Magnitude and determinants of excess total, age-specific and sex-specific all-cause mortality in 24 countries worldwide during 2020 and 2021: results on the impact of the COVID-19 pandemic from the C-MOR project.

INTRODUCTION: To examine the impact of the COVID-19 pandemic on mortality, we estimated excess all-cause mortality in 24 countries for 2020 and 2021, overall and stratified by sex and age. METHODS: Total, age-specific and sex-specific weekly all-cause mortality was collected for 2015-2021 and excess mortality for 2020 and 2021 was calculated by comparing weekly 2020 and 2021 age-standardised mortality rates against expected mortality, estimated based on historical data (2015-2019), accounting for seasonality, and long-term and short-term trends. Age-specific weekly excess mortality was similarly calculated using crude mortality rates. The association of country and pandemic-related variables with excess mortality was investigated using simple and multilevel regression models. RESULTS: Excess cumulative mortality for both 2020 and 2021 was found in Austria, Brazil, Belgium, Cyprus, England and Wales, Estonia, France, Georgia, Greece, Israel, Italy, Kazakhstan, Mauritius, Northern Ireland, Norway, Peru, Poland, Slovenia, Spain, Sweden, Ukraine, and the USA. Australia and Denmark experienced excess mortality only in 2021. Mauritius demonstrated a statistically significant decrease in all-cause mortality during both years. Weekly incidence of COVID-19 was significantly positively associated with excess mortality for both years, but the positive association was attenuated in 2021 as percentage of the population fully vaccinated increased. Stringency index of control measures was positively and negatively associated with excess mortality in 2020 and 2021, respectively. CONCLUSION: This study provides evidence of substantial excess mortality in most countries investigated during the first 2 years of the pandemic and suggests that COVID-19 incidence, stringency of control measures and vaccination rates interacted in determining the magnitude of excess mortality.

Lifetime exposure to air pollution and academic achievement: A nationwide cohort study in Denmark.

Recent research suggests a link between air pollution and cognitive development in children, and studies on air pollution and academic achievement are emerging. We conducted a nationwide cohort study in Denmark to explore the associations between lifetime exposure to air pollution and academic performance in 9th grade. The study encompassed 785,312 children born in Denmark between 1989 and 2005, all of whom completed 9th-grade exit examinations. Using linear mixed models with a random intercept for each school, we assessed the relationship between 16 years of exposure to PM2.5, PM10, and gaseous pollutants and Grade Point Averages (GPA) in exit examinations, covering subjects such as Danish literature, Danish writing, English, mathematics, and natural sciences. The study revealed that a 5 µg/m3 increase in PM2.5 and PM10 was associated with a decrease of 0.99 (95 % Confidence Intervals: -1.05, -0.92) and 0.46 (-0.50, -0.41) in GPA, respectively. Notably, these negative associations were more pronounced in mathematics and natural sciences compared to language-related subjects. Additionally, girls and children with non-Danish mothers were found to be particularly susceptible to the adverse effects of air pollution exposure. These results underscore the potential long-term consequences of air pollution on academic achievement, emphasizing the significance of interventions that foster healthier environments for children's cognitive development.

Air pollution and human health: a phenome-wide association study.

OBJECTIVES: To explore the associations of long-term exposure to air pollution with onset of all human health conditions. DESIGN: Prospective phenome-wide association study. SETTING: Denmark. PARTICIPANTS: All Danish residents aged ≥30 years on 1 January 2000 were included (N=3 323 612). After exclusion of individuals with missing geocoded residential addresses, 3 111 988 participants were available for the statistical analyses. MAIN OUTCOME MEASURE: First registered diagnosis of every health condition according to the International Classification of Diseases, 10th revision, from 2000 to 2017. RESULTS: Long-term exposure to fine particulate matter (PM2.5) and nitrogen dioxide (NO2) were both positively associated with the onset of more than 700 health conditions (ie, >80% of the registered health conditions) after correction for multiple testing, while the remaining associations were inverse or insignificant. As regards the most common health conditions, PM2.5 and NO2 were strongest positively associated with chronic obstructive pulmonary disease (PM2.5: HR 1.06 (95% CI 1.05 to 1.07) per 1 IQR increase in exposure level; NO2: 1.14 (95% CI 1.12 to 1.15)), type 2 diabetes (PM2.5: 1.06 (95% CI 1.05 to 1.06); NO2: 1.12 (95% CI 1.10 to 1.13)) and ischaemic heart disease (PM2.5: 1.05 (95% CI 1.04 to 1.05); NO2: 1.11 (95% CI 1.09 to 1.12)). Furthermore, PM2.5 and NO2 were both positively associated with so far unexplored, but highly prevalent outcomes relevant to public health, including senile cataract, hearing loss and urinary tract infection. CONCLUSIONS: The findings of this study suggest that air pollution has a more extensive impact on human health than previously known. However, as this study is the first of its kind to investigate the associations of long-term exposure to air pollution with onset of all human health conditions, further research is needed to replicate the study findings.

Using sequences of life-events to predict human lives.

Here we represent human lives in a way that shares structural similarity to language, and we exploit this similarity to adapt natural language processing techniques to examine the evolution and predictability of human lives based on detailed event sequences. We do this by drawing on a comprehensive registry dataset, which is available for Denmark across several years, and that includes information about life-events related to health, education, occupation, income, address and working hours, recorded with day-to-day resolution. We create embeddings of life-events in a single vector space, showing that this embedding space is robust and highly structured. Our models allow us to predict diverse outcomes ranging from early mortality to personality nuances, outperforming state-of-the-art models by a wide margin. Using methods for interpreting deep learning models, we probe the algorithm to understand the factors that enable our predictions. Our framework allows researchers to discover potential mechanisms that impact life outcomes as well as the associated possibilities for personalized interventions.

Development of geographic inequality in dental caries and its association with socioeconomic factors over an 18-year period in Denmark.

BACKGROUND: Few studies have examined the development of geographic and socioeconomic inequalities in caries over time or have simultaneously assessed individual-level socioeconomic position (SEP) and neighborhood-level factors as a multi-layered phenomenon influencing caries inequalities. This study examined (i) the trends in geographic inequalities in caries among adolescents in Denmark and (ii) how the association between SEP and caries has progressed over time, when accounting for individual and neighborhood-level confounding factors. METHODS: This nationwide repeated cross-sectional study included 15-year-olds in Denmark from 1995, 2003, and 2013 (n = 149,808). The outcome was caries experience (measured by the decayed, missing, and filled tooth surfaces [DMFS] index). The exposure of interest was SEP, indicated by the previous year's parental education, occupational social class, and (equivalized) disposable household income. Covariates included individual-level factors (immigration status, country of origin, number of children and persons in the family, and household type) and neighborhood (residence municipality)-level factors (Gini index; proportion of unemployed, low-educated, and unmarried/non-cohabiting individuals; proportion of single-parent households and households with overcrowding). Data sources included the Danish national dental and administrative social registers and Statistics Denmark's statistics database (StatBank). Data were analyzed using spatial and spatiotemporal modelling utilizing zero-inflated negative binomial regressions and integrated nested Laplace approximations for Bayesian parametric inference. Observed caries experience geo-maps of the Danish municipalities for 1995, 2003, and 2013 were created. RESULTS: Between 1995 and 2013, caries prevalence in the 15-year-olds declined sharply (1995, 71%; 2013, 45%). Caries experience declined in nearly all socioeconomic subgroups and municipalities. However, geographic inequalities persisted with higher caries levels largely concentrated in the relatively deprived areas of Denmark. Increasing relative socioeconomic inequalities in caries over time were observed with significant graded associations between SEP and caries despite adjustment for the various individual and neighborhood-level covariates and the effect of assessment year (e.g., 15-year-olds with parents having basic education had 1.91-fold [95% CI: 1.86-1.95] higher caries experience than those having parents with high education). CONCLUSIONS: Reducing these enduring inequalities will likely require additional resources and targeted supportive and preventive measures for adolescents from lower SEP backgrounds and those residing in municipalities with higher caries prevalence.

Machine learning models of healthcare expenditures predicting mortality: A cohort study of spousal bereaved Danish individuals.

BACKGROUND: The ability to accurately predict survival in older adults is crucial as it guides clinical decision making. The added value of using health care usage for predicting mortality remains unexplored. The aim of this study was to investigate if temporal patterns of healthcare expenditures, can improve the predictive performance for mortality, in spousal bereaved older adults, next to other widely used sociodemographic variables. METHODS: This is a population-based cohort study of 48,944 Danish citizens 65 years of age and older suffering bereavement within 2013-2016. Individuals were followed from date of spousal loss until death from all causes or 31st of December 2016, whichever came first. Healthcare expenditures were available on weekly basis for each person during the follow-up and used as predictors for mortality risk in Extreme Gradient Boosting models. The extent to which medical spending trajectories improved mortality predictions compared to models with sociodemographics, was assessed with respect to discrimination (AUC), overall prediction error (Brier score), calibration, and clinical benefit (decision curve analysis). RESULTS: The AUC of age and sex for mortality the year after spousal loss was 70.8% [95% CI 68.8, 72.8]. The addition of sociodemographic variables led to an increase of AUC ranging from 0.9% to 3.1% but did not significantly reduce the overall prediction error. The AUC of the model combining the variables above plus medical spending usage was 80.8% [79.3, 82.4] also exhibiting smaller Brier score and better calibration. Overall, patterns of healthcare expenditures improved mortality predictions the most, also exhibiting the highest clinical benefit among the rest of the models. CONCLUSION: Temporal patterns of medical spending have the potential to significantly improve our assessment on who is at high risk of dying after suffering spousal loss. The proposed methodology can assist in a more efficient risk profiling and prognosis of bereaved individuals.

Predicting mortality risk after a fall in older adults using health care spending patterns: a population-based cohort study.

OBJECTIVE: To develop a prognostic model of 1-year mortality for individuals aged 65+ presenting at the emergency department (ED) with a fall based on health care spending patterns to guide clinical decision-making. DESIGN: Population-based cohort study (n = 35,997) included with a fall in 2013 and followed 1 year. METHODS: Health care spending indicators (dynamical indicators of resilience, DIORs) 2 years before admission were evaluated as potential predictors, along with age, sex and other clinical and sociodemographic covariates. Multivariable logistic regression models were developed and internally validated (10-fold cross-validation). Performance was assessed via discrimination (area under the receiver operating characteristic curve, AUC), Brier scores, calibration and decision curve analysis. RESULTS: The AUC of age and sex for mortality was 72.5% [95% confidence interval 71.8 to 73.2]. The best model included age, sex, number of medications and health care spending DIORs. It exhibited high discrimination (AUC: 81.1 [80.5 to 81.6]), good calibration and potential clinical benefit for various threshold probabilities. Overall, health care spending patterns improved predictive accuracy the most while also exhibiting superior performance and clinical benefit. CONCLUSIONS: Patterns of health care spending have the potential to significantly improve assessments on who is at high risk of dying following admission to the ED with a fall. The proposed methodology can assist in predicting the prognosis of fallers, emphasising the added predictive value of longitudinal health-related information next to clinical and sociodemographic predictors.

Danish Pathology Life Course (PATHOLIFE) cohort: a register based cohort extending upon a national tissue biobank.

PURPOSE: The Danish Pathology Life Course (PATHOLIFE) cohort was established to facilitate epidemiological research relating histological and cytological features extracted from patient tissue specimens to the rich life course histories, including both prior and future register data, of the entire Danish population. Research results may increase quality of diagnosis, prognosis and stratification of patient subtypes, possibly identifying novel routes of treatment. PARTICIPANTS: All Danish residents from 1 January 1986 to 31 December 2019, totalling 8 593 421 individuals. FINDINGS TO DATE: We provide an overview of the subpopulation of Danish residents who have had a tissue specimen investigated within the Danish healthcare system, including both the primary sector and hospitals. We demonstrate heterogeneity in sociodemographic and prognostic factors between the general Danish population and the above mentioned subpopulation, and also between the general Danish population and subpopulations of patients with tissue specimens from selected anatomical sites. Results demonstrate the potential of the PATHOLIFE cohort for integrating many different factors into identification and selection of the most valuable tissue blocks for studies of specific diseases and their progression. Broadly, we find that living with a partner, having higher education and income associates with having a biopsy overall. However, this association varies across different tissue and patient types, which also display differences in time-to-death and causes of death. FUTURE PLANS: The PATHOLIFE cohort may be used to study specified patient groups and link health related events from several national health registries, and to sample patient groups, for which stored tissue specimens are available for further research investigations. The PATHOLIFE cohort thereby provides a unique opportunity to prospectively follow people that were characterised and sampled in the past.

Sex differences in health care expenditures and mortality after spousal bereavement: A register-based Danish cohort study.

BACKGROUND: Spousal bereavement is a life event that affects older people differently. We investigated the impact of spousal bereavement on medical expenditures and mortality in the general population, emphasizing on age and sex. METHODS: Data are from a population-based, retrospective cohort study following 924,958 Danish citizens over the age of 65 years, within 2011-2016. Changes in health care expenditures in those who suffer bereavement were compared with time matched changes among those who did not. Mortality hazards were analysed with time to event analysis. RESULTS: A total of 77,722 (~8.4%) individuals experienced bereavement, 65.8% being females. Among males, bereavement was associated with increase of expenditures the year after, that was 42 Euros per week (95% CI, 36 to 48) larger than the non-bereaved group. The corresponding increase for females was 35 Euros per week (95% CI, 30 to 40). The increase of mortality hazards was highest in the first year after bereavement, higher in males than females, in young old and almost absent in the oldest old. Compared with the reference, mortality the year after spousal loss was 70% higher (HR 1.70 [95% CI 1.40 to 2.08]) for males aged 65-69 years and remained elevated for a period of six years. Mortality for females aged 65-69 years was 27% higher in the first year (HR 1.27, [1.07 to 1.52]), normalizing thereafter. CONCLUSION: Bereavement affects older people differently with younger males being most frail with limited recovery potential.

Predicting mortality and visualizing health care spending by predicted mortality in Danes over age 65.

Health care expenditure in the last year of life makes up a high proportion of medical spending across the world. This is often framed as waste, but this framing is only meaningful if it is known at the time of treatment who will go on to die. We analyze the distribution of health care spending by predicted mortality for the Danish population over age 65 over the year 2016, with one-year mortality predicted by a machine learning model based on sociodemographics and use of health care services for the two years before entry into follow-up. While a reasonably good model can be built, extremely few individuals have high ex-ante probability of dying, and those with a predicted mortality of more than 50% account for only 2.8% of total health care expenditure. Decedents outspent survivors by a factor of more than ten, but compared to survivors with similar predicted mortality they spent only 2.5 times as much. Our results suggest that while spending in the last year of life is indeed high, this is nearly all spent in situations where there is a reasonable expectation that the patient can survive.

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

AIM: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.

Impact of the COVID-19 pandemic on total, sex- and age-specific all-cause mortality in 20 countries worldwide during 2020: results from the C-MOR project.

BACKGROUND: To understand the impact of the COVID-19 pandemic on mortality, this study investigates overall, sex- and age-specific excess all-cause mortality in 20 countries, during 2020. METHODS: Total, sex- and age-specific weekly all-cause mortality for 2015-2020 was collected from national vital statistics databases. Excess mortality for 2020 was calculated by comparing weekly 2020 observed mortality against expected mortality, estimated from historical data (2015-2019) accounting for seasonality, long- and short-term trends. Crude and age-standardized rates were analysed for total and sex-specific mortality. RESULTS: Austria, Brazil, Cyprus, England and Wales, France, Georgia, Israel, Italy, Northern Ireland, Peru, Scotland, Slovenia, Sweden, and the USA displayed substantial excess age-standardized mortality of varying duration during 2020, while Australia, Denmark, Estonia, Mauritius, Norway, and Ukraine did not. In sex-specific analyses, excess mortality was higher in males than females, except for Slovenia (higher in females) and Cyprus (similar in both sexes). Lastly, for most countries substantial excess mortality was only detectable (Austria, Cyprus, Israel, and Slovenia) or was higher (Brazil, England and Wales, France, Georgia, Italy, Northern Ireland, Sweden, Peru and the USA) in the oldest age group investigated. Peru demonstrated substantial excess mortality even in the <45 age group. CONCLUSIONS: This study highlights that excess all-cause mortality during 2020 is context dependent, with specific countries, sex- and age-groups being most affected. As the pandemic continues, tracking excess mortality is important to accurately estimate the true toll of COVID-19, while at the same time investigating the effects of changing contexts, different variants, testing, quarantine, and vaccination strategies.

Selective migration and mortality by economic status in Lolland-Falster, Denmark, 1992-2018.

During the past 30 years, a mortality gap developed between Lolland-Falster (the rural-provincial southeastern part) and the rest of Denmark. A main driver was selective in-migration of Danes with a high risk of death, especially of working-ages. In the present study, we determined the role of economic status in this selective in-migration. We used individual-level data from the Central Population Register and data on income source; self- or publicly supported. The study population included people aged 30-64 and living in Denmark at any time between 1992 and 2018. Mortality rate ratios (MRR) were calculated using Poisson regression for three time-periods: 1992-1999, 2000-2009 and 2010-2018. Two in five in-migrants to Lolland-Falster were people on public support. In 2010-2018, they had an MRR of 8.71 (95% confidence interval (CI): 8.05-9.42) compared with self-supported people, and an MRR of 1.49 (95% CI: 1.38-1.61) compared with publicly supported people elsewhere in Denmark. In-migration of working-aged people on public support was a main contributor to the excess mortality in Lolland-Falster as compared with the rest of Denmark. To understand urban-rural differences in health, population movements and national income patterns are important to take into account.

Immigration, mortality, and national life expectancy in the Nordic region, 1990-2019.

•Immigrants have higher life expectancy at age 1 than the native-born in Denmark, Finland and Norway do from 1990 to 2019.•Immigrants in Denmark, Finland and Norway increasingly enhance national life expectancy at age 1 over time.•Immigrants in Sweden have lower life expectancy at age 1 than native-born in Sweden do in 1990, but similar levels by 2019.•The effect of immigrants on national life expectancy at age 1 in Sweden transforms from negative to positive over time.•The unique mortality of immigrants affects rankings of life expectancy at age 1 in the Nordic region in recent years.

Household transmission of the SARS-CoV-2 Omicron variant in Denmark.

In late 2021, the Omicron SARS-CoV-2 variant overtook the previously dominant Delta variant, but the extent to which this transition was driven by immune evasion or a change in the inherent transmissibility is currently unclear. We estimate SARS-CoV-2 transmission within Danish households during December 2021. Among 26,675 households (8,568 with the Omicron VOC), we identified 14,140 secondary infections within a 1-7-day follow-up period. The secondary attack rate was 29% and 21% in households infected with Omicron and Delta, respectively. For Omicron, the odds of infection were 1.10 (95%-CI: 1.00-1.21) times higher for unvaccinated, 2.38 (95%-CI: 2.23-2.54) times higher for fully vaccinated and 3.20 (95%-CI: 2.67-3.83) times higher for booster-vaccinated contacts compared to Delta. We conclude that the transition from Delta to Omicron VOC was primarily driven by immune evasiveness and to a lesser extent an inherent increase in the basic transmissibility of the Omicron variant.

Household transmission of SARS-CoV-2 Omicron variant of concern subvariants BA.1 and BA.2 in Denmark.

SARS coronavirus 2 (SARS-CoV-2) continues to evolve and new variants emerge. Using nationwide Danish data, we estimate the transmission dynamics of SARS-CoV-2 Omicron subvariants BA.1 and BA.2 within households. Among 22,678 primary cases, we identified 17,319 secondary infections among 50,588 household contacts during a 1-7 day follow-up. The secondary attack rate (SAR) was 29% and 39% in households infected with Omicron BA.1 and BA.2, respectively. BA.2 was associated with increased susceptibility of infection for unvaccinated household contacts (Odds Ratio (OR) 1.99; 95%-CI 1.72-2.31), fully vaccinated contacts (OR 2.26; 95%-CI 1.95-2.62) and booster-vaccinated contacts (OR 2.65; 95%-CI 2.29-3.08), compared to BA.1. We also found increased infectiousness from unvaccinated primary cases infected with BA.2 compared to BA.1 (OR 2.47; 95%-CI 2.15-2.84), but not for fully vaccinated (OR 0.66; 95%-CI 0.57-0.78) or booster-vaccinated primary cases (OR 0.69; 95%-CI 0.59-0.82). Omicron BA.2 is inherently more transmissible than BA.1. Its immune-evasive properties also reduce the protective effect of vaccination against infection, but do not increase infectiousness of breakthrough infections from vaccinated individuals.

Polypharmacy occurrence and the related risk of premature death among older adults in Denmark: A nationwide register-based cohort study.

BACKGROUND: Polypharmacy, defined as the concurrent use of ≥5 medications, increases the risk of drug-drug and drug-disease interactions as well as non-adherence to drug therapy. This may have negative health consequences particularly among older adults due to age-related pharmacokinetic and pharmacodynamic changes. This study aims to uncover the occurrence of polypharmacy among older adults in Denmark and investigate how polypharmacy relates to mortality. METHOD: This nationwide register-based study included 1,338,058 adults aged 65+ years between January 2013 and December 2017 in Denmark. Polypharmacy prevalence was measured at time of inclusion while incidence and the association between polypharmacy and mortality were measured over the five-year follow-up using Cox regression. In an attempt to adjust for confounding by indication, propensity scores with overlap weighting were introduced to the regression model. RESULTS: At time of inclusion, polypharmacy prevalence was 29% and over the five years follow-up, 47% of the remaining adults transitioned into polypharmacy. Identified risk factors included multimorbidity (2+ morbidities: HR = 3.51; 95% CI = 3.48-3.53), age (95+ years: HR = 2.85; 95% CI = 2.74-2.96), socioeconomic factors (Highest income quartile: HR = 0.81; 95% CI = 0.80-0.81), region of birth region (Non-western migrants: HR = 0.77; 95% CI = 0.75-0.79), marital status (Divorced: HR = 1.10; 95% CI = 1.10-1.12) and year of inclusion (2017: HR = 1.19; 95% CI = 1.19-1.22). Further analyses showed that polypharmacy involves many different drug cocktails with medication for the cardiovascular system (95%), blood and blood-forming organs (69%), alimentary tract and metabolism (61%) and nervous system (54%) contributing the most. After adjustment for propensity scores with OW, both polypharmacy (HR = 3.48, CI95% = 3.41-3.54) and excessive polypharmacy (HR = 3.48, CI95% = 3.43-3.53) increased the risk of death substantially. CONCLUSION: A considerable proportion of older adults in Denmark were exposed to polypharmacy dependent on health status, socio-economic status, and societal factors. The associated three- to four-fold mortality risk indicate a need for further exploration of the appropriateness of polypharmacy among older adults.

Excess all-cause mortality and COVID-19-related mortality: a temporal analysis in 22 countries, from January until August 2020.

BACKGROUND: This study aimed to investigate overall and sex-specific excess all-cause mortality since the inception of the COVID-19 pandemic until August 2020 among 22 countries. METHODS: Countries reported weekly or monthly all-cause mortality from January 2015 until the end of June or August 2020. Weekly or monthly COVID-19 deaths were reported for 2020. Excess mortality for 2020 was calculated by comparing weekly or monthly 2020 mortality (observed deaths) against a baseline mortality obtained from 2015-2019 data for the same week or month using two methods: (i) difference in observed mortality rates between 2020 and the 2015-2019 average and (ii) difference between observed and expected 2020 deaths. RESULTS: Brazil, France, Italy, Spain, Sweden, the UK (England, Wales, Northern Ireland and Scotland) and the USA demonstrated excess all-cause mortality, whereas Australia, Denmark and Georgia experienced a decrease in all-cause mortality. Israel, Ukraine and Ireland demonstrated sex-specific changes in all-cause mortality. CONCLUSIONS: All-cause mortality up to August 2020 was higher than in previous years in some, but not all, participating countries. Geographical location and seasonality of each country, as well as the prompt application of high-stringency control measures, may explain the observed variability in mortality changes.

Preterm birth after the introduction of COVID-19 mitigation measures in Norway, Sweden, and Denmark: a registry-based difference-in-differences study.

BACKGROUND: Although some studies have reported a decrease in preterm birth following the start of the COVID-19 pandemic, the findings are inconsistent. OBJECTIVE: This study aimed to compare the incidences of preterm birth before and after the introduction of COVID-19 mitigation measures in Scandinavian countries using robust population-based registry data. STUDY DESIGN: This was a registry-based difference-in-differences study using births from January 2014 through December 2020 in Norway, Sweden, and Denmark. The changes in the preterm birth (<37 weeks) rates before and after the introduction of COVID-19 mitigation measures (set to March 12, 2020) were compared with the changes in preterm birth before and after March 12 from 2014 to 2019. The differences per 1000 births were calculated for 2-, 4-, 8-, 12-, and 16-week intervals before and after March 12. The secondary analyses included medically indicated preterm birth, spontaneous preterm birth, and very preterm (<32 weeks) birth. RESULTS: A total of 1,519,521 births were included in this study. During the study period, 5.6% of the births were preterm in Norway and Sweden, and 5.7% were preterm in Denmark. There was a seasonal variation in the incidence of preterm birth, with the highest incidence during winter. In all the 3 countries, there was a slight overall decline in preterm births from 2014 to 2020. There was no consistent evidence of a change in the preterm birth rates following the introduction of COVID-19 mitigation measures, with difference-in-differences estimates ranging from 3.7 per 1000 births (95% confidence interval, -3.8 to 11.1) for the first 2 weeks after March 12, 2020, to -1.8 per 1000 births (95% confidence interval, -4.6 to 1.1) in the 16 weeks after March 12, 2020. Similarly, there was no evidence of an impact on medically indicated preterm birth, spontaneous preterm birth, or very preterm birth. CONCLUSION: Using high-quality national data on births in 3 Scandinavian countries, each of which implemented different approaches to address the pandemic, there was no evidence of a decline in preterm births following the introduction of COVID-19 mitigation measures.