Search

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 4th, 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Long-term exposure to ambient air pollutant concentrations is known to cause chronic lung inflammation, a condition that may promote increased severity of COVID-19 syndrome caused by the novel coronavirus (SARS-CoV-2). In this paper, we empirically investigate the ecologic association between long-term concentrations of area-level fine particulate matter (PM2.5) and excess deaths in the first quarter of 2020 in municipalities of Northern Italy. The study accounts for potentially spatial confounding factors related to urbanization that may have influenced the spreading of SARS-CoV-2 and related COVID-19 mortality. Our epidemiological analysis uses geographical information (e.g., municipalities) and negative binomial regression to assess whether both ambient PM2.5 concentration and excess mortality have a similar spatial distribution. Our analysis suggests a positive association of ambient PM2.5 concentration on excess mortality in Northern Italy related to the COVID-19 epidemic. Our estimates suggest that a one-unit increase in PM2.5 concentration (µg/m3) is associated with a 9% (95% confidence interval: 6–12%) increase in COVID-19 related mortality. [ABSTRACT FROM AUTHOR]

Background There are still many unknowns about COVID-19. We do not know its exact mortality rate nor the speed through which it spreads across communities. This lack of evidence complicates the design of appropriate response policies. Methods We source daily death registry data for 4100 municipalities in Italy's north and match them to Census data. We augment the dataset with municipality-level data on a host of co-factors of COVID-19 mortality, which we exploit in a differences-in-differences regression model to analyze COVID-19-induced mortality. Results We find that COVID-19 killed more than 0.15% of the local population during the first wave of the epidemic. We also show that official statistics vastly underreport this death toll, by about 60%. Next, we uncover the dramatic effects of the epidemic on nursing home residents in the outbreak epicenter: in municipalities with a high share of the elderly living in nursing homes, COVID-19 mortality was about twice as high as in those with no nursing home intown. Conclusions A pro-active approach in managing the epidemic is key to reduce COVID-19 mortality. Authorities should ramp-up testing capacity and increase contact-tracing abilities. Adequate protective equipment should be provided to nursing home residents and staff. [ABSTRACT FROM AUTHOR]

Italy was the first western country strongly hit by the COVID-19 outbreak. This Perspective focuses on the large number of deaths that occurred in nursing homes during the first wave of the pandemic, and the weak capacity of public policy to provide them with adequate protection. The analysis focuses on the case of the Lombardy Region, where the mortality rate due to COVID-19 in nursing homes was the highest in Europe. In the search for possible causes, we investigate the situation of such facilities before the pandemic. Two aspects are analyzed: their institutional embeddedness and recent trends in their management. We conclude by arguing that the negative impact of COVID-19 stems from the poor development of long-term care policy and from the marginality of residential institutions within the healthcare system. [ABSTRACT FROM AUTHOR]

Background: Italy has been the first European country to be affected by the COVID-19 epidemic which started out at the end of February. In this report, we focus our attention on the Veneto Region, in the North-East of Italy, which is one of the areas that were first affected by the rapid spread of SARS-CoV-2. We aim to evaluate the trend of all-cause mortality and to give a description of the characteristics of the studied population.Methods: Data used in the analyses were released by the majority of municipalities and cover the 93% of the total population living in the Veneto Region. We evaluated the trend of overall mortality from Jan.01 to Jun.30. 2020. Moreover we compared the COVID-19-related deaths to the overall deaths.Results: From March 2020, the overall mortality rate increased exponentially, affecting males and people aged > 76 the most. The confirmed COVID-19-related death rate in the Veneto region between Mar.01 and Apr.302020 is 30 per 100,000 inhabitants. In contrast, the all-cause mortality increase registered in the same months in the municipalities included in the study is 219 per 100,000 inhabitants.Conclusions: COVID-19 has a primary role in the increase in mortality but does not entirely explain such a high number of deaths. Strategies need to be developed to reduce this gap in case of future waves of the pandemic. [ABSTRACT FROM AUTHOR]