COVID-19 and mental health in China: the effects of personality.

BACKGROUND: China was the first country affected by the COVID-19 virus, and it is a very important case to study the effects of the virus and the consequent restrictions. However, national representative studies of how the COVID-19 pandemic affects mental health in China are still limited. METHODS: Using two waves of the China Family Panel Studies, we follow the same individuals before and during the pandemic. We compare weighted means using 95% CIs to explore mental health deterioration, and we and perform several linear regressions with the Ordinaly Least Square (OLS) estimator to identify individuals most affected by the COVID-19 pandemic. RESULTS: The prevalence of severe cases of depression, measured using an eight-item version of the common Centre for Epidemiologic Studies Depression Scale (CES-D), increased from 6.68% in 2018 to 7.86% in 2020; quantifiable as around a 18% increase. This deterioration is higher for individuals subject to strict lockdowns, about 0.4 symptoms more on average, and it is stronger among those who already reported symptoms of depression in the 2018 wave of data. Individuals with more open personalities tend to experience more severe deterioration: a 1 SD change in the openness trait corresponds to 0.05 more symptoms. On the other hand, more neurotic individuals seem less negatively affected. CONCLUSION: We find clear evidence of a moderate level of mental health deterioration between 2018 and 2020. These effects are larger for individuals subject to stricter lockdowns and for individuals with more open personalities.

Will the last be the first? School closures and educational outcomes.

Governments have implemented school closures and online learning as one of the main tools to reduce the spread of Covid-19. Despite the potential benefits in terms of containment of virus diffusion, the educational costs of these policies may be dramatic. This work identifies these costs, expressed as decrease in test scores, for the whole universe of Italian students attending the 5th, 8th and 13th grade of the school cycle during the 2021/22 school year. The analysis is based on a difference-in-difference model in relative time, where the control group is the closest generation before the Covid-19 pandemic. Results suggest a national average loss between 1.8-4.0% in Mathematics and Italian test scores. After collecting the precise number of school closure days for the universe of students in Sicily, this work also estimates that the average days of closure decrease the test score by 2.4%. In this context, parents appear to have a partial compensatory effect, but only when holding higher levels of education and when their children are attending low and middle schools. This is likely explained by the lower relevance of parental inputs and higher reliance on other inputs, such as peers, for the higher grades. Finally, the effects are also heterogeneous across class size, parents' country of birth and job conditions, pointing towards potential growing inequalities driven by the lack of frontal teaching.

School-age vaccination, school openings and Covid-19 diffusion.

This article investigates the relationship between school openings and Covid-19 diffusion when school-age vaccination becomes available. The analysis relies on a unique geo-referenced high frequency database on age of vaccination, Covid-19 cases and hospitalization indicators from the Italian region of Sicily. The study focuses on the change of Covid-19 diffusion after school opening in a homogeneous geographical territory (i.e., with the same control measures and surveillance systems, centrally coordinated by the Regional Government). The identification of causal effects derives from a comparison of the change in cases before and after school opening in the school year 2020/21, when vaccination was not available, and in 2021/22, when the vaccination campaign targeted individuals of age 12-19 and above 19. Results indicate that, while school opening determined an increase in the growth rate of Covid-19 cases in 2020/2021, this effect has been substantially reduced by school-age vaccination in 2021/2022. In particular, we find that an increase of approximately 10% in the vaccination rate of school-age population reduces the growth rate of Covid-19 cases after school opening by approximately 1%.

Schools opening and Covid-19 diffusion: Evidence from geolocalized microdata.

Are schools triggering the diffusion of the Covid-19? This question is at the core of an extensive debate about the social and long-run costs of stopping the economic activity and human capital accumulation from reducing the contagion. In principle, many confounding factors, such as climate, health system treatment, and other forms of restrictions, may impede disentangling the link between schooling and Covid-19 cases when focusing on a country or regional-level data. This work sheds light on the potential impact of school opening on the upsurge of contagion by combining a weekly panel of geocoded Covid-19 cases in Sicilian census areas with a unique set of school data. The identification of the effect takes advantage of both a spatial and time-variation in school opening, stemming from the flexibility in opening dates determined by a Regional Decree, and by the occurrence of a national referendum, which pulled a set of poll-station schools towards opening earlier or later September 24th. The analysis finds that census areas where schools opened earlier observed a significant and positive increase in the growth rate of Covid-19 cases between 2.5-3.7%. This result is consistent across several specifications, including accounting for several determinants of school opening, such as the number of temporary teachers, Covid-19 cases in August, and pupils with special needs. Finally, the analysis finds lower effects in more densely populated areas, on younger population, and on smaller class size. The results imply that school reopening generated an increase of one third in cases.

Anxiety and depression among medical doctors in Catalonia, Italy, and the UK during the COVID-19 pandemic.

Healthcare workers have had the longest and most direct exposure to COVID-19 and consequently may suffer from poor mental health. We conducted one of the first repeated multi-country analysis of the mental wellbeing of medical doctors (n = 5,275) at two timepoints during the COVID-19 pandemic (June 2020 and November/December 2020) to understand the prevalence of anxiety and depression, as well as associated risk factors. Rates of anxiety and depression were highest in Italy (24.6% and 20.1%, June 2020), second highest in Catalonia (15.9% and 17.4%, June 2020), and lowest in the UK (11.7% and 13.7%, June 2020). Across all countries, higher risk of anxiety and depression symptoms were found among women, individuals below 60 years old, those feeling vulnerable/exposed at work, and those reporting normal/below-normal health. We did not find systematic differences in mental health measures between the two rounds of data collection, hence we cannot discard that the mental health repercussions of the pandemic are persistent.

Socio-Demographic Factors Involved in a Low-Incidence Phase of SARS-CoV-2 Spread in Sicily, Italy.

BACKGROUND: The present study analysed SARS-CoV-2 cases observed in Sicily and investigated social determinants that could have an impact on the virus spread. METHODS: SARS-CoV-2 cases observed among Sicilian residents between the 1 February 2020 and 15 October 2020 have been included in the analyses. Age, sex, date of infection detection, residency, clinical outcomes, and exposure route have been evaluated. Each case has been linked to the census section of residency and its socio-demographic data. RESULTS: A total of 10,114 patients (202.3 cases per 100,000 residents; 95% CI = 198.4-206.2) were analysed: 45.4% were asymptomatic and 3.62% were deceased during follow-up. Asymptomatic or mild cases were more frequent among young groups. A multivariable analysis found a reduced risk of SARS-CoV-2 cases was found in census sections with higher male prevalence (adj-OR = 0.99, 95% CI = 0.99-0.99; p < 0.001) and presence of immigrants (adj-OR = 0.89, 95% CI 0.86-0.92; p < 0.001). Proportion of residents aged <15 years, residents with a university degree, residents with secondary education, extra-urban mobility, presence of home for rent, and presence of more than five homes per building were found to increase the risk of SARS-CoV-2 incidence. CONCLUSION: Routinely collected socio-demographic data can be predictors of SARS-CoV-2 risk infection and they may have a role in mapping high risk micro-areas for virus transmission.