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Evidence that more people in some countries and fewer in others are dying because of the pandemic, than is reflected by reported coronavirus disease 2019 (Covid-19) mortality rates, is derived from mortality data. Using publicly available databases, deaths attributed to Covid-19 in 2020 and all deaths for the years 2015–2020 were tabulated for 35 countries together with economic, health, demographic and government response stringency index variables. Residual mortality rates (RMR) in 2020 were calculated as excess mortality minus reported mortality rates due to Covid-19 where excess deaths were observed deaths in 2020 minus the average for 2015–2019. Differences in RMR are differences not attributed to reported Covid-19. For about half the countries, RMR's were negative and for half, positive. The absolute rates in some countries were double those in others. In a regression analysis, population density and proportion of female smokers were positively associated with both Covid-19 and excess mortality while the human development index and proportion of male smokers were negatively associated with both. RMR was not associated with any of the investigated variables. The results show that published data on mortality from Covid-19 cannot be directly comparable across countries. This may be due to differences in Covid-19 death reporting and in addition, the unprecedented public health measures implemented to control the pandemic may have produced either increased or reduced excess deaths due to other diseases. Further data on cause-specific mortality is required to determine the extent to which residual mortality represents non-Covid-19 deaths and to explain differences between countries.

Excess mortality is often used to estimate the effect of a certain crisis on the population. It is defined as the number of deaths during a crisis exceeding the expected number based on historical trends. Here, we calculated excess mortality due to the COVID-19 pandemic for Croatia in the 2020–2021 period. The excess was calculated on the national and county level for different age and sex categories. In addition to the absolute number, the excess mortality was also expressed as a ratio of excess deaths to the predicted baseline and excess mortality rate. We showed that using both measures is necessary to avoid incorrect conclusions. The estimated excess mortality on the national level was 14,963, corresponding to an excess percentage of 14.3%. With respect to sex, there was a higher excess mortality rate for men compared to women. An exponential relationship was observed between age and the excess mortality rate.These trends wee representative of most counties as well, with large variations in the magnitude of the effect. However, there were also exceptions to the general rule. The reasons for these deviations were discussed in terms of between-county differences in demographic structure, population density and special events that took place during the pandemic.

Background Comparing non-randomized groups, such as COVID-19 vaccinated and unvaccinated, even in the presence of seemingly relevant control variables, is challenging, but in this study, using English data, I show an achievable approach. Methods First, I estimated age-standardized all-cause mortality among vaccinated and unvaccinated ten years and older, covering 26 months from Apr 21 to May 23. Then, I estimated mortality not involving COVID-19, and finally, I contrasted the calculations. Results First, I found that all-cause mortality among unvaccinated was higher than among vaccinated. But, as the pattern was similar concerning mortality not involving COVID-19, the discrepancy can be attributed mainly to unvaccinated having inferior health at the outset. There were nonetheless indications of significant protection for vaccinated between July 21 and Jan 22. In the absence of control variables as a means to compare non-randomized groups, I reached that conclusion by contrasting all-cause mortality with mortality not involving COVID-19. However, while mortality not involving COVID-19 decreased among unvaccinated compared to the first observation month, it remained high among vaccinated, indicating a relative increase. Conclusions An interpretation is that vaccination, despite a potential temporary protection, has increased mortality. Strengthening the interpretation was relatively high mortality among vaccinated not involving COVID-19 counterintuitively following periods of excess mortality. Further strengthening the interpretation was the relatively high mortality not involving COVID-19 among vaccinated, corresponding with excess mortality during much of the same period. Future research should include data over a longer period than those available for this study. Also, future research should examine different age groups, vaccination types, and the number of doses given.

BackgroundExcess mortality provides a comprehensive measure to assess the true impact of the disease on mortality rates. This study aimed to quantify excess mortality attributable to COVID-19 in northeastern Iran during the pandemic period (2020–2022).MethodsThis population-based cross-sectional study utilized population and mortality data extracted from electronic systems linked to Mashhad University of Medical Sciences (MUMS). Data analysis was conducted using R Version 4.3.3. A log-linear model was employed to predict expected deaths during the two-year pandemic period, incorporating predictor variables such as the year of interest, the presence of COVID-19, and the population size for each respective year. Excess deaths were calculated as the difference between the expected and observed mortality. Furthermore, by considering the confirmed deaths directly attributed to COVID-19 and the difference between these and the excess deaths, the number of indirect deaths during the pandemic was determined.ResultsThe total count of recorded deaths from all causes exceeded the expected deaths by 31.15% (6750 cases) in the first year and 44.74% (10 078 cases) in the second year. The excess deaths were 1.48 and 1.79 times greater than the official reports of COVID-19 for the first and second years, respectively. It was also found that men experienced increased rates of excess deaths in each of the two years. Moreover, urban residents experienced higher rates of excess death in the same years. Based on cause-specific excess mortality, following infectious diseases, cardiovascular diseases (CVDs) accounted for the largest proportion of excess deaths in both years of the pandemic.ConclusionThe overall mortality burden during the COVID-19 pandemic exceeded the official reports, highlighting the undercounting of the number of direct effects and emphasizing the significance of indirect effects. These findings underscore the importance of preparedness and organization of healthcare systems prior to a pandemic.

The long-term mortality risk of natural disasters is a key threat to disaster resilience improvement, yet an authoritative certification and a reliable surveillance system are, unfortunately, yet to be established in many countries. This study aimed to clarify the mechanism of post-disaster indirect deaths in Japan, to improve the existing disaster recovery evaluation system and support decision making in public policy. This study first investigated the definition of indirect deaths via a literature review before examining the observed number of indirect deaths via case study, census data from the Population Demographic and Household Surveys, other social surveys, and reports in the case of the Great East Japan Earthquake and Tsunami, which severely damaged northeastern Japan, especially the three prefectures, which are the target areas in this context (i.e., Fukushima, Iwate, and Miyagi). It was found that the reported number of indirect deaths was significantly underestimated. In total, 4657 indirect deaths were estimated to have occurred in the target prefectures. This was higher than the reported number, which was 3784. The overall statistics established via collaboration between local administrations and governments can be improved to provide better reference for researchers and policymakers to investigate the long-term effects of natural disaster.

Thailand has experienced the most prominent COVID-19 outbreak in 2021, resulting in a new record for COVID-19 cases and deaths. To assess the influence of the COVID-19 outbreak on mortality, we estimated excess all-cause and pneumonia mortality in Thailand during the COVID-19 outbreak from April to October 2021. We used mortality from the previous 5 years to estimate the baseline number of deaths using generalized linear mixed models. The models were adjusted for seasonality and demographics. We found that, during the outbreak in 2021, there was a significant rise in excess fatalities, especially in the older age groups. The estimated cumulative excess death 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, excess pneumonia deaths were also found to be 26.2% (95% CI: 4.8–46.0%) above baseline.

Excess mortality provides a comprehensive measure to assess the true impact of the disease on mortality rates. This study aimed to quantify excess mortality attributable to COVID-19 in northeastern Iran during the pandemic period (2020-2022). This population-based cross-sectional study utilized population and mortality data extracted from electronic systems linked to Mashhad University of Medical Sciences (MUMS). Data analysis was conducted using R Version 4.3.3. A log-linear model was employed to predict expected deaths during the two-year pandemic period, incorporating predictor variables such as the year of interest, the presence of COVID-19, and the population size for each respective year. Excess deaths were calculated as the difference between the expected and observed mortality. Furthermore, by considering the confirmed deaths directly attributed to COVID-19 and the difference between these and the excess deaths, the number of indirect deaths during the pandemic was determined. The total count of recorded deaths from all causes exceeded the expected deaths by 31.15% (6750 cases) in the first year and 44.74% (10 078 cases) in the second year. The excess deaths were 1.48 and 1.79 times greater than the official reports of COVID-19 for the first and second years, respectively. It was also found that men experienced increased rates of excess deaths in each of the two years. Moreover, urban residents experienced higher rates of excess death in the same years. Based on cause-specific excess mortality, following infectious diseases, cardiovascular diseases (CVDs) accounted for the largest proportion of excess deaths in both years of the pandemic. The overall mortality burden during the COVID-19 pandemic exceeded the official reports, highlighting the undercounting of the number of direct effects and emphasizing the significance of indirect effects. These findings underscore the importance of preparedness and organization of healthcare systems prior to a pandemic.

Background The seasonal cycle of the influenza virus causes substantial morbidity and mortality globally. The impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on the circulation of influenza viruses can influence influenza-associated excess mortality. Given the few studies that have explored this topic, the objective of this study was to evaluate influenza-associated excess mortality in the Chinese mainland from 2012 to 2021 and quantify the changes from 2020 to 2021 compared with 2012–2019. Methods Using data from national influenza surveillance report and disease surveillance points, we fitted a generalized additive model on all-cause (AC), pneumonia & influenza (P&I), and respiratory (R) mortality rates. In this model, we included data of influenza activity (A/H1N1, A/H3N2 and B), temperature, absolute humidity, the COVID-19 pandemic, and time trends. The excess mortality was estimated by subtracting the fitted baseline mortality from the predicted mortality, which set influenza activity to zero. Results The respiratory mortality model explained more than 90% of the variance, indicating the good performance. We found that the influenza-associated mortality was generally decreasing from 2020 to 2021, for instance, influenza A/H1N1-associated excess respiratory mortality (ERM) decreased from 2.62 per 100,000 persons (95% confidence interval: 0.16–5.21) to 0.31 (0.02–0.60) in the northern region and from 3.79 (0.09–7.05) to 0.24 (0.02–0.46) in the southern region between 2012–2019 and 2020–2021. A similar pattern was observed for A/H3N2-associated ERM. While the influenza B remained similar scale, for instance, the ERM was 2.90 (0.72–4.3) and 2.26 (1.76–2.76) in the southern region between 2012–2019 and 2020–2021, respectively. Distinct pattern was observed for the AC and P&I outcomes. Conclusions The COVID-19 pandemic has reduced influenza-associated excess mortality, which may be a result of the reduced activity of the influenza virus caused by nonpharmaceutical interventions. Different patterns of regional differences differed for influenza-associated AC, P&I and R mortality. It should be noticed that the contribution of influenza B was generally similar when comparing 2012–2019 and 2020–2021, which highlighted the attention on the influenza B activity. Additional studies are needed to explore the changes in influenza-associated excess mortality afterwards.

Ever since their arrival in North America, European colonists and their descendants have struggled to explain the epidemics that decimated native populations. Century after century, they tried to understand the causes of epidemics, the vulnerability of American Indians, and the persistence of health disparities. They confronted their own responsibility for the epidemics, accepted the obligation to intervene, and imposed social and medical reforms to improve conditions. In Rationalizing Epidemics, David Jones examines crucial episodes in this history: Puritan responses to Indian depopulation in the seventeenth century; attempts to spread or prevent smallpox on the Western frontier in the eighteenth and nineteenth centuries; tuberculosis campaigns on the Sioux reservations from 1870 until 1910; and programs to test new antibiotics and implement modern medicine on the Navajo reservation in the 1950s. These encounters were always complex. Colonists, traders, physicians, and bureaucrats often saw epidemics as markers of social injustice and worked to improve Indians' health. At the same time, they exploited epidemics to obtain land, fur, and research subjects, and used health disparities as grounds for \"civilizing\" American Indians. Revealing the economic and political patterns that link these cases, Jones provides insight into the dilemmas of modern health policy in which desire and action stand alongside indifference and inaction.

Background Standardized mortality surveillance data, capable of detecting variations in total mortality at population level and not only among the infected, provide an unbiased insight into the impact of epidemics, like COVID-19 (Coronavirus disease). We analysed the temporal trend in total excess mortality and deaths among positive cases of SARS-CoV-2 by geographical area (north and centre-south), age and sex, taking into account the deficit in mortality in previous months. Methods Data from the Italian rapid mortality surveillance system was used to quantify excess deaths during the epidemic, to estimate the mortality deficit during the previous months and to compare total excess mortality with deaths among positive cases of SARS-CoV-2. Data were stratified by geographical area (north vs centre and south), age and sex. Results COVID-19 had a greater impact in northern Italian cities among subjects aged 75–84 and 85+ years. COVID-19 deaths accounted for half of total excess mortality in both areas, with differences by age: almost all excess deaths were from COVID-19 among adults, while among the elderly only one third of the excess was coded as COVID-19. When taking into account the mortality deficit in the pre-pandemic period, different trends were observed by area: all excess mortality during COVID-19 was explained by deficit mortality in the centre and south, while only a 16% overlap was estimated in northern cities, with quotas decreasing by age, from 67% in the 15–64 years old to 1% only among subjects 85+ years old. Conclusions An underestimation of COVID-19 deaths is particularly evident among the elderly. When quantifying the burden in mortality related to COVID-19, it is important to consider seasonal dynamics in mortality. Surveillance data provide an impartial indicator for monitoring the following phases of the epidemic, and may help in the evaluation of mitigation measures adopted.