Excess mortality in Israel associated with COVID-19 in 2020-2021 by age group and with estimates based on daily mortality patterns in 2000-2019

Improving retrospective data on recent household deaths: a multi-arm randomized trial in Guinea-Bissau

BACKGROUND

In countries with limited civil registration and vital statistics systems, assessing the impact of health crises requires precise retrospective mortality data. We tested whether calendar methods improve survey or census data on dates of recent household deaths registered in a Health and Demographic Surveillance System (HDSS).

METHODS

Between April and June 2023, we randomized 578 households with HDSS-registered deaths in Guinea-Bissau to interviews by using (i) a standard questionnaire with close-ended questions about dates of deaths, or similar questionnaires supplemented with (ii) a physical calendar of local events printed on paper or (iii) a digital calendar implemented on tablets. We evaluated the accuracy of reported dates through record linkages to HDSS data.

RESULTS

No deaths were reported in 11.8% of the 508 participating households. In other households (n = 448), informants reported 574 deaths since January 2020. Relative to the standard questionnaire, neither the physical calendar nor the digital calendar improved the proportion of deaths reported in the same month and year as recorded by using surveillance data. The physical and digital calendars reduced the share of missing data on dates of deaths (6.1% and 3.2%, respectively, versus 13.1% with the standard questionnaire). Reported dates of deaths obtained by using the digital calendar were more weakly correlated with surveillance data than those collected in other arms. Using the digital calendar also added 1.15 minutes to the data collection.

CONCLUSION

Digital calendars do not improve the reporting of dates of deaths in surveys or censuses. Further trials of the use of a physical calendar in retrospective interviews about recent household deaths are warranted.

Acute coronary syndrome rates by age and sex before and during the COVID-19 pandemic in Israel: nationwide study

BACKGROUND

There have been reports of sharp declines in acute coronary syndrome (ACS) during the COVID-19 pandemic. The study aims to assess nationwide ACS emergency department (ED) visit rates across age and sex subgroups and the general population, with a comparison before and throughout the pandemic's various phases.

METHODS

A multiple interrupted time series analysis was used to assess 61 349 ACS nationwide hospital visits from January 2018 to December 2021 at monthly intervals. The study period was divided into three periods: January 2018-February 2020 (pre-pandemic period); March 2020-January 2021 (early-pandemic period); February 2021-December 2021 (late-pandemic period). Segmented regression with a seasonally adjusted autoregressive moving average structure was used to build predictive models with an estimated reference trendline (counterfactual).

RESULTS

Over 11 months of the early-pandemic period (lockdowns), the largest decrease in visits was seen in women aged 65 and above, of 18.4% [incidence rate ratio (IRR) 0.82; 95% confidence interval (CI) 0.77-0.86]. The lowest decrease was observed in men aged 25-64, of 7.2% (IRR 0.93; 0.91-0.94). During the late-pandemic period, which included high vaccination coverage and no lockdowns, the largest further decrease was in women aged 25-64 of 20.1% (IRR 0.80; 0.75-0.84) on average.

CONCLUSIONS

The pandemic influenced ACS ED visits variably, with substantial declines during phases of high COVID-19 morbidity and mortality. Older individuals, particularly women, demonstrated the largest decrease in ACS ED visits, highlighting the need for tailored public health strategies to maintain public confidence in access to critical care during future health emergencies.

Unraveling the impact of the COVID-19 pandemic on the mortality trends in Belgium between 2020-2022

BACKGROUND

Over the past four years, the COVID-19 pandemic has exerted a profound impact on public health, including on mortality trends. This study investigates mortality patterns in Belgium by examining all-cause mortality, excess mortality, and cause-specific mortality.

METHODS

We retrieved all-cause mortality data from January 1, 2009, to December 31, 2022, stratified by age group and sex. A linear mixed model, informed by all-cause mortality from 2009 to 2019, was used to predict non-pandemic all-cause mortality rates in 2020-2022 and estimate excess mortality. Further, we also analyzed trends in cause-specific and premature mortality.

RESULTS

Different all-cause mortality patterns could be observed between the younger (<45 years) and older age groups. The impact of the COVID-19 pandemic was particularly evident among older age groups. The highest excess mortality occurred in 2020, while a reversal in this trend was evident in 2022. We observed a notable effect of COVID-19 on cause-specific and premature mortality patterns over the three-year period.

CONCLUSIONS

Despite a consistent decline in COVID-19 reported mortality over this three-year period, it remains imperative to meticulously monitor mortality trends in the years ahead.

Geospatial patterns of excess mortality in Belgium: Insights from the first year of the COVID-19 pandemic

OBJECTIVES

Belgium experienced multiple COVID-19 waves that hit various groups in the population, which changed the mortality pattern compared to periods before the pandemic. In this study, we investigated the geographical excess mortality trend in Belgium during the first year of the COVID-19 pandemic.

METHODS

We retrieved the number of deaths and population data in 2020 based on gender, age, and municipality of residence, and we made a comparison with the mortality data in 2017-2019 using a spatially discrete model.

RESULTS

Excess mortality was significantly associated with age, gender, and COVID-19 incidence, with larger effects in the second half of 2020. Most municipalities had higher risks of mortality with a number of exceptions in the northeastern part of Belgium. Some discrepancies in excess mortality were observed between the north and south regions.

CONCLUSIONS

This study offers useful insight into excess mortality and will aid local and regional authorities in monitoring mortality trends.

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.

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.

Characteristics and Motivational Factors of Whole Blood and Convalescent Plasma Donors during the SARS-CoV-2 Pandemic in Israel

Demands for whole blood (WB) and COVID-19 convalescent plasma (CCP) donations during the SARS-CoV-2 (COVID-19) pandemic presented unprecedented challenges for blood services throughout the world. This study aims to understand the motivating factors that drive WB and CCP donations in the context of the pandemic. This cross-sectional study is based on data extracted from surveys of the two volunteer donor cohorts. The findings reveal that when compared to CCP donors, WB donors were more likely to view donation as a form of social engagement (97.7% vs. 87.1%, p < 0.01), advantageous in the workplace (46.4% vs. 28.6%, p < 0.01), advantageous in their social network (58.6% vs. 47.0%, p = 0.01), and view their donation in the context of positive self-satisfaction (99% vs. 95.1%, p = 0.01). The average age of CCP donors was 7.1 years younger than those who donated WB (p < 0.01). Motivational factors were also analyzed by sex and religiosity. In conclusion, whereas both donor groups showed a high motivation to partake in these life-saving commitments, WB donors were more likely to be motivated by factors that, when better-understood and implemented in policies concerning plasma donations, may help to increase these donations.

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.

Gender differences in estimated excess mortality during the COVID-19 pandemic in Thailand

BACKGROUND

There is a limited body of research specifically examining gender inequality in excess mortality and its variations across age groups and geographical locations during the COVID-19 pandemic. This study aims to fill this gap by analyzing the patterns of gender inequality in excess all-cause mortality in Thailand during the COVID-19 pandemic.

METHODS

Data pertaining to all-cause deaths and population between January 1, 2010, and December 31, 2021, were obtained from Thailand's Bureau of Registration Administration. A seasonal autoregressive integrated moving average (SARIMA) technique was used to estimate excess mortality during the pandemic between January 2020 to December 2021. Gender differential excess mortality was measured as the difference in age-standardized mortality rates between men and women.

RESULTS

Our SARIMA-based estimate of all-cause mortality in Thailand during the COVID-19 pandemic amounted to 1,032,921 deaths, with COVID-19-related fatalities surpassing official figures by 1.64 times. The analysis revealed fluctuating patterns of excess and deficit in all-cause mortality rates across different phases of the pandemic, as well as among various age groups and regions. In 2020, the most pronounced gender disparity in excess all-cause mortality emerged in April, with 4.28 additional female deaths per 100,000, whereas in 2021, the peak gender gap transpired in August, with 7.52 more male deaths per 100,000. Individuals in the 80 + age group exhibited the largest gender gap for most of the observed period. Gender differences in excess mortality were uniform across regions and over the period observed. Bangkok showed the highest gender disparity during the peak of the fourth wave, with 24.18 more male deaths per 100,000.

CONCLUSION

The findings indicate an overall presence of gender inequality in excess mortality during the COVID-19 pandemic in Thailand, observed across age groups and regions. These findings highlight the need for further attention to be paid to gender disparities in mortality and call for targeted interventions to address these disparities.

Excess mortality from COVID 19 in Costa Rica: a registry based study using Poisson regression

Background

Official death toll related to COVID-19 has been considerably underestimated in reports from some Latin American countries. This study aimed to analyze the mortality associated with the COVID-19 pandemic in Costa Rica between March 2020 and December 2021.

Methods

A registry based study based on 2017-2021 data from the National Institute of Statistics and Census was designed (N = 128,106). Excess deaths were defined by the WHO as "the difference in the total number of deaths in a crisis compared to those expected under normal conditions"; and were estimated using a Poisson regression, and mortality and years of potential life lost (YPLL) rates were calculated.

Findings

The COVID-19 pandemic represented 15% of the deaths in Costa Rica between March 2020 and December 2021. The mortality rate related to COVID-19 was 83 per 100,000 person-years. Between March and July 2020 (low-incidence period), observed number of deaths was 9%-lower than expected, whereas it was 15% and 24% higher than expected between July 2020 and March 2021 (high incidence period - no vaccination), and between March 2021 and December 2021 (high incidence period - progressive vaccination) respectively. Between July 2020 and December 2021, excess deaths observed and COVID-19 deaths reported were comparable (7461 and 7620 respectively). Nevertheless, there were more deaths than expected for conditions that predispose to COVID-19 deaths. YPLL and mortality rates increased with age, but significant excess deaths were observed in all age-groups older than 30-39 years. No large differences were noted by districts' socioeconomic characteristics although excess death rate was lower in rural compared to urban areas.

Interpretation

Reporting of deaths was only slightly underestimated. In the pre-vaccination period, mortality rate and YPLL rates increased with age, being highest in people aged 60 years or older and justifying the decision to initially prioritize vaccination of older individuals.

Funding

The study was supported by the University of Costa Rica and the Agencia Costarricense de Investigaciones Biomédicas - Fundación Inciensa.

Effect size quantification for interrupted time series analysis: implementation in R and analysis for Covid-19 research

Background

Interrupted time series (ITS) analysis is a time series regression model that aims to evaluate the effect of an intervention on an outcome of interest. ITS analysis is a quasi-experimental study design instrumental in situations where natural experiments occur, gaining popularity, particularly due to the Covid-19 pandemic. However, challenges, including the lack of a control group, have impeded the quantification of the effect size in ITS. The current paper proposes a method and develops a user-friendly R package to quantify the effect size of an ITS regression model for continuous and count outcomes, with or without seasonal adjustment.

Results

The effect size presented in this work, together with its corresponding 95% confidence interval (CI) and P-value, is based on the ITS model-based fitted values and the predicted counterfactual (the exposed period had the intervention not occurred) values. A user-friendly R package to fit an ITS and estimate the effect size was developed and accompanies this paper. To illustrate, we implemented a nation population-based ITS study from January 2001 to May 2021 covering the all-cause mortality of Israel (n = 9,350 thousand) to quantify the effect size of Covid-19 exposure on mortality rates. In the period unexposed to the Covid-19 pandemic, the mortality rate decreased over time and was expected to continue decreasing had Covid-19 not occurred. In contrast, the period exposed to the Covid-19 pandemic was associated with an increased all-cause mortality rate (relative risk = 1.11, 95% CI = 1.04, 1.18, P < 0.001).

Conclusion

For the first time, the effect size in ITS: was quantified, can be estimated by end-users with an R package we developed, and was demonstrated with data showing an increase in mortality following the Covid-19 pandemic. ITS effect size reporting can assist public health policy makers in assessing the magnitude of the entire intervention effect using a single, readily understood measure.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12982-022-00118-7.

Global Excess Mortality during COVID-19 Pandemic: A Systematic Review and Meta-Analysis

BACKGROUND

Currently, reported COVID-19 deaths are inadequate to assess the impact of the pandemic on global excess mortality. All-cause excess mortality is a WHO-recommended index for assessing the death burden of COVID-19. However, the global excess mortality assessed by this index remains unclear. We aimed to assess the global excess mortality during the COVID-19 pandemic.

METHODS

We searched PubMed, EMBASE, and Web of Science for studies published in English between 1 January 2020, and 21 May 2022. Cross-sectional and cohort studies that reported data about excess mortality during the pandemic were included. Two researchers independently searched the published studies, extracted data, and assessed quality. The Mantel-Haenszel random-effects method was adopted to estimate pooled risk difference (RD) and their 95% confidence intervals (CIs).

RESULTS

A total of 79 countries from twenty studies were included. During the COVID-19 pandemic, of 2,228,109,318 individuals, 17,974,051 all-cause deaths were reported, and 15,498,145 deaths were expected. The pooled global excess mortality was 104.84 (95% CI 85.56-124.13) per 100,000. South America had the highest pooled excess mortality [134.02 (95% CI: 68.24-199.80) per 100,000], while Oceania had the lowest [-32.15 (95% CI: -60.53--3.77) per 100,000]. Developing countries had higher excess mortality [135.80 (95% CI: 107.83-163.76) per 100,000] than developed countries [68.08 (95% CI: 42.61-93.55) per 100,000]. Lower middle-income countries [133.45 (95% CI: 75.10-191.81) per 100,000] and upper-middle-income countries [149.88 (110.35-189.38) per 100,000] had higher excess mortality than high-income countries [75.54 (95% CI: 53.44-97.64) per 100,000]. Males had higher excess mortality [130.10 (95% CI: 94.15-166.05) per 100,000] than females [102.16 (95% CI: 85.76-118.56) per 100,000]. The population aged ≥ 60 years had the highest excess mortality [781.74 (95% CI: 626.24-937.24) per 100,000].

CONCLUSIONS

The pooled global excess mortality was 104.84 deaths per 100,000, and the number of reported all-cause deaths was higher than expected deaths during the global COVID-19 pandemic. In South America, developing and middle-income countries, male populations, and individuals aged ≥ 60 years had a heavier excess mortality burden.

Mortality during the first four waves of COVID-19 pandemic in Israel: March 2020-October 2021

BACKGROUND

The COVID-19 pandemic caused four waves of infection in Israel until October 2021. Israel was the first country to offer vaccinations to all the adult population followed by boosters. This study addresses how mortality rates reflect the effects of the pandemic.

METHODS

Total mortality rates and rates of mortality without COVID-19 deaths (non-COVID-19 mortality) between March 2020 and October 2021 were compared with the average pre-COVID-19 rates in 2017-2019 by month, population group and by age group. In addition, a cohort vaccinated at least once by 31 March 2021 was followed up for mortality in the following seven months compared to the corresponding months in 2017-2019.

RESULTS

A small number of excess deaths was found in the first wave and a greater excess in the following waves. The monthly mortality rate ratio was highest in October 2020, 23% higher than the average in 2017-2019, followed by August 2021 (22%), September 2021 (20%) and September 2020 (19%). Excess mortality in the Arab population was greater than for Jews and Others, and they had 65% and 43% higher mortality in September and October, 2020, 20-44% higher mortality between December 2020 and April 2021 and 33%, 45% and 22% higher mortality in August, September and October 2021, respectively. In most months of the pandemic, the non-COVID-19 mortality rates were not significantly different from those in 2017-2019. However, between November 2020 and March 2021, they were significantly lower for the total population and Jews and Others. They were significantly higher for the total population only in August 2021, and particularly for the Arab population. Non-COVID-19 mortality was also lower for most sex/age groups over the total study period. In a cohort of 5.07 million Israeli citizens vaccinated at least once by 31 March, 2021, age adjusted and age specific mortality rates for the following 7 months were lower than the average rates in 2017-2019 for these months, CONCLUSION: Israel has seen significant excess mortality during the COVID-19 pandemic, particularly in the Arab sector. Following lockdowns and administration of vaccinations excess mortality was reduced, and no excess mortality was seen amongst the vaccinated in the months after the vaccination campaign. These findings highlight the importance of public health measures such as mandating mask wearing and population vaccinations to control infection and reduce mortality.