which variation across countries in the age distribution of COVID-19 deaths was driven by variation in the population age distribution.

SETTING AND PRIMARY OUTCOMES

Officially reported COVID-19 deaths and excess deaths for 2020 for all countries where such data were available in the COVerAGE database and the short-term mortality fluctuations harmonised data series, respectively.

RESULTS

A higher share of pandemic-related deaths in 2020 occurred at younger ages in middle-income countries compared with high-income countries. People under age 65 years constituted on average (1) 10% of official deaths and 11 % of excess deaths in high-income countries, (2) 34% of official deaths and 33% of excess deaths in upper-middle-income countries, and (3) 54% of official deaths in LMICs. These contrasting profiles are due only in part to differences in population age structure.

CONCLUSIONS

These findings are driven by some combination of variation in age patterns of infection rates and infection fatality rates. They indicate that COVID-19 is not just a danger to older people in developing countries, where a large share of victims are people of working age, who are caregivers and breadwinners for their families.

Does ‘Data fudging’ explain the autocratic advantage? Evidence from the gap between Official Covid-19 mortality and excess mortality

Governments can underreport Covid-19 mortality to make their performance appear more successful than it is. Autocracies are more likely to ‘fudge’ these data since many autocratic regimes restrict media freedom and thus can prevent domestic media from reporting evidence of undercounting deaths. Autocracies also enjoy greater leverage over reporting health authorities to either fudge data or adopt restrictive definitions of what constitutes Covid-19 mortality. Controlling for other factors that explain official Covid-19 mortality, excess mortality and the difference between the two, our results suggest that any apparent ‘autocratic advantage’ in fighting the pandemic is likely to only exist in official Covid-19 mortality. Analyzing the gap between excess mortality and official Covid-19 mortality we find that autocracies on average have a larger gap between official Covid-19 mortality data and excess mortality data, which points towards ‘autocratic data fudging’ of their official Covid-19 mortality statistics.

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Autocracies have greater incentives and opportunity to underreport Covid-19 mortality.

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Excess mortality provides a check on the reliability of official Covid-19 mortality.

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Autocracies seemingly experience lower official Covid-19 mortality rates.

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Autocracies exhibit a larger gap between excess and reported Covid-19 mortality.

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More autocratic countries are more likely to ‘fudge’ their Covid-19 mortality data.

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.

Collecting mortality data via mobile phone surveys: A non-inferiority randomized trial in Malawi

Despite the urgent need for timely mortality data in low-income and lower-middle-income countries, mobile phone surveys rarely include questions about recent deaths. Such questions might a) be too sensitive, b) take too long to ask and/or c) generate unreliable data. We assessed the feasibility of mortality data collection using mobile phone surveys in Malawi. We conducted a non-inferiority trial among a random sample of mobile phone users. Participants were allocated to an interview about their recent economic activity or recent deaths in their family. In the group that was asked mortality-related questions, half of the respondents completed an abridged questionnaire, focused on information necessary to calculate recent mortality rates, whereas the other half completed an extended questionnaire that also included questions about symptoms and healthcare. The primary trial outcome was the cooperation rate, i.e., the number of completed interviews divided by the number of mobile subscribers invited to participate. Secondary outcomes included self-reports of negative feelings and stated intentions to participate in future interviews. We called more than 7,000 unique numbers and reached 3,054 mobile subscribers. In total, 1,683 mobile users were invited to participate. The difference in cooperation rates between those asked to complete a mortality-related interview and those asked to answer questions about economic activity was 0.9 percentage points (95% CI = -2.3, 4.1), which satisfied the non-inferiority criterion. The mortality questionnaire was non-inferior to the economic questionnaire on all secondary outcomes. Collecting mortality data required 2 to 4 additional minutes per reported death, depending on the inclusion of questions about symptoms and healthcare. More than half of recent deaths elicited during mobile phone interviews had not been registered with the National Registration Bureau. Including mortality-related questions in mobile phone surveys is feasible. It might help strengthen the surveillance of mortality in countries with deficient civil registration systems. Registration: AEA RCT Registry, #0008065 (14 September 2021).

Update on COVID-19 vaccination in pediatric solid organ transplant recipients

BACKGROUND

COVID-19 vaccination has been successful in decreasing rates of SARS-CoV-2 infection in areas with high vaccine uptake. Cases of breakthrough SARS-CoV-2 infection remain infrequent among immunocompetent vaccine recipients who are protected from severe COVID-19. Robust data demonstrate the safety, immunogenicity, and effectiveness of several COVID-19 vaccine formulations. Importantly, Pfizer-BioNTech BNT162b2 mRNA COVID-19 vaccine studies have now included children as young as 5 years of age with safety, immunogenicity, and effectiveness data publicly available. In the United States, emergency use authorization by the Federal Drug Administration and approval from the Centers for Disease Control/Advisory Committee on Immunization Practices have been provided for the 5- to 11-year-old age group.

METHODS

Members of the International Pediatric Transplant Association (IPTA) provide an updated review of current COVID-19 vaccine data with focus on pediatric solid organ transplant (SOT)-specific issues.

RESULTS

This review provides an overview of current COVID-19 immunogenicity, safety, and efficacy data from key studies, with focus on data of importance to pediatric SOT recipients. Continued paucity of data in the setting of pediatric transplantation remains a challenge.

CONCLUSIONS

Further studies of COVID-19 vaccination in pediatric SOT recipients are needed to better understand post-vaccine COVID-19 T-cell and antibody kinetics and determine the optimal vaccine schedule. Increased COVID-19 vaccine acceptability, uptake, and worldwide availability are needed to limit the risk that COVID-19 poses to pediatric solid organ transplant recipients.

A Tale of Three Recent Pandemics: Influenza, HIV and SARS-CoV-2

Emerging infectious diseases are one of the main threats to public health, with the potential to cause a pandemic when the infectious agent manages to spread globally. The first major pandemic to appear in the 20th century was the influenza pandemic of 1918, caused by the influenza A H1N1 strain that is characterized by a high fatality rate. Another major pandemic was caused by the human immunodeficiency virus (HIV), that started early in the 20th century and remained undetected until 1981. The ongoing HIV pandemic demonstrated a high mortality and morbidity rate, with discrepant impacts in different regions around the globe. The most recent major pandemic event, is the ongoing pandemic of COVID-19, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which has caused over 5.7 million deaths since its emergence, 2 years ago. The aim of this work is to highlight the main determinants of the emergence, epidemic response and available countermeasures of these three pandemics, as we argue that such knowledge is paramount to prepare for the next pandemic. We analyse these pandemics’ historical and epidemiological contexts and the determinants of their emergence. Furthermore, we compare pharmaceutical and non-pharmaceutical interventions that have been used to slow down these three pandemics and zoom in on the technological advances that were made in the progress. Finally, we discuss the evolution of epidemiological modelling, that has become an essential tool to support public health policy making and discuss it in the context of these three pandemics. While these pandemics are caused by distinct viruses, that ignited in different time periods and in different regions of the globe, our work shows that many of the determinants of their emergence and countermeasures used to halt transmission were common. Therefore, it is important to further improve and optimize such approaches and adapt it to future threatening emerging infectious diseases.

A WSN Framework for Privacy Aware Indoor Location

In the past two decades, technological advancements in smart devices, IoT, and smart sensors have paved the way towards numerous implementations of indoor location systems. Indoor location has many important applications in numerous fields, including structural engineering, behavioral studies, health monitoring, etc. However, with the recent COVID-19 pandemic, indoor location systems have gained considerable attention for detecting violations in physical distancing requirements and monitoring restrictions on occupant capacity. However, existing systems that rely on wearable devices, cameras, or sound signal analysis are intrusive and often violate privacy. In this research, we propose a new framework for indoor location. We present an innovative, non-intrusive implementation of indoor location based on wireless sensor networks. Further, we introduce a new protocol for querying and performing computations in wireless sensor networks (WSNs) that preserves sensor network anonymity and obfuscates computation by using onion routing. We also consider the single point of failure (SPOF) of sink nodes in WSNs and substitute them with a blockchain-based application through smart contracts. Our set of smart contracts is able to build the onion data structure and store the results of computation. Finally, a role-based access control contract is used to secure access to the system.

Change in age distribution of COVID-19 deaths with the introduction of COVID-19 vaccination

OBJECTIVES

Most countries initially deployed COVID-19 vaccines preferentially in elderly populations. We aimed to evaluate whether population-level vaccine effectiveness is heralded by an increase in the relative proportion of deaths among non-elderly populations that were less covered by vaccination programs.

ELIGIBLE DATA

We collected data from 40 countries on age-stratified COVID-19 deaths during the vaccination period (1/14/2021-5/31/2021) and two control periods (entire pre-vaccination period and excluding the first wave).

MAIN OUTCOME MEASURES

We meta-analyzed the proportion of deaths in different age groups in vaccination versus control periods in (1) countries with low vaccination rates; (2) countries with age-independent vaccination policies; and (3) countries with standard age-dependent vaccination policies.

RESULTS

Countries that prioritized vaccination among older people saw an increasing share of deaths among 0-69 year old people in the vaccination versus the two control periods (summary proportion ratio 1.32 [95 CI% 1.24-1.41] and 1.35 [95 CI% 1.26-1.44)]. No such change was seen on average in countries with age-independent vaccination policies (1.05 [95 CI% 0.78-1.41 and 0.97 [95 CI% 0.95-1.00], respectively) and limited vaccination (0.93 [95 CI% 0.85-1.01] and 0.95 [95 CI% 0.87-1.03], respectively). Proportion ratios were associated with the difference of vaccination rates in elderly versus non-elderly people. No significant changes occurred in the share of deaths in age 0-49 among all 0-69 deaths in the vaccination versus pre-vaccination periods.

CONCLUSIONS

The substantial shift in the age distribution of COVID-19 deaths in countries that rapidly implemented vaccination predominantly among elderly provides evidence for the population level-effectiveness of COVID-19 vaccination and a favorable evolution of the pandemic towards endemicity with fewer elderly deaths.

Quantifying impacts of the COVID-19 pandemic through life-expectancy losses: a population-level study of 29 countries

BACKGROUND

Variations in the age patterns and magnitudes of excess deaths, as well as differences in population sizes and age structures, make cross-national comparisons of the cumulative mortality impacts of the COVID-19 pandemic challenging. Life expectancy is a widely used indicator that provides a clear and cross-nationally comparable picture of the population-level impacts of the pandemic on mortality.

METHODS

Life tables by sex were calculated for 29 countries, including most European countries, Chile and the USA, for 2015-2020. Life expectancy at birth and at age 60 years for 2020 were contextualized against recent trends between 2015 and 2019. Using decomposition techniques, we examined which specific age groups contributed to reductions in life expectancy in 2020 and to what extent reductions were attributable to official COVID-19 deaths.

RESULTS

Life expectancy at birth declined from 2019 to 2020 in 27 out of 29 countries. Males in the USA and Lithuania experienced the largest losses in life expectancy at birth during 2020 (2.2 and 1.7 years, respectively), but reductions of more than an entire year were documented in 11 countries for males and 8 among females. Reductions were mostly attributable to increased mortality above age 60 years and to official COVID-19 deaths.

CONCLUSIONS

The COVID-19 pandemic triggered significant mortality increases in 2020 of a magnitude not witnessed since World War II in Western Europe or the breakup of the Soviet Union in Eastern Europe. Females from 15 countries and males from 10 ended up with lower life expectancy at birth in 2020 than in 2015.

Is Mandatory Vaccination in Population over 60 Adequate to Control the COVID-19 Pandemic in E.U.?

Vaccine hesitancy, which potentially leads to the refusal or delayed acceptance of COVID-19 vaccines, is considered a key driver of the increasing death toll from the pandemic in the EU. The European Commission and several member states’ governments are either planning or have already directly or indirectly announced mandatory vaccination for individuals aged over 60, the group which has repeatedly proved to be the most vulnerable. In this paper, an assessment of this strategy’s benefits is attempted by deriving a metric for the potential gains of vaccination mandates that can be used to compare EU member states. This is completed by examining the reduction in Standard Expected Years of Life Lost (SEYLL) per person for the EU population over 60 as a function of the member states’ vaccination percentage in these ages. The publicly available data and results of the second iteration of the SHARE COVID-19 survey on the acceptance of COVID-19 vaccines, conducted during the summer of 2021, are used as inputs.

Unexposed populations and potential COVID-19 hospitalisations and deaths in European countries as per data up to 21 November 2021

We estimate the potential remaining COVID-19 hospitalisation and death burdens in 19 European countries by estimating the proportion of each country's population that has acquired immunity to severe disease through infection or vaccination. Our results suggest many European countries could still face high burdens of hospitalisations and deaths, particularly those with lower vaccination coverage, less historical transmission and/or older populations. Continued non-pharmaceutical interventions and efforts to achieve high vaccination coverage are required in these countries to limit severe COVID-19 outcomes.

Design parameters optimization of an electrothermal flow biosensor for the SARS-CoV-2 S protein immunoassay

To combat the coronavirus disease 2019 (COVID-19), great efforts have been made by scientists around the world to improve the performance of detection devices so that they can efficiently and quickly detect the virus responsible for this disease. In this context we performed 2D finite element simulation on the kinetics of SARS-CoV-2 S protein binding reaction of a biosensor using the alternating current electrothermal (ACET) effect. The ACET flow can produce vortex patterns, thereby improving the transportation of the target analyte to the binding surface and thus enhancing the performance of the biosensor. Optimization of some design parameters concerning the microchannel height and the reaction surface, such as its length as well as its position on the top wall of the microchannel, in order to improve the biosensor efficiency, was studied. The results revealed that the detection time can be improved by 55% with an applied voltage of 10 V _rms and an operating frequency of 150 kHz and that the decrease in the height of the microchannel and in the length of the binding surface can lead to an increase in the rate of the binding reaction and therefore decrease the biosensor response time. Also, moving the sensitive surface from an optimal position, located in front of the electrodes, decreases the performance of the device.

Inferring the COVID-19 infection fatality rate in the community-dwelling population: a simple Bayesian evidence synthesis of seroprevalence study data and imprecise mortality data

Estimating the coronavirus disease-2019 (COVID-19) infection fatality rate (IFR) has proven to be particularly challenging –and rather controversial– due to the fact that both the data on deaths and the data on the number of individuals infected are subject to many different biases. We consider a Bayesian evidence synthesis approach which, while simple enough for researchers to understand and use, accounts for many important sources of uncertainty inherent in both the seroprevalence and mortality data. With the understanding that the results of one's evidence synthesis analysis may be largely driven by which studies are included and which are excluded, we conduct two separate parallel analyses based on two lists of eligible studies obtained from two different research teams. The results from both analyses are rather similar. With the first analysis, we estimate the COVID-19 IFR to be 0.31% [95% credible interval (CrI) of (0.16%, 0.53%)] for a typical community-dwelling population where 9% of the population is aged over 65 years and where the gross-domestic-product at purchasing-power-parity (GDP at PPP) per capita is $17.8k (the approximate worldwide average). With the second analysis, we obtain 0.32% [95% CrI of (0.19%, 0.47%)]. Our results suggest that, as one might expect, lower IFRs are associated with younger populations (and may also be associated with wealthier populations). For a typical community-dwelling population with the age and wealth of the United States we obtain IFR estimates of 0.43% and 0.41%; and with the age and wealth of the European Union, we obtain IFR estimates of 0.67% and 0.51%.

A Biochemical Analysis of Patients with COVID-19 Infection

Several studies have demonstrated that age, comorbidities, and abnormalities in different clinical biomarkers can be important to understand disease severity. Although clinical features of COVID-19 have been widely described, the assessment of alterations of the most common biochemical markers that are reported in patients with COVID-19 still has not been well established. Here, we report clinical and blood biochemical indicators of 100 patients with COVID-19. Throat-swab upper respiratory samples were obtained from patients and real-time PCR was used to confirm SARS-CoV-2 infection. Gender, age, and clinical features such as diabetes mellitus, hypertension, and smoking habits were investigated. Biochemical parameters were categorized and analyzed according to these clinical characteristics. Triglycerides, GPT, and ALP are the biochemical markers that changed the most in the group of hypertension patients. Cholesterol and triglycerides were significantly different (P=0.01; P=0.04, respectively) between diabetic and nondiabetic patients with COVID-19. Potassium levels were significantly different (P=0.03) when comparing smokers with nonsmoker patients. Our results suggest several potential biochemical indexes that changed in patients with COVID-19 and whether certain comorbidity and clinical characteristics influence these markers.

SARS-CoV-2 infections in 165 countries over time

BACKGROUND

Understanding the dynamics of the COVID-19 pandemic and evaluating the efficacy of control measures requires knowledge of the number of infections over time. This number, however, often differs from the number of confirmed cases because of a large fraction of asymptomatic infections and different testing strategies.

METHODS

This study uses death count statistics, age-dependent infection fatality risks, and stochastic modeling to estimate the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections among adults (aged 20 years or older) in 165 countries over time, from early 2020 until June 25, 2021. The accuracy of the approach is confirmed through comparison with previous nationwide seroprevalence surveys.

RESULTS

The estimates presented reveal that the fraction of infections that are detected vary widely over time and between countries, and hence confirmed cases alone often yield a false picture of the pandemic. As of June 25, 2021, the nationwide cumulative fraction of SARS-CoV-2 infections (cumulative infections relative to population size) was estimated as 98% (95% confidence interval [CI] 93-100%) for Peru, 83% (95% CI 61-94%) for Brazil, and 36% (95% CI 23-61%) for the United States.

CONCLUSIONS

The time-resolved estimates presented expand the possibilities to study the factors that influenced and still influence the pandemic's progression in 165 countries.

COVID-19 mortality rate in children is U-shaped

Children are known to be better protected from COVID-19 than adults, but their susceptibility patterns and the risk relative to other diseases are insufficiently defined. Here, we found that the COVID-19 mortality rate is U-shaped in childhood: it initially decreases, reaching the minimum at the ages 3-10 years, and then increases throughout life. All-cause mortality and mortality from other diseases, such as pneumonia and influenza, show a similar pattern; however, childhood mortality rates from COVID-19 are considerably lower than from other diseases, with the best relative protection achieved at the youngest ages. Consistent with this, the fraction of COVID-19 deaths among all deaths increases as a function of age throughout childhood and the entire life. We discuss implications of the elevated postnatal COVID-19 risk and lower childhood COVID-19 mortality compared to other diseases.

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

Comparing the impact of the COVID-19 pandemic between countries or across time is difficult because the reported numbers of cases and deaths can be strongly affected by testing capacity and reporting policy. Excess mortality, defined as the increase in all-cause mortality relative to the expected mortality, is widely considered as a more objective indicator of the COVID-19 death toll. However, there has been no global, frequently updated repository of the all-cause mortality data across countries. To fill this gap, we have collected weekly, monthly, or quarterly all-cause mortality data from 103 countries and territories, openly available as the regularly updated World Mortality Dataset. We used this dataset to compute the excess mortality in each country during the COVID-19 pandemic. We found that in several worst-affected countries (Peru, Ecuador, Bolivia, Mexico) the excess mortality was above 50% of the expected annual mortality (Peru, Ecuador, Bolivia, Mexico) or above 400 excess deaths per 100,000 population (Peru, Bulgaria, North Macedonia, Serbia). At the same time, in several other countries (e.g. Australia and New Zealand) mortality during the pandemic was below the usual level, presumably due to social distancing measures decreasing the non-COVID infectious mortality. Furthermore, we found that while many countries have been reporting the COVID-19 deaths very accurately, some countries have been substantially underreporting their COVID-19 deaths (e.g. Nicaragua, Russia, Uzbekistan), by up to two orders of magnitude (Tajikistan). Our results highlight the importance of open and rapid all-cause mortality reporting for pandemic monitoring.

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

Comparing the impact of the COVID-19 pandemic between countries or across time is difficult because the reported numbers of cases and deaths can be strongly affected by testing capacity and reporting policy. Excess mortality, defined as the increase in all-cause mortality relative to the expected mortality, is widely considered as a more objective indicator of the COVID-19 death toll. However, there has been no global, frequently-updated repository of the all-cause mortality data across countries. To fill this gap, we have collected weekly, monthly, or quarterly all-cause mortality data from 94 countries and territories, openly available as the regularly-updated World Mortality Dataset. We used this dataset to compute the excess mortality in each country during the COVID-19 pandemic. We found that in several worst-affected countries (Peru, Ecuador, Bolivia, Mexico) the excess mortality was above 50% of the expected annual mortality. At the same time, in several other countries (Australia, New Zealand) mortality during the pandemic was below the usual level, presumably due to social distancing measures decreasing the non-COVID infectious mortality. Furthermore, we found that while many countries have been reporting the COVID-19 deaths very accurately, some countries have been substantially underreporting their COVID-19 deaths (e.g. Nicaragua, Russia, Uzbekistan), sometimes by two orders of magnitude (Tajikistan). Our results highlight the importance of open and rapid all-cause mortality reporting for pandemic monitoring.

Open data products-A framework for creating valuable analysis ready data

This paper develops the notion of "open data product". We define an open data product as the open result of the processes through which a variety of data (open and not) are turned into accessible information through a service, infrastructure, analytics or a combination of all of them, where each step of development is designed to promote open principles. Open data products are born out of a (data) need and add value beyond simply publishing existing datasets. We argue that the process of adding value should adhere to the principles of open (geographic) data science, ensuring openness, transparency and reproducibility. We also contend that outreach, in the form of active communication and dissemination through dashboards, software and publication are key to engage end-users and ensure societal impact. Open data products have major benefits. First, they enable insights from highly sensitive, controlled and/or secure data which may not be accessible otherwise. Second, they can expand the use of commercial and administrative data for the public good leveraging on their high temporal frequency and geographic granularity. We also contend that there is a compelling need for open data products as we experience the current data revolution. New, emerging data sources are unprecedented in temporal frequency and geographical resolution, but they are large, unstructured, fragmented and often hard to access due to privacy and confidentiality concerns. By transforming raw (open or "closed") data into ready to use open data products, new dimensions of human geographical processes can be captured and analysed, as we illustrate with existing examples. We conclude by arguing that several parallels exist between the role that open source software played in enabling research on spatial analysis in the 90 s and early 2000s, and the opportunities that open data products offer to unlock the potential of new forms of (geo-)data.