Age, gender and COVID-19 infections

Data for ten European countries which provide detailed distribution of COVID-19 cases by sex and age show that among people of working age, women diagnosed with COVID-19 substantially outnumber infected men. This pattern reverses around retirement: infection rates among women fall at age 60-69, resulting in a cross-over with infection rates among men. The relative disadvantage of women peaks at ages 20-29, whereas the male disadvantage in infection rates peaks at ages 70-79. The elevated infection rates among women of working age are likely tied to their higher share in health- and care-related occupations. Our examination also suggests a link between women's employment profiles and infection rates in prime working ages. The same factors that determine women's higher life expectancy account for their lower fatality and higher male disadvantage at older ages

The impact of COVID-19 vaccines on the Case Fatality Rate: The importance of monitoring breakthrough infections

Objectives: Test the behavior of the case fatality rate in a mixed population of vaccinated and unvaccinated individuals by illustrating the role of both the effectiveness of vaccines in preventing deaths and the detection of infections among both the vaccinated (breakthrough infections) and unvaccinated individuals. Methods: We simulate three hypothetical case fatality rate scenarios that result from a different combination of vaccine effectiveness in preventing deaths and the efforts in detecting infections among both the vaccinated and unvaccinated individuals. Results: In the presence of vaccines, the case fatality rate depends not only on the effectiveness of vaccines in preventing deaths, but also on the detection of breakthrough infections. As a result, a decline in the case fatality rate may not imply that vaccines are being effective in reducing deaths. Likewise, a constant case fatality rate can still mean that vaccines are effective in reducing deaths. Conclusions: Unless vaccinated people are also tested, the case fatality rate loses its meaning in tracking the pandemic. This shows that unless efforts are directed at detecting breakthrough infections, it is hard to disentangle the effect of vaccines in reducing deaths from the probability of detecting infections on the case fatality rate

A demographic perspective on human wellbeing: Concepts, measurement and population heterogeneity

This introduction to the 2021 special issue of the Vienna Yearbook of PopulationResearch explores demographic perspectives on human wellbeing across time andspace. While the idea of relating demographic parameters to wellbeing has beenaround for a while, a more concrete research agenda on this topic has only recentlygained momentum. Reviewing the research presented in this volume, we show howexisting theoretical concepts and methodological tools in demography can be usedto make substantial advances in the study of wellbeing. We also touch upon themany challenges researchers face in defining and measuring wellbeing, with themost important debate being about whether the focus should be on objective orsubjective measures. The studies discussed here define wellbeing as health andmortality; as income, education or other resources; as happiness or life satisfaction;or as a combination thereof. They cover wellbeing in historical and contemporarypopulations in high- and low-income countries, and also point out important barriersto research on wellbeing, including the lack of good quality data in many regions.Finally, we highlight the value of considering population heterogeneities when studying wellbeing in order to identify population subgroups who are likely to fallbehind, which can have important policy implications

An indirect method to monitor the fraction of people ever infected with COVID-19: An application to the United States

The number of COVID-19 infections is key for accurately monitoring the pandemics. However, due to differential testing policies, asymptomatic individuals and limited large-scale testing availability, it is challenging to detect all cases. Seroprevalence studies aim to address this gap by retrospectively assessing the number of infections, but they can be expensive and time-intensive, limiting their use to specific population subgroups. In this paper, we propose a complementary approach that combines estimated (1) infection fatality rates (IFR) using a Bayesian melding SEIR model with (2) reported case-fatality rates (CFR) in order to indirectly estimate the fraction of people ever infected (from the total population) and detected (from the ever infected). We apply the technique to the U.S. due to their remarkable regional diversity and because they count with almost a quarter of all global confirmed cases and deaths. We obtain that the IFR varies from 1.25% (0.39–2.16%, 90% CI) in Florida, the most aged population, to 0.69% in Utah (0.21–1.30%, 90% CI), the youngest population. By September 8, 2020, we estimate that at least five states have already a fraction of people ever infected between 10% and 20% (New Jersey, New York, Massachussets, Connecticut, and District of Columbia). The state with the highest estimated fraction of people ever infected is New Jersey with 17.3% (10.0, 55.8, 90% CI). Moreover, our results indicate that with a probability of 90 percent the fraction of detected people among the ever infected since the beginning of the epidemic has been less than 50% in 15 out of the 20 states analyzed in this paper. Our approach can be a valuable tool that complements seroprevalence studies and indicates how efficient have testing policies been since the beginning of the outbreak

Socioeconomic environment and survival in patients after ST-segment elevation myocardial infarction (STEMI): a longitudinal study for the City of Vienna

Objectives: This study investigates the relationship between socioeconomic environment (SEE) and survival after ST-segment elevation myocardial infarction (STEMI) separately for women and men in the City of Vienna, Austria. Design: Hospital-based observational data of STEMI patients are linked with district-level information on SEE and the mortality register, enabling survival analyses with a 19-year follow-up (2000-2018). Setting: The analysis is set at the main tertiary care hospital of the City of Vienna. On weekends, it is the only hospital in charge of treating STEMIs and thus provides representative data for the Viennese population. Participants: The study comprises a total of 1481 patients with STEMI, including women and men aged 24-94 years. Primary and secondary outcome measures: Primary outcome measures are age at STEMI and age at death. We further distinguish between deaths from coronary artery disease (CAD), deaths from acute coronary syndrome (ACS), and other causes of death. SEE is proxied via mean individual gross income from employment in each municipal district. Results: Results are based on Kaplan-Meier survival probability estimates, Cox proportional hazard regressions and competing risk models, always using age as the time scale. Descriptive findings suggest a socioeconomic gradient in the age at death after STEMI. This finding is, however, not supported by the regression results. Female patients with STEMI have better survival outcomes, but only for deaths related to CAD (HR: 0.668, 95% CIs 0.452 to 0.985) and other causes of deaths (HR: 0.627, 95% CIs 0.444 to 0.884), and not for deaths from the more acute ACS. Conclusions: Additional research is necessary to further disentangle the interaction between SEE and age at STEMI, as our findings suggest that individuals from poorer districts have STEMI at younger ages, which indicates vulnerability in regard to health conditions in these neighbourhoods

Poor health, low mortality? Paradox found among immigrants in England and Wales

The 'healthy immigrant effect' and 'migrant mortality advantage' describe the better health and lower mortality of international immigrants as compared with the native‐born populations of high‐income countries. However, a growing body of evidence suggests that it is much more common to observe low mortality among immigrants than it is good health, pointing to the existence of a potential paradox that mirrors the well‐known gender paradox in health and mortality. To investigate this, we used the Office for National Statistics Longitudinal Study, a large‐scale representative 1% sample of the England and Wales resident population comprising linked individual‐level health, mortality, and socio‐demographic data. We compared health and mortality within and across major immigrant groups over 20 years using logistic regression for health and discrete‐time survival analysis for mortality, both before and after adjusting for socio‐demographic factors. Of the eight origin subgroups studied, we found persistent evidence of a health‐mortality paradox within three: men and women from India, Pakistan and Bangladesh, and the Caribbean. We discuss potential explanations and implications of this paradox and suggest that decision makers need to react to help these subgroups preserve their health in order to delay the onset of limiting illnesses and emergence of this paradox