Demographic risk factors, healthcare utilization, and mortality during the first year of the Covid-19 pandemic in Austria, Germany, and Italy.

At the population level, there is limited empirical evidence on the characteristics of individuals who were hospitalized because of Covid-19, the role of hospitalization in mortality risk, and how both evolved over time. Through the analysis of surveillance data for 7 million people in Austria, Germany, and Italy, we investigate: (1) the demographic characteristics and outcomes of individuals hospitalized because of Covid-19; and (2) the role of demographic risk factors and healthcare utilization (as measured by hospitalization) for the individual probability of dying because of Covid-19, in both cases comparing the period February to June 2020 with July 2020 to February 2021. We find that the demographic profile of individuals who were hospitalized or died because of Covid-19 is the same in both periods, except for a younger age profile for hospitalizations in the second period. Mortality differentials across countries result from the interaction of demographic risk factors and hospitalization at the individual level.

Demographics of COVID-19 hospitalisations and related fatality risk patterns.

The assessment of hospitalisations and intensive care is crucial for planning health care resources needed over the course of the coronavirus disease 2019 (COVID-19) pandemic. Nonetheless, comparative empirical assessments of COVID-19 hospitalisations and related fatality risk patterns on a large scale are lacking. This paper exploits anonymised, individual-level data on SARS-CoV-2 confirmed infections collected and harmonized by the European Centre for Disease Prevention and Control to profile the demographics of COVID-19 hospitalised patients across nine European countries during the first pandemic wave (February - June 2020). We estimate the role of demographic factors for the risk of in-hospital mortality, and present a case study exploring individuals' comorbidities based on a subset of COVID-19 hospitalised patients available from the Dutch health system. We find that hospitalisation rates are highest among individuals with confirmed SARS-CoV-2 infection who are not only older than 70 years, but also 50-69 years. The latter group has a longer median time between COVID-19 symptoms' onset and hospitalisation than those aged 70+ years. Men have higher hospitalisation rates than women at all ages, and particularly above age 50. Consistently, men aged 50-59 years have a probability of hospitalisation almost double than women do. Although the gender imbalance in hospitalisation remains above age 70, the gap between men and women narrows at older ages. Comorbidities play a key role in explaining selection effects of COVID-19 confirmed positive cases requiring hospitalisation. Our study contributes to the evaluation of the COVID-19 burden on the demand of health-care during emergency phases. Assessing intensity and timing dimensions of hospital admissions, our findings allow for a better understanding of COVID-19 severe outcomes. Results point to the need of suitable calibrations of epidemiological projections and (re)planning of health services, enhancing preparedness to deal with infectious disease outbreaks.

Comparing COVID-19 fatality across countries: a synthetic demographic indicator.

Background: The case fatality rate (CFR) is one of the most important measures for monitoring disease progression and evaluating appropriate policy health measures over the course of the COVID-19 pandemic. To remove biases arising from the age structure of COVID-19 cases in international comparisons of the CFR, existing studies have relied mainly on direct standardisation. Objective: We propose and validate a synthetic indicator of COVID-19 fatality (SCFR) that improves its comparability across countries by adjusting for the age and sex structure of COVID-19 cases without relying on the arbitrary choice of a standard population. Results: Contrary to what comparisons of the crude CFR suggest, differences in COVID-19 fatality across countries according to the proposed SCFR are not very stark. Importantly, once we adjust for the age structure of COVID-19 cases, the higher case fatality among men emerges as the main driver of international differences in COVID-19 CFR. Conclusions: The SCFR is a simple indicator that is useful for monitoring the fatality of SARS-CoV-2 mutations and the efficacy of health policy measures for COVID-19, including vaccination. Contributions: (1) A simple synthetic indicator of COVID-19 fatality that improves its comparability across countries by adjusting for the age and sex structure of COVID-19 cases; (2) Evidence that sex differences in COVID-19 fatality drive international differences in the overall CFR.

HIV/AIDS and time allocation in rural Malawi.

AIDS-related morbidity and mortality are expected to have a large economic impact in rural Malawi, because they reduce the time that adults can spend on production for subsistence and on income-generating activities. However, households may compensate for production losses by reallocating tasks among household members. The data demands for measuring these effects are high, limiting the amount of empirical evidence. In this paper, we utilize a unique combination of qualitative and quantitative data, including biomarkers for HIV, collected by the 2004 Malawi Diffusion and Ideational Change Project, to analyze the association between AIDS-related morbidity and mortality, and time allocation decisions in rural Malawian households. We find that AIDS-related morbidity and mortality have important economic effects on women's time, whereas men's time is unresponsive to the same shocks. Most notably, AIDS is shown to induce diversification of income sources, with women (but not men) reallocating their time, generally from work-intensive (typically farming and heavy chores) to cash-generating tasks (such as casual labor).

HIV risk among currently married couples in rural Malawi: what do spouses know about each other?

In countries with generalized HIV/AIDS epidemics, married couples have a shared risk of acquiring HIV/AIDS. Yet very little research has adopted a couple-level perspective to investigate perceived risk of HIV infection. In this paper, we used population-based data from 768 married monogamous couples in the 2004 Malawi Diffusion and Ideational Change Project (MDICP) to compare respondents' perceptions about their spouses' HIV status to their spouses' actual HIV status. Using chi-squared and Kappa coefficient statistics, we evaluated how accurately respondents assess their spouse's HIV status, and compared the assessment of their spouse's HIV status with their assessment of their own serostatus. We found that individuals tend to overestimate their spouse's as well as their own risk of having HIV. Husbands were generally more accurate in assessing their own risk of HIV infection than that of their wives, but wives were more accurate in assessing the HIV status of their spouses. In our multivariate logistic regression results, we found that marital infidelity is the most important correlate of overestimating individual and spousal HIV risk.