The impact of the COVID-19 pandemic on the provision of instrumental help by older people across Europe.

The outbreak of the COVID-19 pandemic in early 2020 introduced new challenges to social cohesion across Europe. Epidemiological control measures instituted in almost all European countries have impacted the possibility to provide help to others. In addition, individual characteristics contributed to whether individuals were able and willing to provide help to or receive help from others. Against this background, we focus on how private support networks of individuals aged 50 years and older across Europe were directly or indirectly affected by the COVID-19 pandemic. The focus of the paper is on the supply side. While the older population has been mainly perceived as recipients of instrumental help in the COVID-19 pandemic, the paper examines the patterns of providing instrumental help to others by the older generations and their changes during the pandemic. Has the provision of instrumental help increased or decreased in the course of the COVID-19 crisis? Have the groups of recipients changed during the pandemic? What were key determinants for helping others in 2021 as compared to the first phase of the pandemic 1 year before? And how did this differ across countries with different degrees of affectedness by COVID-19? To answer these questions, we analyzed representative data from the Survey of Health, Aging and Retirement in Europe (SHARE) and, in particular, the two waves of the SHARE Corona Survey, fielded in 27 European countries and Israel in 2020 and 2021. Results based on data from more than 45,000 respondents aged 50+ showed that help from children to parents has strongly increased in the first phase of the pandemic, while the opposite (parents helping their children) has decreased-especially in countries that have been hit hardest by the pandemic in 2020. This changed with the continuing crisis. Instrumental help provided to non-kin that was common in Western Europe in the first phase of the pandemic, yielding an optimistic view of increasing solidarity after the outbreak of COVID-19, strongly decreased 1 year later. Our findings provide a contribution to comparative research on micro- and macro-determinants that are crucial for the understanding of intergenerational support in times of crisis.

Intensive care unit occupancy predictions in the COVID-19 pandemic based on age-structured modelling and differential flatness.

The COVID-19 pandemic confronts governments and their health systems with great challenges for disease management. In many countries, hospitalization and in particular ICU occupancy is the primary measure for policy makers to decide on possible non-pharmaceutical interventions. In this paper a combined methodology for the prediction of COVID-19 case numbers, case-specific hospitalization and ICU admission rates as well as hospital and ICU occupancies is proposed. To this end, we employ differential flatness to provide estimates of the states of an epidemiological compartmental model and estimates of the unknown exogenous inputs driving its nonlinear dynamics. A main advantage of this method is that it requires the reported infection cases as the only data source. As vaccination rates and case-specific ICU rates are both strongly age-dependent, specifically an age-structured compartmental model is proposed to estimate and predict the spread of the epidemic across different age groups. By utilizing these predictions, case-specific hospitalization and case-specific ICU rates are subsequently estimated using deconvolution techniques. In an analysis of various countries we demonstrate how the methodology is able to produce real-time state estimates and hospital/ICU occupancy predictions for several weeks thus providing a sound basis for policy makers.

Visible blue light inhibits infection and replication of SARS-CoV-2 at doses that are well-tolerated by human respiratory tissue.

The delivery of safe, visible wavelengths of light can be an effective, pathogen-agnostic, countermeasure that would expand the current portfolio of SARS-CoV-2 intervention strategies beyond the conventional approaches of vaccine, antibody, and antiviral therapeutics. Employing custom biological light units, that incorporate optically engineered light-emitting diode (LED) arrays, we harnessed monochromatic wavelengths of light for uniform delivery across biological surfaces. We demonstrated that primary 3D human tracheal/bronchial-derived epithelial tissues tolerated high doses of a narrow spectral band of visible light centered at a peak wavelength of 425 nm. We extended these studies to Vero E6 cells to understand how light may influence the viability of a mammalian cell line conventionally used for assaying SARS-CoV-2. The exposure of single-cell monolayers of Vero E6 cells to similar doses of 425 nm blue light resulted in viabilities that were dependent on dose and cell density. Doses of 425 nm blue light that are well-tolerated by Vero E6 cells also inhibited infection and replication of cell-associated SARS-CoV-2 by > 99% 24 h post-infection after a single five-minute light exposure. Moreover, the 425 nm blue light inactivated cell-free betacoronaviruses including SARS-CoV-1, MERS-CoV, and SARS-CoV-2 up to 99.99% in a dose-dependent manner. Importantly, clinically applicable doses of 425 nm blue light dramatically inhibited SARS-CoV-2 infection and replication in primary human 3D tracheal/bronchial tissue. Safe doses of visible light should be considered part of the strategic portfolio for the development of SARS-CoV-2 therapeutic countermeasures to mitigate coronavirus disease 2019 (COVID-19).

Estimation of exogenous drivers to predict COVID-19 pandemic using a method from nonlinear control theory.

The currently ongoing COVID-19 pandemic confronts governments and their health systems with great challenges for disease management. Epidemiological models play a crucial role, thereby assisting policymakers to predict the future course of infections and hospitalizations. One difficulty with current models is the existence of exogenous and unmeasurable variables and their significant effect on the infection dynamics. In this paper, we show how a method from nonlinear control theory can complement common compartmental epidemiological models. As a result, one can estimate and predict these exogenous variables requiring the reported infection cases as the only data source. The method allows to investigate how the estimates of exogenous variables are influenced by non-pharmaceutical interventions and how imminent epidemic waves could already be predicted at an early stage. In this way, the concept can serve as an "epidemometer" and guide the optimal timing of interventions. Analyses of the COVID-19 epidemic in various countries demonstrate the feasibility and potential of the proposed approach. The generic character of the method allows for straightforward extension to different epidemiological models.

The Impact of COVID-19 on Informal Caregiving and Care Receiving Across Europe During the First Phase of the Pandemic.

Purpose: We analyzed the effects of COVID-19 as well as its accompanying epidemiological control measures on health-related outcomes (physical and mental health) and unmet care needs of both caregivers and care recipients across Europe and Israel by taking into account country differences. Methods: We applied comparisons of adjusted predictions, controlling for a large set of relevant respondent characteristics, to investigate changes in the physical and mental health of caregivers and care recipients due to COVID-19. Furthermore, multilevel regression models were used to analyze the effect of individual and contextual indicators on the probability of reporting difficulties in receiving care. For the analyses, we used data from 26 countries with 51,983 respondents over 50 years based on the eighth wave of the Survey of Health, Aging and Retirement in Europe (SHARE), which had to be suspended in March 2020, and the SHARE Corona Survey fielded from June to August 2020. Results: During the first phase of the pandemic in spring/summer 2020, the frequency of providing personal care to parents increased in almost all European countries, while care to children, in turn, decreased. Parental caregivers who increased the frequency of providing personal care reported significantly more mental health strains, that is, feeling sad/depressed and anxious/nervous more often since the outbreak of the pandemic. With respect to receiving care, about one out of five care recipients had difficulty in obtaining adequate care from outside the household during the pandemic. The perception of unmet care needs was significantly associated with country differences regarding the duration of the stay-at-home orders. In contrast, the number of confirmed deaths did not have a significant effect on perceiving difficulties related to receiving care. Conclusions: Our findings show the extent of the burden to which caregivers and care recipients were exposed with respect to the unintended consequences of COVID-19-related epidemiological control measures. There is a great need within this population for interventions, which effectively reduce the burden as well as the symptoms of anxiety or depression for caregivers as well as care recipients. This should be recognized by (health) policymakers and social organizations.