Estimating the severity of COVID-19: Evidence from the Italian epicenter

The role of civic capital on vaccination

Can civic-minded individuals fight against a pandemic? In this paper, we show that civic capital plays an important role when assessing the level of compliance with COVID-19 vaccination recommendations. Analyzing data on a large sample of municipalities from the Italian region of Lombardy, we show that the share of vaccinated individuals is significantly higher in municipalities with higher pre-determined levels of civic capital. These findings are robust to the possibility of spatial spillovers across neighboring municipalities. Our findings contribute to the existing evidence highlighting the importance of individual contributions and civic capital as important behavioral determinants affecting the containment of infectious diseases.

In COVID We Trust: The Impact of The Pandemic on Religiousness-Evidence from Italian Regions

By changing many aspects of everyday life, the COVID-19 pandemic and the social distance policies implemented to face it have affected the behaviour of people all over the world. Has the pandemic also affected people's approach towards the divine? Previous evidence suggests that prayer searches on the Internet rose during the pandemic and that people tend to rely mainly on intrinsic rather than extrinsic religiousness to cope with adversity. In the present contribution, using a set of panel random effect estimators, we compare the change in religious attendance in Italian regions before and during the pandemic. Our results suggest that there has been an increase in religiousness during the COVID-19 pandemic. Our findings are robust to several specifications of the model and to different estimators. This suggests that people derive more comfort from religious activities during hard times that are characterized by uncertainty.

The challenge of estimating the direct and indirect effects of COVID-19 interventions - Toward an integrated economic and epidemiological approach

Decisions on public health measures to contain a pandemic are often based on parameters such as expected disease burden and additional mortality due to the pandemic. Both pandemics and non-pharmaceutical interventions to fight pandemics, however, produce economic, social, and medical costs. The costs are, for example, caused by changes in access to healthcare, social distancing, and restrictions on economic activity. These factors indirectly influence health outcomes in the short- and long-term perspective. In a narrative review based on targeted literature searches, we develop a comprehensive perspective on the concepts available as well as the challenges of estimating the overall disease burden and the direct and indirect effects of COVID-19 interventions from both epidemiological and economic perspectives, particularly during the early part of a pandemic. We review the literature and discuss relevant components that need to be included when estimating the direct and indirect effects of the COVID-19 pandemic. The review presents data sources and different forms of death counts, and discusses empirical findings on direct and indirect effects of the pandemic and interventions on disease burden as well as the distribution of health risks.

Bayesian profile regression to study the ecologic associations of correlated environmental exposures with excess mortality risk during the first year of the Covid-19 epidemic in lombardy, Italy

Many countries, including Italy, have experienced significant social and spatial inequalities in mortality during the Covid-19 pandemic. This study applies a multiple exposures framework to investigate how joint place-based factors influence spatial inequalities of excess mortality during the first year of the Covid -19 pandemic in the Lombardy region of Italy. For the Lombardy region, we integrated municipality-level data on all-cause mortality between 2015 and 2020 with 13 spatial covariates, including 5-year average concentrations of six air pollutants, the average temperature in 2020, and multiple socio-demographic factors, and health facilities per capita. Using the clustering algorithm Bayesian profile regression, we fit spatial covariates jointly to identify clusters of municipalities with similar exposure profiles and estimated associations between clusters and excess mortality in 2020. Cluster analysis resulted in 13 clusters. Controlling for spatial autocorrelation of excess mortality and health-protective agency, two clusters had significantly elevated excess mortality than the rest of Lombardy. Municipalities in these highest-risk clusters are in Bergamo, Brescia, and Cremona provinces. The highest risk cluster (C11) had the highest long-term particulate matter air pollution levels (PM2.5 and PM10) and significantly elevated NO2 and CO air pollutants, temperature, proportion ≤18 years, and male-to-female ratio. This cluster is significantly lower for income and ≥65 years. The other high-risk cluster, Cluster 10 (C10), is elevated significantly for ozone but significantly lower for other air pollutants. Covariates with elevated levels for C10 include proportion 65 years or older and a male-to-female ratio. Cluster 10 is significantly lower for income, temperature, per capita health facilities, ≤18 years, and population density. Our results suggest that joint built, natural, and socio-demographic factors influenced spatial inequalities of excess mortality in Lombardy in 2020. Studies must apply a multiple exposures framework to guide policy decisions addressing the complex and multi-dimensional nature of spatial inequalities of Covid-19-related mortality.

Reliability of COVID-19 data: An evaluation and reflection

IMPORTANCE

The rapid proliferation of COVID-19 has left governments scrambling, and several data aggregators are now assisting in the reporting of county cases and deaths. The different variables affecting reporting (e.g., time delays in reporting) necessitates a well-documented reliability study examining the data methods and discussion of possible causes of differences between aggregators.

OBJECTIVE

To statistically evaluate the reliability of COVID-19 data across aggregators using case fatality rate (CFR) estimates and reliability statistics.

DESIGN, SETTING, AND PARTICIPANTS

Cases and deaths were collected daily by volunteers via state and local health departments, as primary sources and newspaper reports, as secondary sources. In an effort to begin comparison for reliability statistical analysis, BroadStreet collected data from other COVID-19 aggregator sources, including USAFacts, Johns Hopkins University, New York Times, The COVID Tracking Project.

MAIN OUTCOMES AND MEASURES

COVID-19 cases and death counts at the county and state levels.

RESULTS

Lower levels of inter-rater agreement were observed across aggregators associated with the number of deaths, which manifested itself in state level Bayesian estimates of COVID-19 fatality rates.

CONCLUSIONS AND RELEVANCE

A national, publicly available data set is needed for current and future disease outbreaks and improved reliability in reporting.

Questioning the spatial association between the initial spread of COVID-19 and transit usage in Italy

Within the much broader framework of global interest, the dilemma concerning the real impact of mode of transport on the spread of COVID-19 has been a priority for transport stakeholders and policy-makers. How dangerous is it to move around a certain territory? Does the danger depend on the mode of transport? By considering a novel and detailed dataset at the level of local labour markets, we analysed the spatial association between the pre-pandemic propensity to use public transport and excess mortality in Italy attributable to the initial spread of COVID-19. We found that places characterised by larger commuting flows exhibit higher excess mortality during the first wave of the pandemic, but observed no significant spatial association between excess mortality and transit usage. Our results were obtained by considering a wide range of heterogeneity in the estimation of quantile regressions across a variety of specifications. Although we do not provide a definitive answer concerning the risk associated with transit use, our analysis suggests that mobility, not modal choice, should be considered a main driver of the initial contagion.

Characteristics of hospitalized patients with SARS-CoV-2 infection during successive waves of the COVID-19 pandemic in a reference hospital in Spain

Since the beginning of the COVID-19 pandemic and until September 2021, Spain suffered five waves of infection, the latter being related to the expansion of the Delta variant and with a high incidence. A vaccination campaign began in December 2020 and by the end of the fifth wave 77.3% of people had been fully vaccinated. Examining the changing dynamics of COVID-19 pandemic and its impact on outcomes among those hospitalized is essential. Our objective was to ascertain any differences in the characteristics and outcomes of hospitalized patients during that period compared to previous waves. We prospectively enrolled 200 consecutively admitted hospital patients from each wave and collected their clinical and demographic data from the medical records, including symptoms, comorbidities, deaths and whether they needed to be admitted to the Intensive Care Unit to receive assisted ventilation. We found that patients in the fifth wave were considerably younger than before, and the mortality rate fell from 22.5 to 2.0%. Admissions to the Intensive Care Unit decreased from 10 to 2%. Patients in the fifth wave had fewer comorbidities, and the age of the patients who died was higher than those who survived. Our results show a marked improvement in patient outcomes in the fifth wave, suggesting success of the vaccination campaign despite the explosion in cases due to the Delta variant.

SARS-CoV-2-Infection (COVID-19): Clinical Course, Viral Acute Respiratory Distress Syndrome (ARDS) and Cause(s) of Death

SARS-CoV-2-infected symptomatic patients often suffer from high fever and loss of appetite which are responsible for the deficit of fluids and of protein intake. Many patients admitted to the emergency room are, therefore, hypovolemic and hypoproteinemic and often suffer from respiratory distress accompanied by ground glass opacities in the CT scan of the lungs. Ischemic damage in the lung capillaries is responsible for the microscopic hallmark, diffuse alveolar damage (DAD) characterized by hyaline membrane formation, fluid invasion of the alveoli, and progressive arrest of blood flow in the pulmonary vessels. The consequences are progressive congestion, increase in lung weight, and progressive hypoxia (progressive severity of ARDS). Sequestration of blood in the lungs worsens hypovolemia and ischemia in different organs. This is most probably responsible for the recruitment of inflammatory cells into the ischemic peripheral tissues, the release of acute-phase mediators, and for the persistence of elevated serum levels of positive acute-phase markers and of hypoalbuminemia. Autopsy studies have been performed mostly in patients who died in the ICU after SARS-CoV-2 infection because of progressive acute respiratory distress syndrome (ARDS). In the death certification charts, after respiratory insufficiency, hypovolemic heart failure should be mentioned as the main cause of death.

Changes in Acute Myocardial Infarction, Stroke, and Heart Failure Hospitalizations During COVID-19 Pandemic in Tuscany-An Interrupted Time Series Study

Objectives: We evaluate the impact of the COVID-19 pandemic on unplanned hospitalization rates for patients without COVID-19, including their length of stay, and in-hospital mortality, overall, and for acute myocardial infarction (AMI), stroke, and heart failure in the Tuscany region of Italy. Methods: We carried out a population-based controlled interrupted time series study using segmented linear regression with an autoregressive error term based on admissions data from all public hospitals in Tuscany. The primary outcome measure was weekly hospitalization rates; secondary outcomes included length of stay, and in-hospital mortality. Results: The implementation of the pandemic-related mitigation measures and fear of infection was associated with large decreases in inpatient hospitalization rates overall (-182 [-234, -130]), unplanned hospitalization (-39 [-51, -26]), and for AMI (-1.32 [-1.98, -0.66]), stroke (-1.51 [-2.56, -0.44]), and heart failure (-8.7 [-11.1, -6.3]). Average length of stay and percent in-hospital mortality for select acute medical conditions did not change significantly. Conclusion: In Tuscany, Italy, the COVID-19 pandemic was associated with large reductions in hospitalization rates overall, as well as for heart failure, and the time sensitive conditions of AMI and stroke during the months January to July 2020.

COVID-19 in Japan, January-March 2020: insights from the first three months of the epidemic

BACKGROUND

Understanding the characteristics and natural history of novel pathogens is crucial to inform successful control measures. Japan was one of the first affected countries in the COVID-19 pandemic reporting their first case on 14 January 2020. Interventions including airport screening, contact tracing, and cluster investigations were quickly implemented. Here we present insights from the first 3 months of the epidemic in Japan based on detailed case data.

METHODS

We conducted descriptive analyses based on information systematically extracted from individual case reports from 13 January to 31 March 2020 including patient demographics, date of report and symptom onset, symptom progression, travel history, and contact type. We analysed symptom progression and estimated the time-varying reproduction number, Rt, correcting for epidemic growth using an established Bayesian framework. Key delays and the age-specific probability of transmission were estimated using data on exposures and transmission pairs.

RESULTS

The corrected fitted mean onset-to-reporting delay after the peak was 4 days (standard deviation: ± 2 days). Early transmission was driven primarily by returning travellers with Rt peaking at 2.4 (95% CrI: 1.6, 3.3) nationally. In the final week of the trusted period (16-23 March 2020), Rt accounting for importations diverged from overall Rt at 1.1 (95% CrI: 1.0, 1.2) compared to 1.5 (95% CrI: 1.3, 1.6), respectively. Household (39.0%) and workplace (11.6%) exposures were the most frequently reported potential source of infection. The estimated probability of transmission was assortative by age with individuals more likely to infect, and be infected by, contacts in a similar age group to them. Across all age groups, cases most frequently onset with cough, fever, and fatigue. There were no reported cases of patients < 20 years old developing pneumonia or severe respiratory symptoms.

CONCLUSIONS

Information collected in the early phases of an outbreak are important in characterising any novel pathogen. The availability of timely and detailed data and appropriate analyses is critical to estimate and understand a pathogen's transmissibility, high-risk settings for transmission, and key symptoms. These insights can help to inform urgent response strategies.

A Vaccination Simulator for COVID-19: Effective and Sterilizing Immunization Cases

In this work, we present a particle-based SEIR epidemic simulator as a tool to assess the impact of different vaccination strategies on viral propagation and to model sterilizing and effective immunization outcomes. The simulator includes modules to support contact tracing of the interactions amongst individuals and epidemiological testing of the general population. The particles are distinguished by age to represent more accurately the infection and mortality rates. The tool can be calibrated by region of interest and for different vaccination strategies to enable locality-sensitive virus mitigation policy measures and resource allocation. Moreover, the vaccination policy can be simulated based on the prioritization of certain age groups or randomly vaccinating individuals across all age groups. The results based on the experience of the province of Lecco, Italy, indicate that the simulator can evaluate vaccination strategies in a way that incorporates local circumstances of viral propagation and demographic susceptibilities. Further, the simulator accounts for modeling the distinction between sterilizing immunization, where immunized people are no longer contagious, and effective immunization, where the individuals can transmit the virus even after getting immunized. The parametric simulation results showed that the sterilizing-age-based vaccination scenario results in the least number of deaths. Furthermore, it revealed that older people should be vaccinated first to decrease the overall mortality rate. Also, the results showed that as the vaccination rate increases, the mortality rate between the scenarios shrinks.

A SIAT3HE model of the COVID-19 pandemic in Bergamo, Italy

The aim of this article is to give a better understanding of the dynamics of the SARS-CoV-2 pandemic in the Bergamo province (Italy), one of the most hit areas of the world, between February and April 2020. A new compartmental model, called SIAT3HE, was designed and fitted on accurate data about the pandemic provided by ATS Bergamo, the health protection agency of the Bergamo province. Our results show that SARS-CoV-2 reached Bergamo in January and infected 318,000 people, the 28.8% of the province population. The 43.1% of the infected individuals stayed asymptomatic. As 6,028 people died due to COVID-19 till April 30th, the infection fatality ratio of SARS-CoV-2 in the Bergamo province was 1.9%. These results are in very good agreement with available information: the number of infections is consistent with the results of recent serological surveys and the number of deaths due to COVID-19 is close to the excess mortality of the considered period.

COVID-19 and the excess of mortality in Italy from January to April 2020: what are the risks for oldest old?

In February 2020, Italy has been the first country in Europe fighting against COVID-19. In March 2020, Italian government declared national lockdown. Until May 4^th, people stayed in home confinement and only the so-called essential works and activities were continued. Like in other countries, both for the disease severity and for the risk of death, the higher the age of people the higher the risk. In the first months of 2020, Italy saw a very high number of deaths related to COVID-19, with a huge age effect. There is an agreement on the view that there had been also an excess of mortality and on the role of mortality as a correct way to reflect the dynamics of the virus’s spread. In this paper we briefly discuss the trends of mortality during the first 4 months of 2020 according to the data by the Italian National Institute of Statistics.

COVID-19 vaccination and unemployment risk: lessons from the Italian crisis

This paper analyzes the impact of mobility contraction on employee furlough and excess deaths in Italy during the COVID-19 crisis. Our approach exploits rainfall patterns across Italian administrative regions as a source of exogenous variation in human mobility to pinpoint the causal effect of mobility restrictions on excess deaths and furlough workers. Results confirm that the first countrywide lockdown has effectively curtailed the COVID-19 epidemics restricting it mainly to the northern part of the country, with the drawback of a countrywide increase in unemployment risk. Our analysis points out that a mobility contraction of 1% leads to a mortality reduction of 0.6%, but it induces an increase of 10% in Wage Guarantee Funds allowed hours. We discuss return-to-work policies and prioritizing policies for administering COVID-19 vaccines in the most advanced stage of a vaccination campaign when the healthy active population is left to be vaccinated.

COVID-19 in the state of São Paulo: the evolution of a pandemic

OBJECTIVES

To retrospectively describe severe cases of hospitalized patients and deaths related to the COVID-19 epidemic in the state of São Paulo, starting from the date of the first record, with symptoms onset on 02/10/2020 up to 05/20/2021.

METHODS

This is a descriptive study carried out using the Influenza Epidemiological Surveillance System (Sistema de Vigilância Epidemiológica da Gripe - SIVEP-Gripe) database. The rates of incidence, mortality, and accumulated incidence in the period were calculated, stratified by age group and Regional Health Department (RHD). In addition, severe cases were geocoded to analyze their spread across the state; and the Effective R, which determines the spread potential of a virus within a population, was calculated.

RESULTS

There was a significant increase in severe cases and deaths recorded in the period of one year, with incidence and mortality rates being heterogeneous within the state. The most critical periods regarding the incidence of severe cases occurred between May and July 2020 and between March and April 2021. The RHD in São José do Rio Preto, Expanded São Paulo, and Araçatuba concentrated the highest incidence and mortality rates. Severe cases and deaths were more frequent in men and in the population over 60 years, while the main risk conditions related to deaths were heart disease (59%) and diabetes (42,8%).

CONCLUSIONS

These results not only provide a detailed profile for more efficient control action plan, but will also allow the historical understanding of the COVID-19 evolution within the state of São Paulo.

The "Great Lockdown": Inactive workers and mortality by Covid-19

In response to the Covid-19 outbreak, the Italian Government imposed an economic lockdown on March 22, 2020, and ordered the closing of all non-essential economic activities. This paper estimates the causal effects of this measure on mortality by Covid-19 and on mobility patterns. The identification of the causal effects exploits the variation in the active population across municipalities induced by the economic lockdown. The difference-in-differences empirical design compares outcomes in municipalities above and below the median variation in the share of active population before and after the lockdown within a province, also controlling for municipality-specific dynamics, daily shocks at the provincial level, and municipal unobserved characteristics. Our results show that the intensity of the economic lockdown is associated with a statistically significant reduction in mortality by Covid-19 and, in particular, for age groups between 40 and 64 and older (with larger and more significant effects for individuals above 50). Back of the envelope calculations indicate that 4793 deaths were avoided, in the 26 days between April 5 and April 30, in the 3518 municipalities which experienced a more intense lockdown. Several robustness checks corroborate our empirical findings.

Local mortality estimates during the COVID-19 pandemic in Italy

Estimates of the real death toll of the COVID-19 pandemic have proven to be problematic in many countries, Italy being no exception. Mortality estimates at the local level are even more uncertain as they require stringent conditions, such as granularity and accuracy of the data at hand, which are rarely met. The "official" approach adopted by public institutions to estimate the "excess mortality" during the pandemic draws on a comparison between observed all-cause mortality data for 2020 and averages of mortality figures in the past years for the same period. In this paper, we apply the recently developed machine learning control method to build a more realistic counterfactual scenario of mortality in the absence of COVID-19. We demonstrate that supervised machine learning techniques outperform the official method by substantially improving the prediction accuracy of the local mortality in "ordinary" years, especially in small- and medium-sized municipalities. We then apply the best-performing algorithms to derive estimates of local excess mortality for the period between February and September 2020. Such estimates allow us to provide insights about the demographic evolution of the first wave of the pandemic throughout the country. To help improve diagnostic and monitoring efforts, our dataset is freely available to the research community.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s00148-021-00857-y.

How many more? Under-reporting of the COVID-19 deaths in Brazil in 2020

Objective

To evaluate the magnitude of under‐reporting the number of deaths due to COVID‐19 in Brazil in 2020, previously shown to occur due to low rate of laboratory testing for SARS‐CoV‐2, reporting delay, inadequate access to medical care, and its poor quality, leading to the low sensitivity of epidemiological surveillance and poor outcomes, often without laboratory confirmation of the cause of death.

Methods

Excess mortality due to COVID‐19 was estimated directly based on various data sources, and indirectly, based on the difference between the observed and expected number of deaths from serious acute respiratory infection (SARI) and all‐natural causes in 2020 had there been no COVID‐19. The absence of laboratory testing for SARS‐CoV‐2 was adjusted based on the proportion of those who tested positive among the tested individuals whose death was attributed to COVID‐19. Least absolute shrinkage and selection operator (lasso) were used to improve prediction of likely mortality without COVID‐19 in 2020.

Results

Under‐reporting of COVID‐19 deaths was 22.62%, with a corresponding mortality rate per 100 000 inhabitants of 115 by the direct method, 71–76 by the indirect methods based on the excess SARI mortality and 95–104 by excess mortality due to natural causes. COVID‐19 was the third cause of mortality that contributed directly with 18%, and indirectly with additional 10–11% to all deaths in Brazil in 2020.

Conclusions

Underestimation of COVID‐19 mortality between 1:5 and 1:4 is likely its lower bound. Timely and accurate surveillance of death causes is of the essence to evaluate the COVID‐19 burden.

Shifts in alcohol consumption during the COVID-19 pandemic: early indications from Australia

BACKGROUND AND AIM

The effect of the COVID-19 pandemic on alcohol consumption is currently unclear. This study aimed to provide early estimates of how stress and demographics will interact with shifts in harmful alcohol consumption from before the COVID-19 outbreak to 2 months into social distancing.

DESIGN

Cross-sectional convenience sample.

SETTING

Australia.

PARTICIPANTS

A total of 1684 Australians aged 18-65 years who drink at least monthly.

MEASUREMENTS

Items from the Alcohol Use Disorders Identification Test (AUDIT) and the stress subscale of the Depression Anxiety and Stress Scale (DASS).

FINDINGS

Overall, harmful drinking decreased during social distancing measures in our sample [2019 score = 8.2, 95% confidence interval (CI) = 7.9-8.4; during the pandemic = 7.3, 95% CI = 7.1-7.6]. Younger drinkers, particularly young women, decreased their consumption the most, but there was a small increase in consumption in middle-aged women. Drinkers experiencing high levels of stress also reported a relatively higher shift in harmful consumption compared with those with low levels of stress (β = 0.65, P = 0.003), despite reporting a small decrease overall.

CONCLUSIONS

The closure of licensed premises and social distancing measures in Australia in response to the COVID-19 outbreak appear to have reduced harmful alcohol consumption in younger drinkers, particularly young women.

Estimating COVID-19 mortality in Italy early in the COVID-19 pandemic

Estimating rates of COVID-19 infection and associated mortality is challenging due to uncertainties in case ascertainment. We perform a counterfactual time series analysis on overall mortality data from towns in Italy, comparing the population mortality in 2020 with previous years, to estimate mortality from COVID-19. We find that the number of COVID-19 deaths in Italy in 2020 until September 9 was 59,000–62,000, compared to the official number of 36,000. The proportion of the population that died was 0.29% in the most affected region, Lombardia, and 0.57% in the most affected province, Bergamo. Combining reported test positive rates from Italy with estimates of infection fatality rates from the Diamond Princess cruise ship, we estimate the infection rate as 29% (95% confidence interval 15–52%) in Lombardy, and 72% (95% confidence interval 36–100%) in Bergamo.

Estimates of COVID-19-related mortality are limited by incomplete testing. Here, the authors perform counterfactual analyses and estimate that there were 59,000–62,000 deaths from COVID-19 in Italy until 9^th September 2020, approximately 1.5 times higher than official statistics.

Non-COVID-19 patients in times of pandemic: Emergency department visits, hospitalizations and cause-specific mortality in Northern Italy

The COVID-19 pandemic forced healthcare services organization to adjust to mutating healthcare needs. Not exhaustive data are available on the consequences of this on non-COVID-19 patients. The aim of this study was to assess the impact of the pandemic on non-COVID-19 patients living in a one-million inhabitants' area in Northern Italy (Bologna Metropolitan Area-BMA), analyzing time trends of Emergency Department (ED) visits, hospitalizations and mortality. We conducted a retrospective observational study using data extracted from BMA healthcare informative systems. Weekly trends of ED visits, hospitalizations, in- and out-of-hospital, all-cause and cause-specific mortality between December 1st, 2019 to May 31st, 2020, were compared with those of the same period of the previous year. Non-COVID-19 ED visits and hospitalizations showed a stable trend until the first Italian case of COVID-19 has been recorded, on February 19th, 2020, when they dropped simultaneously. The reduction of ED visits was observed in all age groups and across all severity and diagnosis groups. In the lockdown period a significant increase was found in overall out-of-hospital mortality (43.2%) and cause-specific out-of-hospital mortality related to neoplasms (76.7%), endocrine, nutritional and metabolic (79.5%) as well as cardiovascular (32.7%) diseases. The pandemic caused a sudden drop of ED visits and hospitalizations of non-COVID-19 patients during the lockdown period, and a concurrent increase in out-of-hospital mortality mainly driven by deaths for neoplasms, cardiovascular and endocrine diseases. As recurrencies of the COVID-19 pandemic are underway, the scenario described in this study might be useful to understand both the population reaction and the healthcare system response at the early phases of the pandemic in terms of reduced demand of care and systems capability in intercepting it.

Epidemics and macroeconomic outcomes: Social distancing intensity and duration

We analyze the determination of the optimal intensity and duration of social distancing policy aiming to control the spread of an infectious disease in a simple macroeconomic-epidemiological model. In our setting the social planner wishes to minimize the social costs associated with the levels of disease prevalence and output lost due to social distancing, both during and at the end of epidemic management program. Indeed, by limiting individuals' ability to freely move or interact with others (since requiring to wear face mask or to maintain physical distance from others, or even forcing some businesses to remain closed), social distancing has on the one hand the effect to reduce the disease incidence and on the other hand to reduce the economy's productive capacity. We analyze both the early and the advanced epidemic stage intervention strategies highlighting their implications for short and long run health and macroeconomic outcomes. We show that both the intensity and the duration of the optimal social distancing policy may largely vary according to the epidemiological characteristics of specific diseases, and that the balancing of the health benefits and economic costs associated with social distancing may require to accept the disease to reach an endemic state. Focusing in particular on COVID-19 we present a calibration based on Italian data showing how the optimal social distancing policy may vary if implemented at national or at regional level.

A scaling approach to estimate the age-dependent COVID-19 infection fatality ratio from incomplete data

SARS-CoV-2 has disrupted the life of billions of people around the world since the first outbreak was officially declared in China at the beginning of 2020. Yet, important questions such as how deadly it is or its degree of spread within different countries remain unanswered. In this work, we exploit the 'universal' increase of the mortality rate with age observed in different countries since the beginning of their respective outbreaks, combined with the results of the antibody prevalence tests in the population of Spain, to unveil both unknowns. We test these results with an analogous antibody rate survey in the canton of Geneva, Switzerland, showing a good agreement. We also argue that the official number of deaths over 70 years old might be importantly underestimated in most of the countries, and we use the comparison between the official records with the number of deaths mentioning COVID-19 in the death certificates to quantify by how much. Using this information, we estimate the infection fatality ratio (IFR) for the different age segments and the fraction of the population infected in different countries assuming a uniform exposure to the virus in all age segments. We also give estimations for the non-uniform IFR using the sero-epidemiological results of Spain, showing a very similar increase of the fatality ratio with age. Only for Spain, we estimate the probability (if infected) of being identified as a case, being hospitalized or admitted in the intensive care units as function of age. In general, we observe a nearly exponential increase of the fatality ratio with age, which anticipates large differences in total IFR in countries with different demographic distributions, with numbers that range from 1.82% in Italy, to 0.62% in China or even 0.14% in middle Africa.

Asocial capital: Civic culture and social distancing during COVID-19

Social distancing can slow the spread of COVID-19 if citizens comply with it and internalize the cost of their mobility on others. We study how civic values mediate this process using data on mobility across Italian provinces between January and May 2020. We find that after the virus outbreak mobility declined, but significantly more in areas with higher civic capital, both before and after a mandatory national lockdown. The effect is not driven by differences in the risk of contagion, health-care capacity, geographic socioeconomic and demographic factors, or by a general North-South divide. Simulating a SIR model calibrated on Italy, we estimate that if all provinces had the same civic capital as those in top-quartile, COVID-related deaths would have been about 60% lower. We find consistent results for Germany where the incidence of the pandemic and restrictions to mobility were milder.

Asocial capital: Civic culture and social distancing during COVID-19

Social distancing can slow the spread of COVID-19 if citizens comply with it and internalize the cost of their mobility on others. We study how civic values mediate this process using data on mobility across Italian provinces between January and May 2020. We find that after the virus outbreak mobility declined, but significantly more in areas with higher civic capital, both before and after a mandatory national lockdown. The effect is not driven by differences in the risk of contagion, health-care capacity, geographic socioeconomic and demographic factors, or by a general North-South divide. Simulating a SIR model calibrated on Italy, we estimate that if all provinces had the same civic capital as those in top-quartile, COVID-related deaths would have been about 60% lower. We find consistent results for Germany where the incidence of the pandemic and restrictions to mobility were milder.

Using newspaper obituaries to "nowcast" daily mortality: Evidence from the Italian COVID-19 hot-spots

Real-time tracking of epidemic helps governments and health authorities make timely data-driven decisions. Official mortality data, whenever reliable and available, is usually published with a substantial delay. We report results of using newspapers obituaries to "nowcast" the mortality levels observed in Italy during the COVID-19 outbreak between February 24, 2020 and April 15, 2020. Mortality levels predicted using obituaries outperform forecasts based on past mortality according to several performance metrics, making obituaries a potentially valid alternative source of information to deal with epidemic surveillance.

Patterns of COVID-19 related excess mortality in the municipalities of Northern Italy during the first wave of the pandemic

The impact of Coronavirus Disease 2019 (COVID-19) on mortality in Italy has been described at the regional level, while less is known about mortality in municipalities, although the spatial distribution of COVID-19 in its first wave has been uneven. We aimed to describe the excess mortality due to COVID-19 from February 23rd to April 30th, 2020 in the three most affected Italian regions, in age and gender subgroups within each municipality. Excess mortality varied widely among municipalities even within the same region; it was higher among the elderly and higher in males except in the ≥75 age group. Thus, nearby municipalities may show a different mortality burden despite being under common regional health policies, possibly as a result of local reinforcements of regional policies. Identifying the municipalities where mortality was higher and the pathways used by the virus to spread may help to concentrate efforts in understanding the reasons why this happened and to identify the frailest areas in light of recurrences of the epidemic.