Age-specific severity of severe acute respiratory syndrome coronavirus 2 in February 2020 to June 2021 in the Netherlands.

Background: The severity of Severe Acute Respiratory Syndrome Coronavirus 2 infection varies with age and time. Here, we quantify how age-specific risks of hospitalization, intensive care unit (ICU) admission, and death upon infection changed from February 2020 to June 2021 in the Netherlands. Methods: A series of large representative serology surveys allowed us to estimate age-specific numbers of infections in three epidemic periods (late-February 2020 to mid-June 2020, mid-June 2020 to mid-February 2021, and mid-February 2021 to late-June 2021). We accounted for reinfections and breakthrough infections. Severity measures were obtained by combining infection numbers with age-specific numbers of hospitalization, ICU admission, and excess all-cause deaths. Results: There was an accelerating, almost exponential, increase in severity with age in each period. The rate of increase with age was the highest for death and the lowest for hospitalization. In late-February 2020 to mid-June 2020, the overall risk of hospitalization upon infection was 1.5% (95% confidence interval [CI] 1.3-1.8%), the risk of ICU admission was 0.36% (95% CI: 0.31-0.42%), and the risk of death was 1.2% (95% CI: 1.0-1.4%). The risk of hospitalization was significantly increased in mid-June 2020 to mid-February 2021, while the risk of ICU admission remained stable over time. The risk of death decreased over time, with a significant drop among ≥70-years-olds in mid-February 2021 to late-June 2021; COVID-19 vaccination started early January 2021. Conclusion: Whereas the increase in severity of Severe Acute Respiratory Syndrome Coronavirus 2 with age remained stable, the risk of death upon infection decreased over time. A significant drop in risk of death among elderly coincided with the introduction of COVID-19 vaccination.

Inequalities in COVID-19 deaths by migration background during the first wave, interwave period and second wave of the COVID-19 pandemic: a closed cohort study of 17 million inhabitants of the Netherlands.

BACKGROUND: It is not known how differences in COVID-19 deaths by migration background in the Netherlands evolved throughout the pandemic, especially after introduction of COVID-19 prevention measures targeted at populations with a migration background (in the second wave). We investigated associations between migration background and COVID-19 deaths across first wave of the pandemic, interwave period and second wave in the Netherlands. METHODS: We obtained multiple registry data from Statistics Netherlands spanning from 1 March 2020 to 14 March 2021 comprising 17.4 million inhabitants. We estimated incidence rate ratios for COVID-19 deaths by migration background using Poisson regression models and adjusted for relevant sociodemographic factors. RESULTS: Populations with a migration background, especially those with Turkish, Moroccan and Surinamese background, exhibited higher risk of COVID-19 deaths than the Dutch origin population throughout the study periods. The elevated risk of COVID-19 deaths among populations with a migration background (as compared with Dutch origin population) was around 30% higher in the second wave than in the first wave. CONCLUSIONS: Differences in COVID-19 deaths by migration background persisted in the second wave despite introduction of COVID-19 prevention measures targeted at populations with a migration background in the second wave. Research on explanatory mechanisms and novel prevention measures are needed to address the ongoing differences in COVID-19 deaths by migration background.

Excess Deaths during Influenza and Coronavirus Disease and Infection-Fatality Rate for Severe Acute Respiratory Syndrome Coronavirus 2, the Netherlands.

Since the 2009 influenza pandemic, the Netherlands has used a weekly death monitoring system to estimate deaths in excess of expectations. We present estimates of excess deaths during the ongoing coronavirus disease (COVID-19) epidemic and 10 previous influenza epidemics. Excess deaths per influenza epidemic averaged 4,000. The estimated 9,554 excess deaths (41% in excess) during the COVID-19 epidemic weeks 12-19 of 2020 appeared comparable to the 9,373 excess deaths (18%) during the severe influenza epidemic of 2017-18. However, these deaths occurred in a shorter time, had a higher peak, and were mitigated by nonpharmaceutical control measures. Excess deaths were 1.8-fold higher than reported laboratory-confirmed COVID-19 deaths (5,449). Based on excess deaths and preliminary results from seroepidemiologic studies, we estimated the infection-fatality rate to be 1%. Monitoring of excess deaths is crucial for timely estimates of disease burden for influenza and COVID-19. Our data complement laboratory-confirmed COVID-19 death reports and enable comparisons between epidemics.

Real-time monitoring shows substantial excess all-cause mortality during second wave of COVID-19 in Europe, October to December 2020.

The European monitoring of excess mortality for public health action (EuroMOMO) network monitors weekly excess all-cause mortality in 27 European countries or subnational areas. During the first wave of the coronavirus disease (COVID-19) pandemic in Europe in spring 2020, several countries experienced extraordinarily high levels of excess mortality. Europe is currently seeing another upsurge in COVID-19 cases, and EuroMOMO is again witnessing a substantial excess all-cause mortality attributable to COVID-19.

Comparing strategies for matching mortality forecasts to the most recently observed data: exploring the trade-off between accuracy and robustness.

BACKGROUND: Given the increased link between retirement age and payments to the development in life expectancy, a precise and regular forecast of life expectancy is of utmost importance. The choice of the jump-off rates, i.e. the rates in the last year of the fitting period, is essential for matching mortality forecasts to the most recently observed data. A general approach to the choice of the jump-off rates is currently lacking. OBJECTIVE: We evaluate six different options for the jump-off rates and examine their effects on the robustness and accuracy of the mortality forecast. DATA AND METHODS: Death and exposure numbers by age for eight European countries over the years 1960-2014 were obtained from the Human Mortality Database. We examined the use of model values as jump-off rates versus observed values in the last year or averaged over the last couple of years. The future life expectancy at age 65 is calculated for different fitting periods and jump-off rates using the Lee-Carter model and examined on accuracy (mean absolute forecast error) and robustness (standard deviation of the change in projected e65). RESULTS: The choice for the jump-off rates clearly influences the accuracy and robustness of the mortality forecast, albeit in different ways. For most countries using the last observed values as jump-off rates resulted in the most accurate method, which relates to the relatively high estimation error of the model in recent years. The most robust method is obtained by using an average of observed years as jump-off rates. The more years that are averaged, the better the robustness, but accuracy decreases with more years averaged. CONCLUSION: Carefully considering the best choice for the jump-off rates is essential when forecasting mortality. The best strategy for matching mortality forecasts to the most recently observed data depends on the goal of the forecast, the country-specific past mortality trends observed, and the model fit.

Ethnic Differences in Returning Home: Explanations From a Life Course Perspective.

Ethnic differences in leaving and returning home may reflect varying cultural norms regarding intergenerational coresidence, but also differences in transitions in linked domains, for example, employment and partnership transitions. This study uses Dutch population register data to compare returning home among second-generation Turks, Moroccans, Surinamese, and Antilleans with native Dutch who had left the parental home between age 16 and 28 in the period 1999 to 2011 (N = 194,020). All second-generation groups were found to be more likely to return home than native Dutch. A large part of these differences was related to the timing and occurrence of other key events in the life course, such as age at leaving home and partnership dissolution. Although the impact of partnership dissolution on returning home was found to be strong among all origin groups, it was less pronounced among second-generation youth, particularly Turks and Moroccans, than native Dutch youth. Possible explanations and implications are discussed.

The future of smoking-attributable mortality: the case of England & Wales, Denmark and the Netherlands.

AIMS: We formally estimate future smoking-attributable mortality up to 2050 for the total national populations of England & Wales, Denmark and the Netherlands, providing an update and extension of the descriptive smoking-epidemic model. METHODS: We used smoking prevalence and population-level lung cancer mortality data for England & Wales, Denmark and the Netherlands, covering the period 1950-2009. To estimate the future smoking-attributable mortality fraction (SAF) we: (i) project lung cancer mortality by extrapolating age-period-cohort trends, using the observed convergence of smoking prevalence and similarities in past lung cancer mortality between men and women as input; and (ii) add other causes of death attributable to smoking by applying a simplified version of the indirect Peto-Lopez method to the projected lung cancer mortality. FINDINGS: The SAF for men in 2009 was 19% (44 872 deaths) in England & Wales, 22% (5861 deaths) in Denmark and 25% (16 385 deaths) in the Netherlands. In our projections, these fractions decline to 6, 12 and 14%, respectively, in 2050. The SAF for women peaked at 14% (38 883 deaths) in 2008 in England & Wales, and is expected to peak in 2028 in Denmark (22%) and in 2033 in the Netherlands (23%). By 2050, a decline to 9, 17 and 19%, respectively, is foreseen. Different indirect estimation methods of the SAF in 2050 yield a range of 1-8% (England & Wales), 8-13% (Denmark) and 11-16% (the Netherlands) for men, and 7-16, 12-26 and 13-31% for women. CONCLUSIONS: From northern European data we project that smoking-attributable mortality will remain important for the future, especially for women. Whereas substantial differences between countries remain, the age-specific evolution of smoking-attributable mortality remains similar across countries and between sexes.