Psychosocial impact of the Covid-19 pandemic: Identification of most vulnerable populations.

With the aim of analyzing the psychosocial impact of Covid-19 pandemic on society in general and health care workers in particular, we developed a 74-question survey questionnaire which was shared through social media. After analyzing 56,656 responses obtained during the first pandemic peak, the results showed an early and important negative impact on family finances, fear of working with Covid-19 patients and ethical issues related to Covid-19 care among healthcare workers (HCW). We have identified 7 target groups at higher risk of impaired mental health and susceptible to benefiting from an intervention: women, under 42 years of age, people with care burden, socio-economically deprived groups, people with unskilled or unqualified jobs, Covid-19 patients, and HCW working with Covid-19 patients. These results should encourage the active implementation of specific strategies to increase resilience in these groups and to prepare an adequate organizational response. Summary boxO_ST_ABSWhat is already known?C_ST_ABSO_LIStudies in small cohorts have reported an important impact of the Covid-19 pandemic on the general population at several levels C_LIO_LIAccording to previous studies in small cohorts, approximately 20% of the population suffered from impaired mental health status due to the pandemic C_LI What are the new findings?O_LIWe have studied 56,656 survey questionnaires to assess the impact of the Covid-19 outbreak on health status, family finances, habits, general health and mental health status, and ethics, especially in health care workers C_LIO_LIWe have identified 7 target groups susceptible to benefitting from an intervention, and which should be taken into account when designing new contention measures against the pandemic C_LI What do the new findings imply?O_LIThe design and active implementation of interventions to build individual resilience, especially for the targeted populations described, and preparation of an appropriate organizational response are key C_LIO_LIThe results obtained in this project could help local and national Governments to design or adjust coping measures against future outbreaks C_LI

The trade-off between formal and informal care in Spain.

Understanding the factors that determine the type and amount of formal care is important for predicting use in the future and developing long-term policy. In this context, we jointly analyze the provision of care at both the extensive (choice of care) and the intensive margin (number of hours of care received). In particular, we estimate and test, for the first time in this area of research, a sample selection model with the particularities that the first step is a multinomial logit model and the hours of care is an interval variable. Our results support the complementary and task-specific models which evidence has been found in other countries. Furthermore, we obtain evidence of substitution between formal and informal care for the male, young, married and unmarried subsamples. Regarding the hours of care, we find significant biases in predicted hours of care when sample selection is not taken into account. For the whole sample, the average bias is 2.77% for total hours and 3.23% for formal care hours. However, biases can be much larger (up to 10-15%), depending on the subsample and the type of care considered.

A sequential model of older workers' labor force transitions after a health shock.

In this paper we estimate and validate a three-period sequential model of older workers' labor force transitions following a health/disability shock, using retrospective information from Spanish cross-section data. Central to the analysis are the effects of the various disabilities and their severity. We find that the probability of remaining employed decreases both with age and the severity of the shock. Moreover, we find strong interactions between age and severity for older workers and none for prime-age workers. Suffering any kind of disability reduces the probability of being employed immediately prior to retirement age, and in such cases it is severity which is the strongest indicator. With respect to demographics, we find that female gender, having a retired spouse or being married all reduce the probabilities of both remaining in employment and returning to work following a spell of inactivity; in turn, principal breadwinner status, education and skill levels increase this likelihood.