Epidemiological characteristics of COVID-19 cases and estimates of the reproductive numbers 1 month into the epidemic, Italy, 28 January to 31 March 2020

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.

Stay at Home! Governance Quality and Effectiveness of Lockdown

In order to control the spread of the COVID-19 pandemic, during the first wave of the pandemic numerous countries decided to adopt lockdown policies. It had been a considerable time since such measures were last introduced, and the first time that they were implemented on such a global scale in a contemporary, information intensive society. The effectiveness of such measures may depend on how citizens perceive the capacity of government to set up and implement sound policies. Indeed, lockdown and confinement policies in general are binding measures that people are not used to, and which raise serious concerns among the population. For this reason governance quality could affect the perception of the benefits related to the government's choice to impose lockdown, making citizens more inclined to accept it and restrict their movements. In the present paper we empirically investigate the relation between the efficacy of lockdown and governance quality (measured through World Governance Indicators). Our results suggest that countries with higher levels of government effectiveness, rule of law and regulatory quality reach better results in adopting lockdown measures.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11205-021-02742-3.

Differences in the clinical characteristics of COVID-19 patients who died in hospital during different phases of the pandemic: national data from Italy

Background

Epidemiological data obtained during the initial wave of the COVID-19 epidemic showed that persons dying with COVID-19 were typically older men with multiple chronic conditions. No studies have assessed if the characteristics of patients dying with COVID-19 have changed in the second phase of the epidemic, when the initial wave subsided. The aim of the present study was to compare characteristics of patients dying with COVID-19 in Italy in the first ‘peak’ phase of the epidemic and in its second phase.

Methods

Medical charts of patients with COVID-19 who died while in hospital in Italy were reviewed to extract information on pre-existing comorbidities, in-hospital complications, and disease trajectories. The course of the epidemic was classified in two 3-month periods: March–May 2020 and June–August 2020.

Findings

Overall, in the Italian population, 34,191 COVID-19 deaths occurred in March–May 2020 and 1,404 in June–August 2020. Patients dying in March–May were significantly younger (80.1 ± 10.6 vs. 82.8 ± 11.1 years, p < 0.001) and less frequently female (41.9% vs. 61.8%, p < 0.001) than those dying in June–August. The medical charts of 3533 patients who died with PCR-confirmed SARS-CoV-2 infection in March–May 2020 (10.3% of all deaths occurring in this period) and 203 patients who died in June–August 2020 (14.5% of all deaths occurring in this period) were analysed. Patients who died in March–May 2020, compared to those who died in June–August 2020, had significantly lower rates of multiple comorbidities (3 or more comorbidities: 61.8% vs 74.5%, p = 0.001) and superinfections (15.2% vs. 52.5%, p < 0.001). Treatment patterns also substantially differed in the two study periods, with patients dying in March–May 2020 being less likely to be treated with steroids (41.7% vs. 69.3%, p < 0.001) and more likely to receive antivirals (59.3% vs. 41.4%, p < 0.001). Survival time also largely differed, with patients dying in March–May 2020 showing a shorter time from symptoms onset to death (mean interval: 15.0 vs. 46.6 days, p < 0.001). The differences observed between the two periods remained significant in a multivariate analysis.

Interpretation

The clinical characteristics of patients dying with COVID-19 in Italy, their treatment and symptom-to-death survival time have significantly changed overtime. This is probably due to an improved organization and delivery of care and to a better knowledge of disease treatment.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40520-020-01764-0.

The Efficacy of Lockdown Against COVID-19: A Cross-Country Panel Analysis

BACKGROUND

There has been much debate about the effectiveness of lockdown measures in containing COVID-19, and their appropriateness given the economic and social cost they entail. To the best of our knowledge, no existing contribution to the literature has attempted to gauge the effectiveness of lockdown measures over time in a longitudinal cross-country perspective.

OBJECTIVES

This paper aims to fill the gap in the literature by assessing, at an international level, the effect of lockdown measures (or the lack of such measures) on the numbers of new infections. Given this policy's expected change in effectiveness over time, we also measure the effect of having a lockdown implemented over a given number of days (from 7 to 20 days).

METHODS

We pursue our objectives by means of a quantitative panel analysis, building a longitudinal dataset with observations from countries all over the world, and estimating the impact of lockdown via feasible generalized least squares fixed effect, random effects, generalized estimating equation, and hierarchical linear models.

RESULTS

Our results show that lockdown is effective in reducing the number of new cases in the countries that implement it, compared with those countries that do not. This is especially true around 10 days after the implementation of the policy. Its efficacy continues to grow up to 20 days after implementation.

CONCLUSION

Results suggest that lockdown is effective in reducing the R0, i.e. the number of people infected by each infected person, and that, unlike what has been suggested in previous analyses, its efficacy continues to hold 20 days after the introduction of the policy.