Number Of Excess Deaths Research Articles

Science-based exit from stringent countermeasures against COVID-19: Mortality prediction using immune landscape between 2021 and 2022 in Japan

BackgroundStringent public health and social measures against COVID-19 infection were implemented to avoid an overwhelming hospital caseload and excessive number of deaths, especially among elderly people. We analyzed population-level immunity and predicted mortality, calculated as the potential number of deaths on a given calendar date in Japan, to develop a science-based exit strategy from stringent control measures. MethodsImmune proportions were inferred by age group using vaccination coverage data and the estimated number of naturally infected individuals. Immunity against symptomatic illness and death were estimated separately, allowing for inference of the immune fraction that was protected against either COVID-19-related symptomatic infection or death. By multiplying the infection fatality risk by age group for the immune fraction, the potential number of deaths was obtained. ResultsAccounting for a second and third dose of messenger RNA vaccine in the present-day population, approximately 155,000 potential deaths would be expected among people aged ≥ 60 years if all individuals were infected at the very end of 2022. A fourth dose (i.e., second booster) with a coverage identical to that of the third dose could reduce mortality by 60%. In all examined settings, the largest number of deaths occurred among people aged 80 years and older. ConclusionsOur estimates can help policymakers understand the mortality impact of the COVID-19 epidemic in a quantitative manner and the critical importance of timely immunization so as to assist in decision making.

Mortality of the Danish Nationwide AQP4 Antibody-Seropositive Neuromyelitis Optica Spectrum Disorder Patient Cohort.

We aimed to evaluate the mortality of patients with AQP4 antibody-seropositive (AQP4-Ab+) neuromyelitis optica spectrum disorder (NMOSD) in Denmark compared with that in the general population. We identified patients with AQP4-Ab+ NMOSD fulfilling the 2015 International Panel for Neuromyelitis Optica Diagnosis (IPND) criteria from multiple sources (laboratories and the Danish Multiple Sclerosis Registry). We obtained detailed information about patients from hospital records and about the general population matched on age, sex, and calendar year from Statistics Denmark. We calculated standardized mortality ratio (SMR), excess number of deaths per 1,000 person-years (EDR), and life expectancies compared with those of the matched general population. We examined predictive factors of mortality and the cause of death. Of 66 patients with AQP4-Ab+ NMOSD between 2008 and 2020, 15 died. Overall, the SMR was 2.54 (95% CI 1.47-4.09), and the EDR was 16.8 (95% CI 4.6-34.3). The median life expectancy for patients with AQP4-Ab+ NMOSD was 64.08 years (95% CI 53.02-83.9), compared with 83.07 years for the general population. Risk of death over time was increased in the patient population with a hazard ratio (HR) of 2.22 (1.34-3.68; p = 0.002). The cause of death was directly related to NMOSD in 93% of the cases. The age at disease onset was an independent predictor of death (HR 1.042; 95% CI 1.006-1.079; p = 0.02). AQP4-Ab+ NMOSD is associated with increased mortality and shorter life expectancy compared with that in the general population, underlining the need for highly effective treatment approaches.

Evaluation of risks of cardiovascular disease from radiation exposure linked to computed tomography scans in the UK

Epidemiological studies of patient populations have shown that high doses of radiation increase risks of cardiovascular disease (CVD). Results from a recent meta-analysis of 93 epidemiological studies covering a wide range of doses provided evidence of a causal association between radiation exposure and CVD, and indicated excess relative risk per Gy for maximum dose below 500 mGy or delivered at low dose rates. These doses cover the range of organ doses expected from multiple diagnostic computed tomography (CT) scans. Dose-effect factors for the excess absolute risk of mortality from CVD following radiation exposure were derived from the meta-analysis. The present study uses these factors to estimate excess risks of mortality for various types of CVD, including cerebrovascular disease (CeVD), from CT scans of the body and head, assuming that the meta-analytic factors were accurate and represented a causal relationship. Estimates are based on cumulative doses to the heart and brain from CT scans performed on 105 574 patients on 12 CT scanners over a period of 5½ years. The results suggest that the excess number of deaths from CeVD could be 7 or 26 per 100 000 patients depending whether threshold brain doses of 200 mGy or 50 mGy, respectively are assumed. These results could have implications for head CT scans. However, the results rely on the validity of risk factors derived in the meta-analysis informing this assessment and which include significant uncertainties. Further incidence studies should provide better information on risk factors and dose thresholds, particularly for CeVD following head CT scans.

Mind the gap! The role of health policy capacity and vaccination acceptance in European Covid‐19 mortality differences

AbstractTwo years of the Covid‐19 pandemic caused significantly different death tolls in European countries. Nine of the 30 countries with the highest accumulated fatalities belong to Central and Eastern Europe, although the solidarity of the European Union (EU) provided vaccines for all member states. Using correlation and cluster analysis, this paper identifies the demographic, social, and political factors which can explain the differences. As generally accepted in the literature, the death toll is measured by the number of excess deaths. The examination separates the prevaccination and vaccination periods. While the impact of other factors is also present, vaccination coverage has a salient explanatory role in the excess deaths of the second period. The experiences of the Covid‐19 pandemic simultaneously highlight the importance and sociopolitical constraints of health policy at the European level. The analysis confirms that complementary competences between the European and national levels are adequate for the EU health policy.

Mortality in Norway and Sweden during the COVID-19 pandemic 2020–22: A comparative study

BackgroundNorway and Sweden picked two different ways to mitigate the dissemination of the SARS-CoV-2 virus. Norway introduced the strictest lockdown in Europe with strict border controls and intense virus tracking of all local outbreaks while Sweden did not. That resulted in 477 COVID-19 deaths (Norway) and 9737 (Sweden) in 2020, respectively. MethodsWeekly number of COVID-19 related deaths and total deaths for 2020–22 were collected as well as weekly number of deaths for 2015–19 which were used as controls when calculating excess mortality. During the first 12–18 months with high rate of virus transmission in the society, excess mortality rates were used as substitute for COVID-19 deaths. When excess mortality rates later turned negative because of mortality displacement, COVID-19 deaths adjusted for bias due to overreporting were used. ResultsThere were 17521 COVID-19 deaths in Sweden and 4272 in Norway in the study period. The rate ratio (RR) of COVID-19 related deaths in Sweden vs. Norway to the end of week 43, 2022, was 2.11 (95% CI 2.05–2.19). RR of COVID-19 related deaths vs. excess number of deaths were 2.5 (Sweden) and 1.3 (Norway), respectively. RR of COVID-19 deaths in Sweden vs. Norway after adjusting for mortality displacement and lockdown, was 1.35 (95% CI 1.31–1.39), corresponding to saving 2025 life in Norway. If including all deaths in 2022, RR= 1.28 (95% CI 1.24–1.31). ConclusionsBoth COVID-19 related mortality and excess mortality rates are biased estimates. When adjusting for bias, mortality differences declined over time to about 30% higher mortality in Sweden after 30 months with pandemics.

Mediation of daily ambient ozone concentration on association between daily mean temperature and mortality in 7 metropolitan cities of Korea

BackgroundClimate change is suspected to cause adverse health effects, and increased ozone concentration is one of the proposed pathways. We examined the mediation of ozone on the association between temperature and daily mortality and estimated excess mortality due to climate change. MethodsDaily mean temperature, 8-hour maximum ozone concentration, and daily number of non-accidental deaths from 7 metropolitan cities in Korea (Seoul, Busan, Daegu, Incheon, Daejeon, Gwangju, and Ulsan) between January 1, 2006 and December 31, 2019 were analyzed. A mediation analysis using a linear regression model for temperature and ozone and a Poisson regression model for temperature and mortality adjusting for ozone was conducted on days with temperature higher than or lower than city specific minimum mortality temperature. We calculated excess mortality due to direct and indirect effects of daily temperature exceeding average daily temperature from 1960 to 1990. ResultsThe daily mean temperature from 2006 to the end of 2019 was 1.15 ± 2.94 °C higher than the average daily temperature from 1960 to 1990. The pooled relative risk (for a 1 °C increment) of indirect effects through increased ozone were 1.0002 [95% confidence interval (CI): 0.9999, 1.0004] and 1.0003 (95% CI: 1.0002, 1.0005) in days with higher than or lower than minimum mortality temperature, respectively. The numbers of excess deaths during the study period were 2072.5 (95% CI: 1957.1, 2186.5) due to direct effects in days with higher than minimal mortality temperature, and 94.6 (95% CI: 84.3, 101.7) and 268.5 (95% CI: 258.4, 289.1) due to indirect effects in days with higher than and lower than minimal mortality temperature, respectively. ConclusionWe observed a mediating effect of ozone between temperature and daily mortality. There has been excess deaths due direct effect of temperature and indirect effects through ozone.

Estimation of Excess Mortality in Germany During 2020-2022.

Background This study estimates the burden of COVID-19 on mortality in Germany. It is expected that many people have died because of the new COVID-19 virus who otherwise would not have died. Estimating the burden of the COVID-19 pandemic on mortality by the number of officially reported COVID-19-related deaths has been proven to be difficult due to several reasons. Because of this, a better approach, which has been used in many studies, is to estimate the burden of the COVID-19 pandemic by calculating the excess mortality for the pandemic years. An advantage of such an approach is that additional negative impacts of a pandemic on mortality are covered as well, such as a possible pandemic-induced strain on the healthcare system. Methods To calculate the excess mortality in Germany for the pandemic years 2020 to 2022, we compare the reported number of all-cause deaths (i.e., the number of deaths independently of underlying causes) with the number of statistically expected all-cause deaths. For this, the state-of-the-art method of actuarial science, based on population tables, life tables, and longevity trends, is used to estimate the expected number of all-cause deaths from 2020 to 2022 if there had been no pandemic. Results The results show that the observed number of deaths in 2020 was close to the expected number with respect to the empirical standard deviation; approximately 4,000 excess deaths occurred. By contrast, in 2021, the observed number of deaths was two empirical standard deviations above the expected numberand even more than four times the empirical standard deviation in 2022. In total, the number of excess deaths in the year 2021 is about 34,000and in 2022 about 66,000 deaths, yielding a cumulated 100,000 excess deaths in both years. The high excess mortality in 2021 and 2022 was mainly due to an increase in deaths in the age groups between 15 and 79 years and started to accumulate only from April 2021 onward. A similar mortality pattern was observed for stillbirths with an increase of about 9.4% in the second quarter and 19.4% in the fourth quarter of the year 2021 compared to previous years. Conclusions These findings indicate that something must have happened in spring 2021 that led to a sudden and sustained increase in mortality, although no such effects on mortality had been observed during the early COVID-19 pandemic so far. Possible influencing factors are explored in the discussion.

Estimating Excess Mortality Due to Prostate, Breast, and Uterus Cancer during the COVID-19 Pandemic in Peru: A Time Series Analysis.

During the COVID-19 pandemic, most of the deaths in Peru were related to COVID-19; however, cancer deaths have also been exacerbated in the first months of the pandemic. Despite this, excess mortalities of prostate, breast, and uterus cancer are not available by age group and region from January to December 2020. Therefore, we estimated the excess deaths and excess death rates (per 100,000 habitants) due to prostate, breast, and uterus cancer in 25 Peruvian regions. We did a time series analysis. Prostate, breast, and uterus cancer death data for 25 Peruvian regions were retrieved during the COVID-19 pandemic in 2020, as well as data for up to 3 years prior (2017-2019) from the Sistema Informatico Nacional de Defunciones at the Ministry of Health of Peru. Deaths in 2020 were defined as observed deaths. The expected deaths (in 2020) were estimated using the average deaths over 3 preceding years (2017, 2018 and 2019). Excess mortality was calculated as the difference between observed mortality and expected mortality in 2020. We estimated that the number of excess deaths and the excess death rates due to prostate, breast, and uterus cancer were 610 deaths (55%; 12.8 deaths per 100,000 men), 443 deaths (43%; 6 deaths per 100,000 women), and 154 deaths (25%; 2 deaths per 100,000 women), respectively. Excess numbers of deaths and excess death rates due to prostate and breast cancer increased with age. These excess deaths were higher in men aged ≥ 80 years (596 deaths (64%) and 150 deaths per 100,000 men) and women aged 70-79 years (229 deaths (58%) and 15 deaths per 100,000 women), respectively. In summary, during the COVID-19 pandemic, there were excess prostate and breast cancer mortalities in 2020 in Peru, while excess uterus cancer mortalities were low. Age-stratified excess death rates for prostate cancer and breast cancer were higher in men ≥ 80 years and in women ≥ 70 years, respectively.

Ethnic/Racial Disparity in Mortality from COVID-19: Data for the Year 2020 in Brazil.

The study aimed to investigate ethnic/racial disparities in COVID-19 mortality in Brazilian federative units and their respective capitals in 2020. Population data and number of COVID-19 deaths were extracted by skin color (white, black, brown and indigenous) from all Brazilian states and their respective capitals. The mortality rate of COVID-19 by ethnicity in Brazilian states was higher between people from brown skin color, followed by indigenous and black. Only in one state, in the Federal District and in the federal capital, age-standardized mortality rates were higher among white's people. There is a high percentage of deaths from COVID-19 higher than expected among non-white individuals, especially in south-central states and capitals of the country. Mortality from COVID-19 affect ethnic-racial groups unevenly in Brazil and the number of excess deaths among non-whites was over 9000. Urgent government measures are needed to reduce the racial disparity in health indicators in Brazil.

Excess mortality during the coronavirus pandemic (COVID-19) in Poland

Abstract The COVID-19 pandemic, has begun a global changes in the mortality model, exceeding its predicted levels under standard conditions. The aim of the study was to assess the phenomenon of excess mortality in Poland in 2020 and in the first half of 2021 compared to 2016-2019 based on the data of the Central Statistical Office. The number of excess deaths was defined as the difference between the deaths in 2021 and the average number of deaths in the previous years. In accordance with the Eurostat methodology the 2016-2019 average was taken as the reference point. In 2020, the number of deaths in Poland amounted to 485,259 and was higher by 14.9% than expected on the basis of mortality in 2016-2019 (the absolute excess number of deaths amounted to 67,112). 43% of the excess deaths were deaths caused by Sars-Cov-2, 27% other deaths among infected people, and 30% deaths among those without confirmed infection. In this group, the highest increases were recorded for deaths due to cardiovascular diseases, neurological diseases and mental disorders. In the first half of 2021, 270,662 people died in Poland, i.e. 23.9% more than in the corresponding period in 2016-2019 and 22.9% more than in the first half of 2020, whereas 58,096 people died due to COVID-19 (22% of all deaths). The highest increases for non-viral deaths compared to 2016-2019 were recorded for blood diseases and immune mechanisms (121.53%), infectious and parasitic diseases (90.76%), mental disorders (34.93%) and cardiovascular diseases (11.65%). Excess mortality is a very serious problem of the public health. The increased mortality in 2020 and 2021 was closely related to the pandemic, as direct COVID-19 victims accounted for the majority of the observed increases in mortality. However, attention should be paid to the growth in mortality related to other causes, mainly mental disorders, for which mortality increases most rapidly, which requires immediate action. Key messages • The increased mortality in 2020 and 2021 was closely related to the pandemic, as direct COVID-19 victims accounted for approximately 90% of the observed increases in mortality in Poland. • In the group of no-related with COVID-19 deaths the highest increases were recorded for mortality due to cardiovascular diseases, neurological diseases and mental disorders.

Assessment of disease burden related to non-optimal temperature across China

Objective: To estimate the excess mortality attributed to non-optimal ambient temperature in China. Methods: Mortality data and meteorological data from 239 counties in 2013-2018 were collected to simulate the quantitative exposure-response relationship between the temperature and mortality using distributed lag nonlinear models for time series studies. Then the number of non-optimal-temperature-related excess deaths was assessed and the spatial distribution was explored. Results: There were averagely (12±8) cases of all-cause deaths per day per county from 2013 to 2018. The average daily temperature was (14.98±10.31)℃, and the daily average relative humidity was (68.79±17.25)%. The daily average O3 concentration was (58.95±34.96) μg/m³, and the daily average PM2.5 concentration was (54.97±45.56) μg/m³. The exposure-response curve between daily average temperature and all-cause mortality showed a "U" shape, and the theoretical minimum mortality temperature (MMT) corresponding to the minimum number of deaths was 21.60 ℃. When the temperature was higher than MMT, the heat-related health effect increased with the temperature rising. When the temperature was lower than MMT, the cold-related effect increased with the temperature decreasing. The attributable fraction (AF) of death caused by non-optimal temperature was 8.76% (95%CI: 8.07%-9.10%), and the AF of death caused by cold effect and heat effect was 7.21% (95%CI: 6.51%-7.57%) and 1.55% (95%CI: 1.46%-1.61%), respectively. The excess deaths from non-optimal temperature in 2015 were 519 122, 72.98% of which could be attributed to low temperature. The number of excess deaths caused by non-optimal temperature mainly showed a decreasing trend from the east to the west, relatively high (117 522) in East China. Heilongjiang Province (in Northeast China) had the most excess deaths (26 924) caused by low temperature, and Guangdong Province(in South China) had the most excess deaths (27 763) caused by high temperature. Conclusion: The non-optimal temperature has a significant impact on health and causes a considerable burden of disease in China with obvious spatial heterogeneity.

Childhood adversity and energy poverty

The literature on the antecedents of energy poverty does not consider the potential role of early life experiences. This study fills this gap in the literature by providing causal evidence that early life experiences have a direct effect on subsequent energy poverty status. Using data from China Family Panel Studies, we analyze whether being a child or adolescent in the Great Chinese Famine raises the likelihood of being in energy poverty in adulthood. We find that, conditional on surviving, a one unit increase in the intensity of the Famine, measured by the number of excess deaths per 100 people, leads to a 1.2–1.6 percentage points decline in the probability of being in energy poverty in adulthood, depending on the exact specification and measure of energy poverty. We also find that personal income is a channel through which being a child or adolescent during the Great Famine affects the proclivity to be in energy poverty later in life. These findings are robust to alternative ways of measuring childhood adversity and energy poverty and suggest that resilience is an unobserved strength that carries meaningful economic consequences.

Mapping and bibliometric analysis of scientific publications on the use of textile materials for protection in pandemics

One of the main segments of technical textiles are textile materials applied in the medical field. These are products specifically developed to meet the demands of healthcare applications. These products are commonly used in personal protective clothing for healthcare professionals and patients, in order to avoid or minimize the risks of cross-infections. During the occurrence of pandemics, there is a worldwide spread of an epidemic causing an excessive number of deaths. In December 2019 there were the first cases of Severe Acute Respiratory Syndrome, caused by a new type of coronavirus, SARS-CoV-2, beginning the Coronavirus Pandemic. In that regard and considering the role of medical textiles for personal protection, the purpose of this work was to map and investigate the main research focuses related to the use of textile materials for protection in pandemics, in the last five years. The methodology used is the ProKnow-C, following all of its steps from the selection of databases and keywords, to obtaining and bibliometric analyzing the final portfolio with 16 articles. From this portfolio, it was possible to gain a knowledge base about textiles materials applied in the medical field. Also, identify the most relevant journals and authors and understand the focus of research now that is the development of respiratory protection masks. Still as a result of the research carried out, it is possible to note that the efforts to solve problems related to personal protection in the Medicine field results in an intense synergy between Textile Engineering and Materials Science.

Quantifying Utilitarian Outcomes to Inform Triage Ethics: Simulated Performance of a Ventilator Triage Protocol under Sars-CoV-2 Pandemic Surge Conditions

Background Equitable protocols to triage life-saving resources must be specified prior to shortages in order to promote transparency, trust and consistency. How well proposed utilitarian protocols perform to maximize lives saved is unknown. We aimed to estimate the survival rates that would be associated with implementation of the New York State 2015 guidelines for ventilator triage, and to compare them to a first-come-first-served triage method. Methods We constructed a simulation model based on a modified version of the New York State 2015 guidelines compared to a first-come-first-served method under various hypothetical ventilator shortages. We included patients with SARs-CoV-2 infection admitted with respiratory failure requiring mechanical ventilation to three acute care hospitals in New York from 3/01/2020 and 5/27/2020. We estimated (1) survival rates, (2) number of excess deaths, (3) number of patients extubated early or not allocated a ventilator due to capacity constraints, (4) survival rates among patients not allocated a ventilator at triage or extubated early due to capacity constraints. Results 807 patients were included in the study. The simulation model based on a modified New York State policy did not decrease mortality, excess death or exclusion from ventilators compared to the first-come-first-served policy at every ventilator capacity we tested using COVID-19 surge cohort patients. Survival rates were similar at all the survival probabilities estimated. At the lowest ventilator capacity, the modified New York State policy has an estimated survival of 28.5% (CI: 28.4-28.6), compared to 28.1% (CI: 27.7-28.5) for the first-come-first-served policy. Conclusions This simulation of a modified New York State guideline-based triage protocol revealed limitations in achieving the utilitarian goals these protocols are designed to fulfill. Quantifying these outcomes can inform a better balance among competing moral aims.

Estimating national excess mortality from subnational data: application to Argentina.

ABSTRACTThis paper presents a method to estimate excess mortality where national data are missing for some or all of the coronavirus disease 2019 (COVID-19) pandemic period, but subnational data exist, such as in Argentina. By making use of the stability of the regional distribution of deaths, data on deaths in Córdoba province were used to project excess deaths in Argentina from March 2020 up to the end of 2021. The number of excess deaths was estimated at 134 504, which is 14.8% higher than the reported number of COVID-19 deaths in Argentina for the same time period.

Underestimation in Reporting Excess COVID-19 Death Data in Poland during the First Three Pandemic Waves.

The issue whether official Polish COVID-19 death statistics correctly reflect the actual number of deaths is a contentious issue in public discourse and an important policy-wise question in Poland although it has not been the subject of thorough research so far. There had been clearly elevated excess mortality—5100 (death rate of 2.3 per 10,000) during the first wave, 77,500 (21.0 per 10,000) during the second one, and 48,900 (13.5 per 10,000) in the third. This study finds that during the second and the third pandemic wave, our data on excess mortality will match very well the somewhat belatedly officially reported COVID-19 deaths if we assume that only 60% of cases were officially detected. Based on principal component analysis of death timing, except for the age bracket below 40, where COVID-19 deaths calculated on the basis of our model explain 55% of excess mortality, for the remaining age groups, combined COVID-19 deaths explain 95% of excess mortality. Based on the share of excess mortality attributable to COVID-19 during the second wave, this infection in Poland caused the death of 73,300 people and not of 37,600 as officially reported. The third wave caused 46,200 deaths instead of the reported 34,700. The first wave was, indeed, as officially reported, very mild, and the number of excess deaths was too low to be used to calculate COVID-19 deaths directly. However, assuming that the detection rate remained comparable to the average in subsequent waves, we can set the number of deaths at 3500 instead of the reported 2100.

Temporal trends in cause-specific mortality in a rural-provincial area of Denmark, Lolland-Falster, 1970-2018.

In Denmark, rural-provincial Lolland-Falster currently has the highest mortality, caused mainly by the high mortality of in-migrating people. To identify possible preventive measures to combat this excess mortality insight into the underlying diseases is needed. We used data from Danish registers to calculate cause-specific mortality for 1970-1979, 1980-1989, 1990-1999, 2000-2009 and 2010-2018 divided into cancer, cardiovascular diseases, respiratory diseases, external causes and other causes (all remaining causes). We calculated age-standardised mortality rates for Lolland-Falster and the rest of Denmark: mortality rate ratios and excess number of deaths per 100,000 person-years for Lolland-Falster distinguishing between long-term residents (10+ years) and in-migrants. In 1970-1979, the age-standardised mortality rates for Lolland-Falster resembled those for rest of Denmark. Over time, age-standardised mortality rates for cardiovascular diseases decreased but more so for the rest of Denmark than for Lolland-Falster. Age-standardised mortality rates for other diseases increased but more so for Lolland-Falster than for the rest of Denmark. The excess mortality in Lolland-Falster derived in particular from in-migrants: in 2010-2018 the mortality rate ratios for this population reached 2.29 (95% confidence interval 1.96-2.69) for external causes and 2.12 (95% confidence interval 1.97-2.29) for other diseases. In-migrants had in total 411 excess deaths per 100,000 person-years. Of these 27% came from tobacco smoking-related causes of death. However, another 25% came from ill-defined, unspecified and a broad range of other, minor causes of deaths. The excess mortality of in-migrants to Lolland-Falster was attributable to all main causes of deaths, which stresses the complexity in combatting geographical disparities in mortality.

A population-based cohort approach to assess excess mortality due to the spread of COVID-19 in Italy, January-May 2020.

To assess the impact of the COVID-19 pandemic on all-cause mortality in Italy during the first wave of the epidemic, taking into consideration the geographical heterogeneity of the spread of COVID-19. This study is a retrospective, population-based cohort study using national statistics throughout Italy. Survival analysis was applied to data aggregated by day of death, age groups, sex, and Italian administrative units (107 provinces). We applied Cox models to estimate the relative hazards (RH) of excess mortality, comparing all-cause deaths in 2020 with the expected deaths from all causes in the same time period. The RH of excess deaths was estimated in areas with a high, moderate, and low spread of COVID-19. We reported the estimate also restricting the analysis to the period of March-April 2020 (first peak of the epidemic). The study population consisted of 57,204,501 individuals living in Italy as of January 1, 2020. The number of excess deaths was 36,445, which accounts for 13.4% of excess mortalities from all causes during January-May 2020 (i.e., RH = 1.134; 95% confidence interval (CI): 1.129-1.140). In the macro-area with a relatively higher spread of COVID-19 (i.e., incidence rate, IR): 450-1,610 cases per 100,000 residents), the RH of excess deaths was 1.375 (95% CI: 1.364-1.386). In the area with a relatively moderate spread of COVID-19 (i.e., IR: 150-449 cases) it was 1.049 (95% CI: 1.038-1.060). In the area with a relatively lower spread of COVID-19 (i.e., IR: 30-149 cases), it was 0.967 (95% CI: 0.959-0.976). Between March and April (peak months of the first wave of the epidemic in Italy), we estimated an excess mortality from all causes of 43.5%. The RH of all-cause mortality for increments of 500 cases per 100,000 residents was 1.352 (95% CI: 1.346-1.359), corresponding to an increase of about 35%. Our analysis, making use of a population-based cohort model, estimated all-cause excess mortality in Italy taking account of both time period and of COVID-19 geographical spread. The study highlights the importance of a temporal/geographic framework in analyzing the risk of COVID-19-epidemy related mortality.

Diagnostic and age composition of excess mortality associated with the New Year holidays in Russia

Statistics show that in many countries of the world holidays are associated with an increase in morbidity and mortality; this is especially pronounced during the New Year and Christmas period. This article presents an estimate of the excess number of deaths in Russia during the January holidays in 2011–2019 by main classes of causes of death and by age groups. The study relies on the Rosstat dataset of 16.83 million individual non-personalized death records referring to 2011–2019. The authors of the paper estimate excess mortality for each cause and age group as the difference between actually observed mortality and the LOWESS moving average calculated for non-holiday period, extrapolated to the holidays. The calculations showed that the period of excess mortality lasted from January 1 to January 22 with a maximum on January 1. Over 22 days, excess mortality in 2011–2019 amounted to 89.0 thousand cases or 8.4% in relation to mortality on non-holidays; excess mortality on January 1 amounted to 11.4 thousand cases. In contrast to mortality from diseases of the circulatory, respiratory, and digestive systems, the contribution of which to excess mortality was proportional to their prevalence on non-holidays, proportion of excess mortality from external causes almost doubled (23.6% versus 12.7 % on weekdays). January 1 saw the highest excess mortality from external causes, including that of alcohol poisoning, homicide, and suicide, in all age groups; on January 2 the highest increase was observed in mortality from diseases of the circulatory system; on January 9 and 10 — from the pathologies of the respiratory and digestive systems. January holidays in Russia are associated with significant excess mortality, primarily as a result of the abuse of strong alcoholic beverages. Informing the population about the fatal consequences of such a consumption regime and a decrease in the availability of strong alcohol, the maximum sales of which falls on December, can reduce the damage during the January holidays.

Estimation of Excess Deaths in Turin from COVID-19 and other causes, October to November 2020

IntroductionUnderstanding the effect of COVID-19 on mortality during this emergency and evaluating unexplained increases in deaths due to nonspecific outcomes can provide a more complete picture of this period and give better instrument to deal with the pandemy in the future.ObjectiveThe aim is to evaluate in the city of Turin the excess in the number of deaths from October to November 2020.MethodsThe number of excess deaths was defined as the difference between the deaths observed in the pandemic period of 2020 and the deaths expected for the years 2014-2019.ResultsThere were approximately 2047 total all causes deaths in Turin October 1 to November 30 2020, representing 630 more deaths than would typically be expected at that time of year. This excess was higher between men than in women. The number of excess all cause death was higher in 80 years old, less evident between 60-79 years old and very few between under 60 years old. Regarding the place of death, the number of excess all cause death was higher in hospital or in some health institutions for old people. Regarding the causes of deaths the explanation of these excess of deaths was COVID-19 infection only for a part of deaths and there are some excess of deaths not caused by COVID-19. The cause of excess of death not COVID-19 seems to be due to cardiovascular diseases, respiratory diseases, psychiatric disorders, neurological diseases, diabetes or nephrological diseases and to other undefinited causes.ConclusionsThe results showed during pandemic an increase of mortality respect to the expected mortality. Only a part of this excess deaths is due to COVID-19 but there is a relevant percentage of excess of deaths apparentely not due to COVID-19 but probably due to other causes. A better knowledge of these phenomena could help to improve any gaps in territorial assistance and provide indications for the future management of the pandemic in Europe.Key messages Increase of mortality in pandemic respect to the expected mortality.There is an excess of deaths apparentely not due to COVID-19.