School openings and the COVID-19 outbreak in Italy. A provincial-level analysis using the synthetic control method

Unlocking the importance of perceived governance: The impact on COVID-19 in NUTS-2 European regions

In the immediate aftermath of the pandemic, governments implemented non-pharmaceutical interventions (NPIs). Previous literature suggests that NPI effectiveness is influenced by governance quality. The acceptance and perceived necessity of these measures by the public are crucial to their success, as NPIs cannot be easily enforced without public support. Does regional governance also play a role? This study examines the correlation between the quality of governance in European NUTS-2 regions and the spread of COVID-19. The findings indicate that overall perceived governance, and its perceived quality and corruption pillars, significantly impact the effectiveness of these interventions. This effect was pronounced during the first wave and then diminished in importance, disappearing before vaccines were available, suggesting that regional governance matters especially in the immediate aftermath of an exogenous shock.

Assessing the effectiveness of international government responses to the COVID-19 pandemic

This paper examines the effectiveness of non-pharmaceutical measures adopted by governments to control the evolution of the COVID-19 pandemic. Using a Panel VAR model for the OECD countries, we test for Granger causality between the 7-day cumulative incidence, mortality rate, and government response indexes. Granger-type statistics reveal evidence that the evolution of the COVID-19 pandemic influenced the measures taken by governments. However, limited or nonexistent evidence supports the reverse situation. This suggests that government measures were not highly effective in controlling the pandemic. While not implying total ineffectiveness, our results indicate a considerable lack of efficacy, emphasizing a lesson for governments to learn from and correct in preparation for similar events in the future.

Schools and the transmission of Sars-Cov-2: Evidence from Italy

This paper studies the effect on the spread of Sars-Cov-2 in Italy of schools' re-openings and closures. Exploiting different re-opening dates across regions after the summer break of 2020, I show that early-opening regions experienced more cases in the 40 days following school re-openings compared with late-opening ones. However, there is great uncertainty around the estimates, and this suggests a wide dispersion in the effects of school re-openings on Sars-Cov-2 transmission. I also study the effect of school closures in Campania, one of the biggest regions in Southern Italy. Using a synthetic control approach, I show that school closures are associated with lower numbers of cases relative to the counterfactual group, particularly in younger age groups. In contrast, I find no significant effects on older age groups, which are more likely to require hospitalization. Finally, by exploiting survey data, I provide descriptive evidence on the increased incidence rate among teachers and students relative to the general population, following school re-openings.

Comparative impact assessment of COVID-19 policy interventions in five South Asian countries using reported and estimated unreported death counts during 2020-2021

There has been raging discussion and debate around the quality of COVID death data in South Asia. According to WHO, of the 5.5 million reported COVID-19 deaths from 2020-2021, 0.57 million (10%) were contributed by five low and middle income countries (LMIC) countries in the Global South: India, Pakistan, Bangladesh, Sri Lanka and Nepal. However, a number of excess death estimates show that the actual death toll from COVID-19 is significantly higher than the reported number of deaths. For example, the IHME and WHO both project around 14.9 million total deaths, of which 4.5-5.5 million were attributed to these five countries in 2020-2021. We focus our gaze on the COVID-19 performance of these five countries where 23.5% of the world population lives in 2020 and 2021, via a counterfactual lens and ask, to what extent the mortality of one LMIC would have been affected if it adopted the pandemic policies of another, similar country? We use a Bayesian semi-mechanistic model developed by Mishra et al. (2021) to compare both the reported and estimated total death tolls by permuting the time-varying reproduction number (Rt) across these countries over a similar time period. Our analysis shows that, in the first half of 2021, mortality in India in terms of reported deaths could have been reduced to 96 and 102 deaths per million compared to actual 170 reported deaths per million had it adopted the policies of Nepal and Pakistan respectively. In terms of total deaths, India could have averted 481 and 466 deaths per million had it adopted the policies of Bangladesh and Pakistan. On the other hand, India had a lower number of reported COVID-19 deaths per million (48 deaths per million) and a lower estimated total deaths per million (80 deaths per million) in the second half of 2021, and LMICs other than Pakistan would have lower reported mortality had they followed India's strategy. The gap between the reported and estimated total deaths highlights the varying level and extent of under-reporting of deaths across the subcontinent, and that model estimates are contingent on accuracy of the death data. Our analysis shows the importance of timely public health intervention and vaccines for lowering mortality and the need for better coverage infrastructure for the death registration system in LMICs.

The importance of investing in data, models, experiments, team science, and public trust to help policymakers prepare for the next pandemic

The COVID-19 pandemic has brought about valuable insights regarding models, data, and experiments. In this narrative review, we summarised the existing literature on these three themes, exploring the challenges of providing forecasts, the requirement for real-time linkage of health-related datasets, and the role of 'experimentation' in evaluating interventions. This literature review encourages us to broaden our perspective for the future, acknowledging the significance of investing in models, data, and experimentation, but also to invest in areas that are conceptually more abstract: the value of 'team science', the need for public trust in science, and in establishing processes for using science in policy. Policy-makers rely on model forecasts early in a pandemic when there is little data, and it is vital to communicate the assumptions, limitations, and uncertainties (theme 1). Linked routine data can provide critical information, for example, in establishing risk factors for adverse outcomes but are often not available quickly enough to make a real-time impact. The interoperability of data resources internationally is required to facilitate sharing across jurisdictions (theme 2). Randomised controlled trials (RCTs) provided timely evidence on the efficacy and safety of vaccinations and pharmaceuticals but were largely conducted in higher income countries, restricting generalisability to low- and middle-income countries (LMIC). Trials for non-pharmaceutical interventions (NPIs) were almost non-existent which was a missed opportunity (theme 3). Building on these themes from the narrative review, we underscore the importance of three other areas that need investment for effective evidence-driven policy-making. The COVID-19 response relied on strong multidisciplinary research infrastructures, but funders and academic institutions need to do more to incentivise team science (4). To enhance public trust in the use of scientific evidence for policy, researchers and policy-makers must work together to clearly communicate uncertainties in current evidence and any need to change policy as evidence evolves (5). Timely policy decisions require an established two-way process between scientists and policy makers to make the best use of evidence (6). For effective preparedness against future pandemics, it is essential to establish models, data, and experiments as fundamental pillars, complemented by efforts in planning and investment towards team science, public trust, and evidence-based policy-making across international communities. The paper concludes with a 'call to actions' for both policy-makers and researchers.

On the determinants of anti-COVID restriction and anti-vaccine movements: the case of IoApro in Italy

Following restrictions to control the spread of COVID-19, and subsequent vaccination campaigns, sentiments against such policies were quick to arise. While individual-level determinants that led to such attitudes have drawn much attention, there are also reasons to believe that the macro context in which these movements arose may contribute to their evolution. In this study, exploiting data on business activities which supported a major Italian anti-restriction and anti-vaccine movement, IoApro, using quantitative analysis that employs both a fractional response probit and logit model and a beta regression model, we investigate the relationship between socio-economic characteristics, institutional quality, and the flourishing of this movement. Our results suggest a U-shaped relationship between income and the proliferation of the movement, meaning that support for these movements increases the greater the degree of economic decline. Our results further indicate that the share of the population between 40 and 60 years old is positively related to support for such movements, as is institutional corruption.

Performance of two educational approaches in increasing knowledge of high-school students about COVID-19 during the first wave of pandemic

OBJECTIVES

The coronavirus disease (COVID-19) pandemic has greatly altered peoples' daily lives. Teachers and students were found quite unprepared for the emergence of the first COVID-19 wave. So, improving the knowledge of students about COVID-19 is an important issue.

METHODS

In this study, 240 high students attended. Two interventions with the same contents, but in different ways, were delivered. A structured questionnaire was utilized to collect data on demographic information, and information about the behavioral intention toward COVID-19 before and after the educational interventions as well as a control group that received no educational intervention.

RESULTS

students in all arms had similar baseline knowledge of COVID-19. The results of the post-analysis showed the efficiency of educational techniques in increasing students' knowledge about COVID-19. So the audio-visual training method performed significantly better than the visual training method (p = 0.03). Both approaches achieved better scores than the control group (P < 0.001).

CONCLUSION

During the outbreak of COVID-19, multimedia-based learning is a more effective educational approach and can improve the learning outcomes related to COVID-19 and achieve learning goals without close contact than written materials.

Assessing the effectiveness of mandatory outdoor mask policy: The natural experiment of Campania

Face masks are possibly the main symbol of the COVID-19 pandemic. Once rarely used in Western countries, in the last two years they have become an object it is impossible to leave one's home without. Italy made their use a legal requirement, even outdoors, from late 2020 to early 2022. The effectiveness of this policy in reducing COVID-19 cases has been widely debated. The recent cancellation of their mandatory use in Italy offers an interesting setting in which to test its impact, since one Italian region (Campania) extended the restriction for a further three weeks. We aim to shed some light on the real-world impact of mandatory use of face masks outdoors, identifying the effect of this policy on the spread of COVID-19. By means of a quantitative analysis, employing a synthetic control method approach, we find that Campania had statistically the same number of cases as its synthetic counterfactual, built from a donor pool formed from the other Italian provinces. Hence, results suggest that while it imposes a burden on the public, the use of face masks outdoors is not correlated with a decrease in the number of COVID-19 cases.

The effect of self-esteem on the spread of a pandemic. A cross-country analysis of the role played by self-esteem in the spread of the COVID-19 pandemic

Extant research on COVID-19 suggests that many socio-economic determinants, by affecting personal behavior, have influenced the evolution of the pandemic. In this paper we study the role played in this regard by average levels of self-esteem in the public. There are reasons to believe that both low and very levels of self-esteem may have an effect on the spread of COVID-19, for opposite reasons. On the one hand, people with low self-esteem may not worry enough to behave in the way recommended (and prescribed, through non-pharmaceutical interventions) by the authorities; people with very high self-esteem, on the other hand, may be over-confident and fail to follow the prescriptions, believing that they do not need them. In this study we test this hypothesis by means of a quantitative cross-country analysis, using a hybrid model and the Rosenberg self-esteem scale. Our results suggest the existence of a U-shaped relationship between the trend of COVID-19 and average levels of self-esteem in a country.

Evaluation of a COVID-19 rapid antigen testing program among student athletes in a public high school district

PURPOSE

The purpose of this study is to evaluate a COVID-19 rapid antigen testing program among high school athletes through testing data and qualitative analysis from key stakeholders.

METHODS

Testing data was obtained by the partnering school district. Testing staff, coaches, and parents participated in a focus group using a semi-structured focus group guide. Transcripts were analyzed using a grounded theory approach to produce the themes of the study.

RESULTS

Rapid antigen tests quickly identified a COVID-19-positive student athlete, which allowed for quick isolation and zero transmission to teammates. Focus groups with parents, testing staff, and coaches indicated the testing program improved perceived safety and demonstrated the ability for school staff to implement a widespread COVID-19 screening program with minimal training.

CONCLUSIONS

As schools continue to respond to various waves of COVID-19 infections, targeted testing for high-risk activities in school settings such as sports programs may help prevent school outbreaks during times of high community transmission rates. This evaluation adds to a body of literature that will aid schools and policy makers in their decision on how to best keep student athletes and school communities safe for future waves of COVID-19 infection and other pandemics.

Mechanisms influencing the factors of urban built environments and coronavirus disease 2019 at macroscopic and microscopic scales: The role of cities

In late 2019, the coronavirus disease 2019 (COVID-19) pandemic soundlessly slinked in and swept the world, exerting a tremendous impact on lifestyles. This study investigated changes in the infection rates of COVID-19 and the urban built environment in 45 areas in Manhattan, New York, and the relationship between the factors of the urban built environment and COVID-19. COVID-19 was used as the outcome variable, which represents the situation under normal conditions vs. non-pharmacological intervention (NPI), to analyze the macroscopic (macro) and microscopic (micro) factors of the urban built environment. Computer vision was introduced to quantify the material space of urban places from street-level panoramic images of the urban streetscape. The study then extracted the microscopic factors of the urban built environment. The micro factors were composed of two parts. The first was the urban level, which was composed of urban buildings, Panoramic View Green View Index, roads, the sky, and buildings (walls). The second was the streets' green structure, which consisted of macrophanerophyte, bush, and grass. The macro factors comprised population density, traffic, and points of interest. This study analyzed correlations from multiple levels using linear regression models. It also effectively explored the relationship between the urban built environment and COVID-19 transmission and the mechanism of its influence from multiple perspectives.

Increasing ventilation reduces SARS-CoV-2 airborne transmission in schools: A retrospective cohort study in Italy's Marche region

Introduction

While increasing the ventilation rate is an important measure to remove inhalable virus-laden respiratory particles and lower the risk of infection, direct validation in schools with population-based studies is far from definitive.

Methods

We investigated the strength of association between ventilation and SARS-CoV-2 transmission reported among the students of Italy's Marche region in more than 10,000 classrooms, of which 316 were equipped with mechanical ventilation. We used ordinary and logistic regression models to explore the relative risk associated with the exposure of students in classrooms.

Results and discussion

For classrooms equipped with mechanical ventilation systems, the relative risk of infection of students decreased at least by 74% compared with a classroom with only natural ventilation, reaching values of at least 80% for ventilation rates >10 L s-1 student-1. From the regression analysis we obtained a relative risk reduction in the range 12%15% for each additional unit of ventilation rate per person. The results also allowed to validate a recently developed predictive theoretical approach able to estimate the SARS-CoV-2 risk of infection of susceptible individuals via the airborne transmission route. We need mechanical ventilation systems to protect students in classrooms from airborne transmission; the protection is greater if ventilation rates higher than the rate needed to ensure indoor air quality (>10 L s-1 student-1) are adopted. The excellent agreement between the results from the retrospective cohort study and the outcome of the predictive theoretical approach makes it possible to assess the risk of airborne transmission for any indoor environment.

Correlations between the urban built environmental factors and the spatial distribution at the community level in the reported COVID-19 samples: A case study of Wuhan

COVID-19 has dramatically changed the lifestyle of people, especially in urban environments. This paper investigated the variations of built environments that were measurably associated with the spread of COVID-19 in 150 Wuhan communities. The incidence rate in each community before and after the lockdown (January 23, 2020), as respective dependent variables, represented the situation under normal circumstances and non-pharmaceutical interventions (NPI). After controlling the population density, floor area ratio (FAR), property age and sociodemographic factors, the built environmental factors in two spatial dimensions, the 15-minute walking life circle and the 10-minute cycling life circle, were brought into the Hierarchical Linear Regression Model and the Ridge Regression Model. The results indicated that before lockdown, the number of markets and schools were positively associated with the incidence rate, while community population density and FAR were negatively associated with COVID-19 transmission. After lockdown, FAR, GDP, the number of hospitals (in the 15-minute walking life circle) and the bus stations (in the 10-minute cycling life circle) became negatively correlated with the incidence rate, while markets remained positive. This study effectively extends the discussions on the association between the urban built environment and the spread of COVID-19. Meanwhile, given the limitations of sociodemographic data sources, the conclusions of this study should be interpreted and applied with caution.

Carrot and stick: Economic support and stringency policies in response to COVID-19

To address the economic losses caused by the COVID-19 pandemic, countries have implemented, together with policies aimed at stopping the spread of the virus, a mixture of fiscal and monetary measures. This work investigates the effect of containment policies and economic support measures on economic growth in the short run, investigating a time window of six quarters in a cross country perspective. Our results confirm the existence of a negative effect of stringency measures on GDP; we also detect a positive effect from economic support measures. Moreover, looking at the interaction between these two kinds of interventions, our findings suggest that up to a relatively low level of stringency policies, economic support measures are able to positively counterbalance the negative impact of containment and closure policies. When the level of closures became more severe, however, the economic support measures that countries adopt are not able to completely recoup, in the short run, the economic losses due to stringency policies. Results suggest that in order to have a positive net effect, policymakers should take into account the level of stringency measures implemented before investing in economic support.

When and how do business shutdowns work? Evidence from Italy's first COVID-19 wave

Governments around the world have adopted unprecedented policies to deal with COVID-19. This paper zooms in on business shutdowns and investigates their effectiveness in reducing mortality. We leverage highly granular death registry data for almost 5000 Italian municipalities in a diff-in-diff approach that allows us to mitigate endogeneity concerns credibly. Our results, which are robust to controlling for a host of co-factors, offer strong evidence that business shutdowns effectively curb mortality. We calculate that they may have reduced the death toll from the first wave of COVID-19 in Italy by about 40%. Our findings also highlight that timeliness is key - by acting 1 week earlier, their effectiveness could have been increased by an additional 5%. Finally, shutdowns should be targeted. Closing service activities with a high degree of interpersonal contact saves the most lives. Shutting down production activities, while substantially reducing mobility, only has mild effects on mortality.

Back to school or … back to lockdown? The effects of opening schools on the diffusion of COVID-19 in Italian regions

The opening of schools that coincided with the beginning of fall 2020 and the arrival of the second wave of COVID-19 in continental Europe has fostered significant debate in several countries. Some contributions have suggested that youngsters play a minor role in the spread of the virus, given the specific characteristics of this infection; other scholars have raised concerns about the necessary movement that involves keeping schools open, and the consequent potential spread of the virus. In this study, we focus on the Italian case, an interesting setting in which to test the impact of opening schools on the spread of COVID-19, because of the different dates at which schools have opened in the various Italian provinces, and because of the different rates at which the virus has spread across Italy. Our results suggest that open schools have a positive impact on COVID-19 cases, whose spread occurs between 10 and 14 days after opening. While closing schools or using distance learning have other social and economic consequences, making it necessary for policymakers to adopt a holistic evaluation, it should be taken into account that open schools have an impact on the spread of the pandemic.

Vaccination nudges: A study of pre-booked COVID-19 vaccinations in Sweden

A nudge changes people's actions without removing their options or altering their incentives. During the COVID-19 vaccine rollout, the Swedish Region of Uppsala sent letters with pre-booked appointments to inhabitants aged 16–17 instead of opening up manual appointment booking. Using regional and municipal vaccination data, we document a higher vaccine uptake among 16- to 17-year-olds in Uppsala compared to untreated control regions (constructed using the synthetic control method as well as neighboring municipalities). The results highlight pre-booked appointments as a strategy for increasing vaccination rates in populations with low perceived risk.

Work ethics, stay-at-home measures and COVID-19 diffusion : How is the pandemic affected by the way people perceive work?

Non-pharmaceutical interventions aimed at reducing the spread of COVID-19 rely largely on voluntary compliance among the target population to be effective, since such measures, which are aimed at the entire population, are very hard to enforce. In this paper, we focus on the impact of different work ethics on the spread of COVID-19. There are indeed reasons to believe that populations with different attitudes toward work will react differently to stay-at-home orders and other policies that forbid people from working. By means of a quantitative analysis, using hybrid model estimators, we test the impact of different work ethics on COVID-19 diffusion in a sample of 30 European countries. Results show that the more a population holds certain beliefs about work-namely, that it is humiliating to receive money without working, that people who do not work become lazy, and that work always comes first-the higher contagion rates of COVID-19 are, ceteris paribus. On the other hand, the more a population perceives work as a social duty, the lower contagion rates are. All this suggests that different work ethics matter in the containment of COVID-19.

Impact of implementation timing on the effectiveness of stay-at-home requirement under the COVID-19 pandemic: Lessons from the Italian Case

When a new infectious outbreak emerges, governments must initially rely on non-pharmaceutical interventions (NPIs) to mitigate the impact of the pathogen. Although a strict stay-at-home requirement (i.e., lockdown) presents high effectiveness in reducing patients hospitalized in intensive care units (ICUs), it comes with unintended physical, psychological, and economic damages for the citizens. Using how Italy managed the COVID-19 outbreak from February to September 2020 on a national basis, this study aims at understanding the impact of implementation timing on the effectiveness of NPIs. Our findings may be helpful to avoid the implementation of stay-at-home requirements when it is not strictly necessary. A compartmental SEICRD model was developed to create the baseline scenario without NPIs. Generalized Poisson regressions were applied to study the change in effectiveness over-time of NPIs on Avoided ICUs for each one of the Italian regions. Our study suggests that although the stay-at-home requirement is the most effective measure in reducing ICU hospitalizations in regions encountering the outbreak early, its effectiveness decreases in regions encountering the outbreak later, where a set of other NPIs are more effective. We developed a reference of daily new cases when lockdown should be implemented or avoided, accordingly. Our findings could be useful to support policymakers in contrasting the pandemic and in limiting the societal and economic impact of stringent NPIs.

COVID-19 Diffusion Before Awareness: The Role of Football Match Attendance in Italy

Anecdotal evidence suggests that football matches may have played a role in the spread of COVID-19 all over Europe. Nevertheless, from a scientific point of view, the impact of football matches on the spread of COVID-19 remains unclear. In this paper we study, via a quantitative analysis, the case of Italy, a country badly affected by COVID, and one where attending football matches is very popular. We consider the impact of matches played in January and February 2020 on the dynamic of the pandemic in March and April the same year. Our results, which consider all levels of Italian professional football, and the highest level of amateur football, show that matches played in January and February had an impact on the evolution of the pandemic in March and April. These results suggest that great care must be taken before considering re-opening stadia.

Water pollution and administrative division adjustments: A quasi-natural experiment in Chaohu Lake, China

Administrative division adjustments, such as agglomerations, upgrading, and revocation, introduce a series of uncertain impacts on the social and economic development in administrative regions. Previous studies have focused more on the economic effects of administrative division adjustments, but in this paper, we also consider the environmental effects of such adjustments. In 2011, with the approval of the State Council, the prefecture-level Chaohu city was officially revoked, resulting in a county-level Chaohu city. One district and four counties under the jurisdiction of the original Chaohu city were placed under the jurisdiction of Hefei, Wuhu, and Ma'anshan. This adjustment made Chaohu Lake an inner lake of Hefei city. The administrative division adjustment of Chaohu Lake, China, is used as a quasi-natural experiment to explore the influence of such an adjustment on pollution control. The synthetic control method (SCM) is used in this study to evaluate the effect of the administrative division adjustment on the water quality indicators of Chaohu Lake. The following conclusions are drawn. First, after the administrative division adjustment, some water quality indicators, such as ammonia nitrogen, improved; however, other major pollution indicators, such as chemical oxygen demand (COD) and dissolved oxygen (DO), worsened to varying degrees. Second, the results reveal that improper development ideas, excessive industrial expansion, and the shift in economic growth and environmental goals were problems after the adjustment. Returning to the original intention of the administrative division adjustment, rationalizing the Chaohu Lake management system and designing a sound and feasible accountability mechanism are fundamental measures for reducing pollution.

The Effects of School Closures on COVID-19: A Cross-Country Panel Analysis

BACKGROUND

There has been much debate about the effects and importance of closing, keeping closed, or not opening schools in order to prevent COVID-19 contagion. This policy has been questioned regarding both its efficacy and the social cost it entails, including the possible asymmetric impact it has on genders in many societies due to traditional childcare roles. To the best of our knowledge no existing contribution has attempted to gauge the effectiveness of such a policy over time, in a longitudinal cross-country perspective.

OBJECTIVES

This paper aimed to fill the gap in the literature by assessing, at a European level, the effect of school closures (or the lack of such measures) on the numbers of new COVID-19 infections, in the absence of vaccines. Given this policy's expected change in effectiveness over time, we also measured the effectiveness of having schools closed after a given number of days (from 7 to 100).

METHODS

We pursued our objectives by means of a quantitative panel analysis, building a longitudinal dataset with observations from countries in Europe, from 1 January to 30 September, and estimating the impact of school closure via feasible-generalised least-squares fixed effect and random effect estimators, and analysis of variance (ANOVA) mixed models.

RESULTS

Our results show that having schools closed is effective in reducing the number of new cases. Countries that implement closure have fewer new COVID-19 cases than those that do not. This becomes a reality around 20 days after the implementation of the policy. Its efficacy continues to be detectable up to 100 days after implementation. The result is robust to controls for other forms of social distancing.

CONCLUSION

Results suggest that school closure is effective in reducing the number of people who are infected with COVID-19. Unlike what has been suggested in previous analyses or with regard to other diseases, its efficacy continues to be detectable up to 100 days after the introduction of the policy.

Economic expectations and anxiety during the COVID-19 pandemic: a one-year longitudinal evaluation on Italian university students

The COVID-19 pandemic has produced an extensive aggravation of people's anxiety level. Different policies aimed at fighting the spread of the virus could affect anxiety in various ways. We built an ad hoc web-based survey, administered to the student population of three Italian universities at the beginning of the pandemic and at one year's distance, to collect information on retrospective and current anxiety levels and the underlining reasons. The survey also included questions concerning sociodemographic, economic, labor, lifestyle, academic career, and on-line teaching features, which prevents students from identifying the main survey topic to be anxiety. This research aims at assessing the change in anxiety levels between the analyzed periods and the main determinants of such change, focusing on students' economic expectancies. Results from a Poisson regression model show that anxiety has increased compared to both the pre-pandemic level and the one quantified during the first lockdown. This increase is revealed to be mostly driven by economic and career-related uncertainties, rather than by job loss and proximity to COVID-19. Thus, policymakers should take action to provide certainties both in terms of economic prospects and reopening strategies, especially to avoid that the resulting increase in anxiety translates into an amplified suicide risk.

Does social capital enforce social distancing? The role of bridging and bonding social capital in the evolution of the pandemic

By shaping the way people look at members of their networks as well as strangers, social capital affects the behavior of a population during a pandemic. Over the course of 2020, various countries implemented non-pharmaceutical interventions (NPI), imposing restrictions that were difficult to enforce (due to the scale of the policies) in order to protect the public from the threat of COVID-19. This is an interesting quasi-experimental setting in which to test the compliance of populations with different levels of social capital with government suggestions and prescriptions. With the help of European Social Survey data, and the John Hopkins University dataset on the spread of COVID-19 around the world, the present work aims to test the impact within a sample of European countries with different social capital stocks on the spread of coronavirus. The results show that countries with higher social capital have fewer COVID-19 cases, ceteris paribus for NPI. This is especially true if this capital is of the bonding kind.

Fighting the COVID pandemic: National policy choices in non-pharmaceutical interventions

The COVID-19 pandemic pushed countries to adopt various non-pharmaceutical interventions (NPIs). Due to the features of the pandemic, which spread over time and space, governments could decide whether or not to follow policy choices made by leaders of countries affected by the virus before them. In this study, we aim to empirically model the adoption of NPIs during the first wave of COVID-19 in the 14 European countries with more than 10 million inhabitants, in order to detect whether a policy diffusion mechanism occurred. By means of a multivariate approach based on Principal Component Analysis and Cluster Analysis, we manage to derive three clusters representing different behaviour models to which the different European countries belong in the different periods of the first wave: pre-pandemic, summer relaxation and deep-lockdown scenarios. These results bring a two-fold contribution: on the one hand, they may help us to understand differences and similarities among European countries during the first wave of the COVID-19 outbreak and guide future quantitative or qualitative studies; on the other, our findings suggest that with minor exceptions (such as Sweden and Poland), different countries adopted very similar policy strategies, which are likely to be due more to the unfolding of the pandemic than to specific governmental strategies.