Magnitude, global variation, and temporal development of the COVID-19 infection fatality burden

How deadly is an infection with SARS-CoV-2 worldwide over time? This information is critical for developing and assessing public health responses on the country and global levels. However, imperfect data have been the most limiting factor for estimating the COVID-19 infection fatality burden during the first year of the pandemic. Here we leverage recently emerged compelling data sources and broadly applicable modeling strategies to estimate the crude infection fatality rate (cIFR) in 77 countries from 28 March 2020 to 31 March 2021, using 2.4 million reported deaths and estimated 435 million infections by age, sex, country, and date. The global average of all cIFR estimates is 1.2% (10th to 90th percentile: 0.2% to 2.4%). The cIFR varies strongly across countries, but little within countries over time, and it is often lower for women than men. Cross-country differences in cIFR are largely driven by the age structures of both the general and the truly infected population. While the broad trends and patterns of the cIFR estimates are more robust, we show that their levels are uncertain and sensitive to input data and modeling choices. In consequence, increased efforts at collecting high-quality data are essential for accurately estimating the cIFR, which is a key indicator for better understanding the health and mortality consequences of this pandemic.

Declines in life expectancy following the COVID-19 pandemic in provinces of Spain

The COVID-19 pandemic has impacted population health on a global scale. Most of the studies on mortality impacts are at national level, while broad evidence exists on heterogeneous COVID-19 incidence across regions and within countries. Using Spanish data for 2020, we estimate life expectancy changes in 2020 compared with the 2017-19 period in 50 Spanish provinces. We visualize longer-term trends (1990-2020), and compare the robustness of our province-specific results with cumulative COVID-19 incidence using regional data from the Spanish ENECOVID seroprevalence study. In 2020 there was a 1.2 and 1.1 year drop in life expectancy for men and women in Spain, but this impact was heterogeneous across regions. For men these losses were highest in the province of Segovia (-3.5 years decline), while for women the highest drop was observed in Salamanca (-2.8 years decline). Life expectancy actually increased in Santa Cruz de Tenerife (+1.1 and +0.6 years for men and women, respectively). Declines in life expectancy in 2020 were also highly correlated with the cumulative seroprevalence through November 2020 ({rho}=0.80 and 0.77 in men and women, respectively). Monitoring regional life expectancy dynamics provide valuable and granular information on the heterogeneous impacts of the pandemic on health at the population level. Similar exercises in other European countries may reveal insightful geographic patterns in mortality impacts in COVID-19 pandemic years.

Sex differences in the mortality rate for coronavirus disease 2019 compared to other causes of death

Men are more likely than women to die due to coronavirus disease 2019 (COVID-19). This paper sets out to examine whether the magnitude of the sex differences in the COVID-19 mortality rate are unusual when compared to other common causes of death. In doing so, we aim to provide evidence as to whether the causal pathways for the sex differences in the mortality rate of COVID-19 likely differ from those for other causes of death. We found that sex differences in the age-standardized COVID-19 mortality rate were substantially larger than for the age-standardized all-cause mortality rate and most other common causes of death. These differences were especially large in the oldest age groups. One Sentence SummaryThe sex difference in the mortality rate of coronavirus disease 2019 is substantially larger than for other common causes of death.

COVeAGE-DB: A database of age-structured COVID-19 cases and deaths.

COVerAGE-DB is an open-access database including cumulative counts of confirmed COVID-19 cases, deaths, and tests by age and sex. The main goal of COVerAGE-DB is to provide a centralized, standardized, age-harmonized, and fully reproducible database of COVID-19 data. Original data and sources are provided alongside data and measures in age-harmonized formats. An international team, composed of more than 60 researchers, contributed to the collection of data and metadata in COVerAGE-DB from governmental institutions, as well as to the design and implementation of the data processing and validation pipeline. The database is still in development, and at this writing, it includes 89 countries, and 237 subnational areas. Cumulative counts of COVID-19 cases, deaths, and tests are recorded daily (when possible) since January 2020. Many time series thus fully capture the first pandemic wave and the beginning of later waves. Since collection efforts began for COVerAGE-DB several studies have used the data.

Global years of life lost to COVID-19

Understanding the mortality impact of COVID-19 requires not only counting the dead, but analyzing how premature the deaths are. We calculate years of life lost (YLL) across 42 countries due to COVID-19 attributable deaths, and also conduct an analysis based on estimated excess deaths. As of June 13th 2020, YLL in heavily affected countries are 2 to 6 times the average seasonal influenza; over two thirds of the YLL result from deaths in ages below 75 and one quarter from deaths below 55; and men have lost 47% more life years than women. The results confirm the large mortality impact of COVID-19 among the elderly. They also call for heightened awareness in devising policies that protect vulnerable demographics losing the largest number of life-years. One Sentence SummaryAcross 42 countries, the years of life lost due to COVID-19 are up to 6 times that of the average seasonal flu.

Monitoring life expectancy levels during the COVID-19 pandemic: Example of the unequal impact in Spanish regions

BackgroundTo provide an interpretable summary of the impact on mortality of the COVID-19 pandemic we estimate weekly and annual life expectancies at birth in Spain and its regions. MethodsWe used daily death count data from the Spanish MoMo, and death counts from 2018, and population on 1 July, 2019 by region (CCAA), age groups, and sex from the Spanish National Statistics Institute. We estimated weekly and annual (2019 and 2020*, the shifted annual calendar period up to June 14th 2020) life expectancies at birth as well as their differences with respect to 2019. ResultsWeekly life expectancies at birth in Spain were lower in weeks 11-20, 2020 compared to the same weeks in 2019. This drop in weekly life expectancy was especially strong in weeks 13 and 14 (March 23rd to April 5th), with national declines ranging between 6.1 and 7.6 years and maximum regional weekly declines of up to 15 years in Madrid. Annual life expectancy differences between 2019 and 2020 also reflected an overall drop in annual life expectancy of 0.8 years for both men and women. These drops ranged between 0 years in several regions (e.g. Canary and Balearic Islands) to 2.7 years among men in Madrid. ConclusionsLife expectancy is an easy to interpret measure for understanding the heterogeneity of mortality patterns across Spanish regions. Weekly and annual life expectancy are sensitive useful indicators for understanding disparities and communicating the gravity of the situation because differences are expressed in intuitive year units. Key messages- Weekly and annual updated life expectancy are valuable indicators of the health impacts of the pandemic in populations. - The impact of the COVID-19 pandemic in Spain has been severe and highly heterogeneous, with weekly life expectancy falls of up to 15 years in Madrid, and with annual life expectancy falls ranging between 0 and 2.7 years. - Our results for Spain provide important insights into the magnitude of the pandemic in mortality levels across regions and are easy to interpret and compare.

Monitoring trends and differences in COVID-19 case fatality rates using decomposition methods: Contributions of age structure and age-specific fatality

The population-level case-fatality rate (CFR) associated with COVID-19 varies substantially, both across countries time and within countries over time. We analyze the contribution of two key determinants of the variation in the observed CFR: the age-structure of diagnosed infection cases and age-specific case-fatality rates. We use data on diagnosed COVID-19 cases and death counts attributable to COVID-19 by age for China, Germany, Italy, South Korea, Spain, the United States, and New York City. We calculate the CFR for each population at the latest data point and also for Italy over time. We use demographic decomposition to break the difference between CFRs into unique contributions arising from the age-structure of confirmed cases and the age-specific case-fatality. In late April 2020, CFRs varied from 2.2% in South Korea to 13.0% in Italy. The age-structure of detected cases often explains more than two thirds of cross-country variation in the CFR. In Italy, the CFR increased from 4.2% to 13.0% between March 9 and April 22, 2020, and more than 90% of the change was due to increasing age-specific case-fatality rates. The importance of the age-structure of confirmed cases likely reflects several factors, including different testing regimes and differences in transmission trajectories; while increasing age-specific case-fatality rates in Italy could indicate other factors, such as the worsening health outcomes of those infected with COVID-19. Our findings lend support to recommendations for data to be disaggregated by age, and potentially other variables, to facilitate a better understanding of population-level differences in CFRs. They also show the need for well designed seroprevalence studies to ascertain the extent to which differences in testing regimes drive differences in the age-structure of detected cases.