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Eur Econ Rev ; : 104003, 2022 Jan 19.
Article in English | MEDLINE | ID: covidwho-1629787


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.

PLoS One ; 16(11): e0259213, 2021.
Article in English | MEDLINE | ID: covidwho-1496532


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.

Anxiety/etiology , COVID-19/psychology , Depression/etiology , Occupational Diseases/psychology , Physicians/psychology , Adult , Female , Health Personnel/psychology , Humans , Italy , Male , Middle Aged , Pandemics
Healthcare (Basel) ; 9(7)2021 Jul 09.
Article in English | MEDLINE | ID: covidwho-1308331


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.