Assessing excess mortality in Vienna and Austria after the first year of the COVID-19 pandemic

In Austria, the first confirmed COVID-19 death occurred in early March 2020. Since then, the question as to whether and, if so, to what extent the COVID-19 pandemic has increased overall mortality has been raised in the public and academic discourse. In an effort to answer this question, Statistics Vienna (City of Vienna, Department for Economic Affairs, Labour and Statistics) has evaluated the weekly mortality trends in Vienna, and compared them to the trends in other Austrian provinces. For our analysis, we draw on data from Statistics Austria and the Austrian Agency for Health and Food Safety (AGES), which are published along with data on the actual and the expected weekly numbers of deaths via the Vienna Mortality Monitoring website. Based on the definition of excess mortality as the actual number of reported deaths from all causes minus the expected number of deaths, we calculate the weekly prediction intervals of the expected number of deaths for two age groups (0 to 64 years and 65 years and older). The temporal scope of the analysis covers not only the current COVID-19 pandemic, but also previous flu seasons and summer heat waves. The results show the actual weekly numbers of deaths and the corresponding prediction intervals for Vienna and the other Austrian provinces since 2007. Our analysis underlines the importance of comparing time series of COVID-19-related excess deaths at the sub-national level in order to highlight within-country heterogeneities.

On assessing excess mortality in Germany during the COVID-19 pandemic

Coronavirus disease 2019 (COVID-19) is associated with a very high number of casualties in the general population. Assessing the exact magnitude of this number is a non-trivial problem, as relying only on officially reported COVID-19 associated fatalities runs the risk of incurring in several kinds of biases. One of the ways to approach the issue is to compare overall mortality during the pandemic with expected mortality computed using the observed mortality figures of previous years. In this paper, we build on existing methodology and propose two ways to compute expected as well as excess mortality, namely at the weekly and at the yearly level. Particular focus is put on the role of age, which plays a central part in both COVID-19-associated and overall mortality. We illustrate our methods by making use of age-stratified mortality data from the years 2016 to 2020 in Germany to compute age group-specific excess mortality during the COVID-19 pandemic in 2020.

Estimation of excess all-cause mortality due to COVID-19 in Thailand

Background: Thailand has recently experienced the most prominent COVID-19 outbreak, resulting in a new record for COVID-19 cases and deaths. To assess the influence of the COVID-19 outbreak on mortality, we aimed to estimate excess mortality in Thailand. Methods: We estimated the baseline number of deaths in the absence of COVID-19 using generalized linear mixed models (GLMMs). The models were adjusted for seasonality and demographics. We evaluated the excess mortality from April to October 2021 in Thailand. Results: We found that the estimated cumulative excess death from April to October 2021 was 14.3% (95% CI: 8.6%-18.8%) higher than the baseline. The results also showed that the excess deaths in males were higher than in females by approximately 26.3%. The excess deaths directly caused by the COVID-19 infections accounted for approximately 75.0% of the all-cause excess deaths. Furthermore, the cumulative COVID-19 cases were found to be correlated with the cumulative excess deaths with a correlation coefficient of 0.9912 (95% CI, 0.9392-0.9987). Conclusions: The recent COVID-19 outbreak in Thailand significantly impacts mortality and affects people for specific ages and sex. During the outbreak in 2021, there was a significant rise in excess fatalities, especially in the older age groups. The increase in mortality was higher in men than in women.

Factors associated with excess all-cause mortality in the first wave of the COVID-19 pandemic in the UK: A time series analysis using the Clinical Practice Research Datalink

Background Excess mortality captures the total effect of the Coronavirus Disease 2019 (COVID-19) pandemic on mortality and is not affected by misspecification of cause of death. We aimed to describe how health and demographic factors were associated with excess mortality during, compared to before, the pandemic. Methods and findings We analysed a time series dataset including 9,635,613 adults (≥40 years old) registered at United Kingdom general practices contributing to the Clinical Practice Research Datalink. We extracted weekly numbers of deaths and numbers at risk between March 2015 and July 2020, stratified by individual-level factors. Excess mortality during Wave 1 of the UK pandemic (5 March to 27 May 2020) compared to the prepandemic period was estimated using seasonally adjusted negative binomial regression models. Relative rates (RRs) of death for a range of factors were estimated before and during Wave 1 by including interaction terms. We found that all-cause mortality increased by 43% (95% CI 40% to 47%) during Wave 1 compared with prepandemic. Changes to the RR of death associated with most sociodemographic and clinical characteristics were small during Wave 1 compared with prepandemic. However, the mortality RR associated with dementia markedly increased (RR for dementia versus no dementia prepandemic: 3.5, 95% CI 3.4 to 3.5; RR during Wave 1: 5.1, 4.9 to 5.3); a similar pattern was seen for learning disabilities (RR prepandemic: 3.6, 3.4 to 3.5; during Wave 1: 4.8, 4.4 to 5.3), for black or South Asian ethnicity compared to white, and for London compared to other regions. Relative risks for morbidities were stable in multiple sensitivity analyses. However, a limitation of the study is that we cannot assume that the risks observed during Wave 1 would apply to other waves due to changes in population behaviour, virus transmission, and risk perception. Conclusions The first wave of the UK COVID-19 pandemic appeared to amplify baseline mortality risk to approximately the same relative degree for most population subgroups. However, disproportionate increases in mortality were seen for those with dementia, learning disabilities, non-white ethnicity, or living in London.

Narrowing gap in regional and age-specific excess mortality in the first year and a half of COVID-19 in Hungary

In the first year and a half of the pandemic, the excess mortality in Hungary was 28,400, which was 1,700 lower than the official statistics on COVID-19 deaths. This discrepancy can be partly explained by protective measures instated during the COVID-19 pandemic that decreased the intensity of the seasonal flu outbreak, which caused on average 3,000 deaths per year. Compared to the second wave of the COVID-19 pandemic, the third wave showed a reduction in the differences in excess mortality between age groups and regions. The excess mortality rate for people aged 75+ fell significantly in the third wave, partly due to the vaccination schedule and the absence of a normal flu season. For people aged 40-77, the excess mortality rate rose slightly in the third wave. Between regions, excess mortality was highest in Northern Hungary and Western Transdanubia, and much lower in Central Hungary, where the capital is located. The excess mortality rate for men was almost twice as high as that for women in almost all age groups.

No substantial excess all-cause mortality among cardiac implantable electronic device patients during the first COVID‑19 lockdown in the Leiden area

In the Netherlands, the coronavirus disease 2019 (COVID‑19) pandemic has resulted in excess mortality nationwide. Chronic heart disease patients are at risk for a complicated COVID‑19 course. The current study investigates all-cause mortality among cardiac implantable electronic device (CIED) patients during the first peak of the pandemic and compares the data to the statistics for the corresponding period in the two previous years. Data of adult CIED patients undergoing follow-up at the Leiden University Medical Centre were analysed. All-cause mortality between 1 March and 31 May 2020 was evaluated and compared to the data for the same period in 2019 and 2018. At the beginning of the first peak of the pandemic, 3,171 CIED patients (median age 70 years; 68% male; 41% ischaemic aetiology) were alive. Baseline characteristics of the 2019 (n = 3,216) and 2018 (n = 3,169) cohorts were comparable. All-cause mortality during the peak of the pandemic was 1.4% compared to 1.6% and 1.4% in the same period in 2019 and 2018, respectively (p = 0.84). During the first peak of the COVID‑19 pandemic, there was no substantial excess mortality among CIED patients in the Leiden area, despite the fact that this is group at high risk for a complicated course of a COVID‑19 infection. Strict adherence to the preventive measures may have prevented substantial excess mortality in these vulnerable patients.

Climate change in Russia – problems of public health

Climate change and the accompanying social risks have already become one of the main problems of the world community. An increase in the frequency and duration of natural disasters (floods, typhoons, mudflows, etc.) lead to significant loss of life. Heat waves have caused excess mortality among the urban population, especially among Russian megacities. WHO initiated the development of national adaptation plans, and Russia has accumulated some experience in developing a regional action plan using the example of the Arkhangelsk region. and a local plan in Moscow. The National Adaptation Plan of the Russian Federation provides for the participation of the Ministry of Health, but there is no intersectoral interaction, the best practices of other countries have not been sufficiently studied.