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Before the COVID-19 pandemic, ventilation in buildings was not always given its due importance. The World Health Organization has highlighted the important role of air exchange with the outdoors in improving the air quality in buildings; buildings should, therefore, be equipped with mechanical ventilation or adequate air conditioning systems. This paper aims to investigate different retrofit solutions for air conditioning, evaluating them in terms of energy consumption and cost and the impact of increased outdoor air exchange rates on countering the propagation of COVID-19; the latter is the main novelty of the paper. As a case study, we take an existing office building located in Central Italy that was previously not equipped with a mechanical ventilation system (a system with primary air was introduced during the study). The energy analysis was conducted using dynamic simulation software after validation through energy bills; energy and economic analyses were conducted considering different external-air exchange rates. An optimal number of outdoor air changes was found to mitigate the risk of COVID-19 infection, a finding in line with the international literature. The increase in air changes with outdoor air leads to a rise in energy consumption and costs. These values were evaluated for different air conditioning systems and operational schedules. These drawbacks can be made less significant by combining interventions in the system with energy-efficiency measures applied to the building envelope. [ABSTRACT FROM AUTHOR]

Air conditioning systems can play a positive or negative role in the spread of COVID-19 infection. The importance of sufficient outdoor air changes in buildings was highlighted by the World Health Organization, therefore these should be guaranteed by mechanical ventilation systems or adequate air conditioning systems. The proposed case study concerns the optimal number of outdoor air changes to limit COVID-19 contagion for a school building in Central Italy. The Wells–Riley model is used to assess the risk of airborne infection, while energy consumption is calculated by a dynamic energy simulation software. The scope of the paper offers an innovative method to define the optimal ventilation strategy for the building's HVAC system design to reduce the risk of infection with limited increases in energy consumption and greenhouse gas emissions. Results show that the desirable approach is the one in which the same low value of contagion risk is set in all rooms. This new approach results in significant energy savings, compared to the most common ones (setting the same high outdoor air rates for all rooms) to counteract the risk of infection. Finally, the zero-emission building target is verified by introducing a suitable photovoltaic system to offset pollutant emissions. [ABSTRACT FROM AUTHOR]

This paper uses the case of Italy during the Covid-19 pandemic to critically assess the EU legal framework on third-country national migrants' equal access to social benefits. In Italy, migrants are structurally excluded from core social protections, a situation that during the pandemic led to a worsening of existing patterns of inequality; migrants have been more exposed than citizens to poverty, unemployment, and destitution. The first part of the paper looks for the EU legal root of this situation: it examines the EU legal framework in the migration field, showing that it is affected by fragmentation and inconsistencies. These problems become even more acute at the national level, where the Italian legislature mis-transposed the EU migration directives, thus affecting the use of discretionary clauses therein and severely curtailing migrants' equal treatment rights. Then, the second part of the paper asks whether adopting a mainstreaming approach to enhance equality could improve the situation of migrants. The paper argues that equality mainstreaming in the migration field shows good potential, while also encountering some structural limits. Therefore, it can hardly be considered a silver bullet against the problem of migrants' discrimination. [ABSTRACT FROM AUTHOR]

Several animal species have been found to be susceptible to SARS-CoV-2 infection. The occurrence of infection in dogs and cats living in close contact with owners deserves particular attention from public health authorities in a One Health approach. In this study, we conducted serological screening to identify SARS-CoV-2 exposure in the sera from dogs and cats in three regions of southern Italy sampled during the years 2021 and 2022. We collected 100 serum samples in 2021 (89 from dogs and 11 from cats) and 640 in 2022 (577 from dogs and 63 from cats). Overall, the ELISA positivity rate was found to be 2.7% (20/740), with higher seroprevalence in dogs. Serum neutralization tests confirmed positivity only in two samples collected from dogs, and the assays, performed with serologically distinct SARS-CoV-2 variants, showed variant-specific positivity. This paper shows that monitoring SARS-CoV-2 exposure in animals might be affected by the viral antigenic evolution, which requires continuous updates to the serological tests used. Serological surveys are useful in understanding the true extent of exposure occurring in specific animal populations, not suffering the same limitations as molecular tests, and could help in identifying the infecting virus if tests able to characterize the immune response are used. The use of variant-specific validated serological methods should always be considered in serosurvey studies in order to determine the real impact of emerging variants on animal populations and its implications for veterinary and human health, as well as to identify potential reservoirs of the virus and its evolutionary changes. [ABSTRACT FROM AUTHOR]

The paper reports on the results of a comparative corpus analysis of texts published in Primorski dnevnik, the Slovenian daily published in Italy, in 2020 and 2021. We contrast these texts with information from Slovenian corpora and language resources. The research is focused on the lexis connected with the Covid-19 epidemic as this topic brings about a number of specifics such as rapid genesis and determinologization, single- or self-referentiality, using loanwords (from English), etc. The research is based on corpus-linguistic survey of 618 issues (two volumes) of the Trieste daily newspaper Primorski dnevnik. We used this body of texts to create a corpus that can be used to discern the differences in the use of lexemes in different datasets. The aim of the paper is to demonstrate the level of difference in the lexis of Standard Slovene on both sides of the border. For this reason, we chose to employ corpus methodology as it allows us to compare large bodies of data. The analysis confirmed our initial hypothesis that there is a high level of variation in language use in this region and that this variation cannot be attributed to the factors that normally explain the deviations from standard language, the effects of languages in contact and minority languages. [ABSTRACT FROM AUTHOR]

Purpose: This paper investigates the relationship between labour hoarding practices and training investments during severe economic downturns focusing on the case of Italy during the Great Recession. Design/methodology/approach: Data come from the 2010 Italian wave of Continuing Vocational Training Survey (CVTS). Econometric estimates plug a proxy of labour hoarding into the probability function that firms provide either off-the-job or on-the-job training. A bivariate selectivity probit model is also used for robustness sake. Findings: Results show that labour hoarding should not be considered as an enhancer of training investments when considered as a standing-alone practice in presence of severe and deep economic downturn. However, labour hoarding does not penalize off-the-job training investments if it occurs in an innovative firm or in a firm that perceive specific skill requirements in the workforce during the recessionary period. Originality/value: The paper contributes to the debate on the role of labour hoarding during severe recessions by showing that it cannot be functional to re-oriented firms' investments aimed at upskilling their workforce. It is only compatible with new training courses that accompany the workforce across a technological transition. Policy implications deals with the suitability of job retention schemes or state-financed furlough during recessions, as occurred during the coronavirus disease 2019 (COVID-19) pandemic. [ABSTRACT FROM AUTHOR]

COVID-19, which broke out globally in 2019, is an infectious disease caused by a novel strain of coronavirus, and its spread is highly contagious and concealed. Environmental vectors play an important role in viral infection and transmission, which brings new difficulties and challenges to disease prevention and control. In this paper, a type of differential equation model is constructed according to the spreading functions and characteristics of exposed individuals and environmental vectors during the virus infection process. In the proposed model, five compartments were considered, namely, susceptible individuals, exposed individuals, infected individuals, recovered individuals, and environmental vectors (contaminated with free virus particles). In particular, the re-positive factor was taken into account (i.e., recovered individuals who have lost sufficient immune protection may still return to the exposed class). With the basic reproduction number R 0 of the model, the global stability of the disease-free equilibrium and uniform persistence of the model were completely analyzed. Furthermore, sufficient conditions for the global stability of the endemic equilibrium of the model were also given. Finally, the effective predictability of the model was tested by fitting COVID-19 data from Japan and Italy. [ABSTRACT FROM AUTHOR]

"Can order spring from Chaos?" is the title of an extensive Report on Italian science published by NATURE on 12 May 1983 and written by Robert Walgate, the Chief European Correspondent. It is a twenty pages complete paper touching all aspects of the struggle of Italian scientists to work in the "curious amalgam of ingenuity and muddle, a reflection of the political system". (Nature, 1983; 303: 109–128). To read it after four decades is interesting but somewhat depressing since the main problems unfolded in the paper have not been solved, starting with the largely insufficient support of fundamental curiosity driven research. At page 114 you could find a item called: ITALY's TOP SCIENTISTS: Four in the top one thousand. The Author refers to the data reported by the ISI (Institute of Scientific Information) that took two years to scan 3,000 major journals over the period 1965–78 and covered 5 millions articles and 67 millions references. The four top Italian scientists working in Italy were: Eraldo Antonini (3127 citations), Enrico Clementi (4001), Silvio Garattini (2833), and Giorgio Giacomelli (2483); 3 out of four were 52 years old, and one 55. Antonini did not see the Report since he passed away on March 18, 1983. However the information leaked before the publication of Nature because I remember the Messaggero of Rome reporting a whole page with the ranking of the four Italians, and even a picture of Eraldo. The students of the first year Medical course, his Class, welcomed the Professor with a standing ovation. After a short time the Board of the SIB (Società Italiana di Biochimica) casted a unanimous vote in favour of the motion of President Noris Siliprandi to begin the annual Congress with an Antonini Lecture, forever. As reported below, the tradition began immediately at the Congress in Saint-Vicent, Italy, and is continuing. In this paper I report an account of the Eraldo Antonini Lectures that I attended over the years and until September 2019, a few months before the pandemics lock down. [ABSTRACT FROM AUTHOR]

Background: Coronavirus disease 2019 (COVID-19) has had a significant influence on nutritional status. There have been several studies on dietary habits and nutritional status in connection with COVID-19. However, there has been no research on the bibliometric analysis of these papers. Therefore, our objective was to assess the most relevant scientific research on nutrition and COVID-19, as well as to assess current hot themes. Methods: We obtained data from the Scopus database on June 30, 2021. Qualitative and quantitative analyzes were conducted based on the Scopus. Collaboration and term analysis was performed using VOSviewer software version 1.6.16. Results: At the time of data collection, there were 177,946 documents in COVID-19. Scopus found 1885 articles related to nutrition and COVID-19 after narrowing the search to those terms. This includes 1309 (69.44%) research articles, 268 (14.22%) review papers, and 308 other types of document. The USA was the largest producer, with 24.83% of the documents, followed by Italy with 11.88% (n = 224), the UK with 10.82% (n = 204), and China with 7.59% (n = 143). The most active institution was Sapienza Università di Roma (n = 30, 1.59%). The leading journal in COVID-19 nutrition research was Nutrients (n = 115, 6.10%). The article with 310 citations published by Di Renzo et al. in 2020 was the most influential reference. The hot topics were stratified into three clusters: (1) "Food security in the COVID-19 pandemic"; (2) "nutritional determinants and COVID-19 outcomes"; and (3) "changes in dietary habits during the COVID-19 pandemic and its consequences". Conclusions: This is the first bibliometric research to offer comprehensive information on COVID-19 and nutrition in the published literature. Research will likely be helpful to scholars and policymakers. This study sheds light on the growth and development of nutrition and covid-19-related research and should contribute to the expansion of the global frontier in the major hot topics, including "food security in the COVID-19 pandemic"; "nutritional determinants and COVID-19 outcomes"; and "changes in diet habits during the COVID-19 pandemic and its consequences". [ABSTRACT FROM AUTHOR]

2020 will be remembered worldwide as the year of COVID-19 outbreak. The onset of this pandemic abruptly changed everybody's life and, in a particular manner, doctors' lives. Our hand surgery department became rapidly one of the first COVID-19-specialized wards in Italy, impacting considerably the authors' routines and activities. In this paper, the authors focus on how the demographics of patients with hand trauma changed and how they had to modify their activity. The authors retrospectively took into consideration all patients reaching their emergency department (ED) with hand trauma between 9 March 2020 (the day of the beginning of the first lockdown in Italy) and 8 March 2021 and compared them to those who reached the ED in the three previous years. Authors have analyzed the number of patients, their gender and age, the severity of their trauma, where the trauma occurred, the type of lesion, the percentage of patients who underwent surgery, and the percentage of patients who had an emergency admission. In the last year, the number of patients reaching the ED for a hand trauma has been reduced by two thirds (975 patients during the past year), the mean age of those patients has slightly increased, the severity of cases has increased, places of trauma and type of lesions have changed, and, lastly, the percentage of patients needing surgery who were admitted immediately has increased. This paper shows how the type of patients reaching the ED changed and discusses how surgeons evolved and modified their habits in treating those patients during the first lockdown and the year that followed. [ABSTRACT FROM AUTHOR]

Background: In 2020 the world faced the spread of the coronavirus infection disease (Covid-19). This was a general public health emergency but many people with disabilities might have been particularly affected. Objective: This paper aims to investigate the impact of the Covid-19 pandemic on children with Cerebral Palsy (CP) and their families. Methods: 110 parents of children with CP (aged 2 to 19) who completed a questionnaire were included. These children were under the care of one of the Italian Children Rehabilitation Centers. Socio-demographic and clinical information about patients and their families were collected. In addition, difficulties on adopting protective measures and in respecting lockdown rules by children were explored. We adopted the ICF (International Classification of Functioning, Disability and Health) framework to create multiple choice questions. Descriptive statistics were reported and logistic regression analyses were run in order to identify the predictors of perceived impairment in motor, speech, manual and behavioral abilities. Results: Daily activities of children, as well as rehabilitation and fitness sessions, underwent a change during the pandemic. Spending more time with family due to lockdown measures, has had, in some cases a positive effect however there was a perceived decrease in rehabilitation support and school activities. The age range (between 7 and 12 years) and difficulty in respecting rules emerged as significant predictors of the perceived impairment due to Covid-19 pandemic. Conclusions: The pandemic has had different impacts on children and their families on the basis of children's characteristics. Rehabilitation activities during a hypothetic lockdown should consider these characteristics. [ABSTRACT FROM AUTHOR]

COVID-19 is the highly communicable disease which is being announced as pandemic by WHO. The disease has already impacted the economies of big nations like China, Italy, United states etc and now this disease is hitting our developing country i.e. India too. COVID-19 or Corona virus is human to human spread disease and thus social distancing is the only measure which everyone can take to minimize its spread. National lockdown is the measure taken by Government to create distance among people. But what will be the probable impact of this lockdown on different sectors of our country. This paper aims to analyze impact of COVID-19 on the educational sector of India. [ABSTRACT FROM AUTHOR]

Around the world, the 2019 Coronavirus disease (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has raised serious public health problems and major medical challenges. The Italian Society of Pediatric Gastroenterology, Hepatology and Nutrition (SIGENP) published several papers on the impact of COVID-19 on the current management, diagnosis, and treatment of acute and chronic gastrointestinal, hepatic, immune-mediated, and functional disorders. The present article summarizes the most relevant SIGENP reports and consensus during and after the peak of the COVID-19 outbreak, including the diagnosis and treatment of inflammatory bowel disease (IBD), indications and timing of digestive endoscopy, and insights into the novel hepatitis. [ABSTRACT FROM AUTHOR]

During the first wave of the COVID-19 pandemic in Italy, practitioners had to make tragic decisions regarding the allocation of scarce resources in the ICU. The Italian debate has paid a lot of attention to identifying the specific regulatory criteria for the allocation of resources in the ICU; in this paper, however, we argue that deciding such criteria is not enough for the implementation of fair and transparent allocative decisions. In this respect, we discuss three ethical issues: (a) in the Italian context, the treating physician, rather than a separate committee, was generally the one responsible for the allocation decision; (b) although many allocative guidelines have supported moral equivalence between withholding and withdrawing treatments, some health professionals have continued to consider it a morally problematic aspect; and (c) the health workers who have had to make the aforementioned decisions or even only worked in ICU during the pandemic often experienced moral distress. We conclude by arguing that, even if these problems are not directly related to the above-mentioned issues of distributive justice, they can nevertheless directly affect the quality and ethics of the implementation of allocative criteria, regardless of those chosen. [ABSTRACT FROM AUTHOR]

The last year of Covid-19 pandemic has been characterized by the continuous chase between the vaccination campaign and the appearance of new variants that puts further obstacles to the possibility of eradicating the virus and returning to normality in a short period. In the present paper we develop a deterministic compartmental model to describe the evolution of the Covid-19 in Italy as a combined effect of vaccination campaign, new variant spreading and mobility restrictions. Particular attention is given to the mechanism of waning immunity, appropriately timed with respect to the effective progress of the vaccination campaign in Italy. We perform a retrospective analysis in order to explore the role that different mechanisms, such as behavioral changes, variation of the population mobility, seasonal variability of the virus infectivity, and spreading of new variants have had in shaping the epidemiological curve. We find that, in the large time window considered, the most relevant mechanism is the seasonal variation in the stability of the virus, followed by the awareness mechanism, that induces individuals to increase/relax self-protective measures when the number of active cases increases/decreases. The appearance of the Delta variant and the mobility variations have had instead only marginal effects. In absence of vaccines the emerging scenario would have been dramatic with a percentage difference in the number of total infections and total deaths, in both cases, larger than fifty per cent. The model also predicts the appearance of a more contagious variant (the Omicron variant) and its becoming dominant in January 2022. [ABSTRACT FROM AUTHOR]

Several epidemiological models have been proposed to study the evolution of COVID-19 pandemic. In this paper, we propose an extension of the SUIHTER model, to analyse the COVID-19 spreading in Italy, which accounts for the vaccination campaign and the presence of new variants when they become dominant. In particular, the specific features of the variants (e.g. their increased transmission rate) and vaccines (e.g. their efficacy to prevent transmission, hospitalization and death) are modeled, based on clinical evidence. The new model is validated comparing its near-future forecast capabilities with other epidemiological models and exploring different scenario analyses. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has been characterized by a social media "infodemic": an overabundance of information whose authenticity may not always be guaranteed. With the potential to lead individuals to harmful decisions for the society, this infodemic represents a severe threat to information security, public health and democracy. In this paper, we assess the interplay between the infodemic and specific aspects of the pandemic, such as the number of cases, the strictness of containment measures, and the news media coverage. We perform a comparative study on three countries that employed different managements of the COVID-19 pandemic in 2020—namely Italy, the United Kingdom, and New Zealand. We first analyze the three countries from an epidemiological perspective to characterize the impact of the pandemic and the strictness of the restrictions adopted. Then, we collect a total of 6 million posts from Facebook to describe user news consumption behaviors with respect to the reliability of such posts. Finally, we quantify the relationship between the number of posts published in each of the three countries and the number of confirmed cases, the strictness of the restrictions adopted, and the online news media coverage about the pandemic. Our results show that posts referring to reliable sources are consistently predominant in the news circulation, and that users engage more with reliable posts rather than with posts referring to questionable sources. Furthermore, our modelling results suggest that factors related to the epidemiological and informational ecosystems can serve as proxies to assess the evolution of the infodemic. [ABSTRACT FROM AUTHOR]

Introduction: This paper describes how mortality among hospitalised COVID-19 patients changed during the first three waves of the epidemic in Italy. Methods: This prospective cohort study used the Kaplan-Meier method to analyse the time-dependent probability of death of all of the patients admitted to a COVID-19 referral centre in Milan, Italy, during the three consecutive periods of: 21 February-31 July 2020 (first wave, W1), 1 August 2020–31 January 2021 (second wave, W2), and 1 February-30 April 2021 (third wave, W3). Cox models were used to examine the association between death and the period of admission after adjusting for age, biological sex, the time from symptom onset to admission, disease severity upon admission, obesity, and the comorbidity burden. Results: Of the 2,023 COVID-19 patients admitted to our hospital during the study period, 553 (27.3%) were admitted during W1, 838 (41.5%) during W2, and 632 (31.2%) during W3. The crude mortality rate during W1, W2 and W3 was respectively 21.3%, 23.7% and 15.8%. After adjusting for potential confounders, hospitalisation during W2 or W3 was independently associated with a significantly lower risk of death than hospitalisation during W1 (adjusted hazard ratios [AHRs]: 0.75, 95% confidence interval [CI] 0.59–0.95, and 0.58, 95% CI 0.44–0.77). Among the patients aged >75 years, there was no significant difference in the probability of death during the three waves (AHRs during W2 and W3 vs W1: 0.93, 95% CI 0.65–1.33, and 0.88, 95% CI 0.59–1.32), whereas those presenting with critical disease during W2 and W3 were at significantly lower risk of dying than those admitted during W1 (AHRs 0.61, 95% CI 0.43–0.88, and 0.44, 95% CI 0.28–0.70). Conclusions: Hospitalisation during W2 and W3 was associated with a reduced risk of COVID-19 death in comparison with W1, but there was no difference in survival probability in patients aged >75 years. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic is bringing disruptive effects on the healthcare systems, economy and social life of countries all over the world. Even though the elder portion of the population is the most severely affected by the COVID-19 disease, the counter-measures introduced so far by governments took into little account the age structure, with restrictions that act uniformly on the population irrespectively of age. In this paper, we introduce a SIRD model with age classes for studying the impact on the epidemic evolution of lockdown policies applied heterogeneously on the different age groups of the population. The proposed model is then applied to age-stratified COVID-19 Italian data. The simulation results suggest that control measures focused to specific age groups may bring benefits in terms of reduction of the overall mortality rate. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 epidemic in Italy has severely affected people aged more than 80, especially socially isolated. Aim of this paper is to assess whether a social and health program reduced mortality associated to the epidemic. Methods: An observational retrospective cohort analysis of deaths recorded among >80 years in three Italian cities has been carried out to compare death rate of the general population and "Long Live the Elderly!" (LLE) program. Parametric and non-parametric tests have been performed to assess differences of means between the two populations. A multivariable analysis to assess the impact of covariates on weekly mortality has been carried out by setting up a linear mixed model. Results: The total number of services delivered to the LLE population (including phone calls and home visits) was 34,528, 1 every 20 day per person on average, one every 15 days during March and April. From January to April 2019, the same population received one service every 41 days on average, without differences between January-February and March-April. The January-April 2020 cumulative crude death rate was 34.8‰ (9,718 deaths out of 279,249 individuals; CI95%: 34.1–35.5) and 28.9‰ (166 deaths out of 5,727 individuals; CI95%:24.7–33.7) for the general population and the LLE sample respectively. The general population weekly death rate increased after the 11th calendar week that was not the case among the LLE program participants (p<0.001). The Standardized Mortality Ratio was 0.83; (CI95%: 0.71–0.97). Mortality adjusted for age, gender, COVID-19 weekly incidence and prevalence of people living in nursing homes was lower in the LLE program than in the general population (p<0.001). Conclusions: LLE program is likely to limit mortality associated with COVID-19. Further studies are needed to establish whether it is due to the impact of social care that allows a better clients' adherence to the recommendations of physical distancing or to an improved surveillance of older adults that prevents negative outcomes associated with COVID-19. [ABSTRACT FROM AUTHOR]

European countries struggled to fight against the second and the third waves of the COVID-19 pandemic, as the Test-Trace-Isolate (TTI) strategy widely adopted over the summer and early fall 2020 failed to contain the spread of the disease effectively. This paper sheds light on the effectiveness of such a strategy in two European countries (Spain and Italy) by analysing data from June to December 2020, collected via a large-scale online citizen survey with 95,251 and 43,393 answers in Spain and Italy, respectively. Our analysis describes several weaknesses in each of the three pillars of the TTI strategy: Test, Trace, and Isolate. We find that 40% of respondents had to wait more than 48 hours to obtain coronavirus tests results, while literature has shown that a delay of more than one day might make tracing all cases inefficient. We also identify limitations in the manual contact tracing capabilities in both countries, as only 29% of respondents in close contact with a confirmed infected individual reported having been contact traced. Moreover, our analysis shows that more than 45% of respondents report being unable to self-isolate if needed. We also analyse the mitigation strategies deployed to contain the second wave of coronavirus. We find that these interventions were particularly effective in Italy, where close contacts were reduced by more than 20% in the general population. Finally, we analyse the participants' perceptions about the coronavirus risk associated with different daily activities. We observe that they are often gender- and age-dependent, and not aligned with the actual risk identified by the literature. This finding emphasises the importance of deploying public-health communication campaigns to debunk misconceptions about SARS-CoV-2. Overall, our work illustrates the value of online citizen surveys to quickly and efficiently collect large-scale population data to support and evaluate policy decisions to combat the spread of infectious diseases, such as coronavirus. [ABSTRACT FROM AUTHOR]

The global impact of coronavirus disease 2019 (COVID-19) is unprecedented, and many control and prevention measures have been implemented to test for and trace COVID-19. However, invisible-spreaders, who are associated with nucleic acid detection and asymptomatic infections, have received insufficient attention in the current COVID-19 control efforts. In this paper, we analyze the time series infection data for Italy, Germany, Brazil, India and Sweden since the first wave outbreak to address the following issues through a series of experiments. We conclude that: 1) As of June 1, 2020, the proportion of invisible-spreaders is close to 0.4% in Sweden, 0.8% in early Italy and Germany, and 0.4% in the middle and late stages. However, in Brazil and India, the proportion still shows a gradual upward trend; 2) During the spread of this pandemic, even a slight increase in the proportion of invisible-spreaders could have large implications for the health of the community; and 3) On resuming work, the pandemic intervention measures will be relaxed, and invisible-spreaders will cause a new round of outbreaks. [ABSTRACT FROM AUTHOR]

The dataset described in this paper contains daily data about COVID-19 cases that occurred in Italy over the period from Jan. 29, 2020 to October 15, 2021, divided into ten age classes of the population, the first class being 0–9 years, the tenth class being >90 years. The dataset contains eight columns, namely: date (day), age class, number of new cases, number of newly hospitalized patients, number of patients entering intensive care, number of deceased patients, number of recovered patients, number of active infected patients. This data has been officially released for research purposes by the Italian authority for COVID-19 epidemiologic surveillance (Istituto Superiore di Sanità – ISS), upon formal request by the authors, in accordance with the Ordonnance of the Chief of the Civil Protection Department n. 691 dated Aug. 4, 2020. A separate file contains the numerosity of the population in each age class, according to the National Institute of Statistics’ (ISTAT) data of the resident population of Italy as of Jan. 2020. This data has potential use, for instance, in epidemiologic studies of the effects of the COVID-19 contagion in Italy, in mortality analysis by age class, and in the development and testing of dynamical models of the contagion. [ABSTRACT FROM AUTHOR]

The three European countries included in the northwest littoral of the Mediterranean region – Italy, France and Spain – reported their first cases of the SARS-CoV-2 coronavirus early in 2020. The subsequent epidemic strongly impacted these countries, challenging the healthcare systems efficiency, and the capacity and transparency of their public statistics structures. Because public statistics were not fully adapted to such a new health situation, the available official data could not wholly describe the epidemic correctly. This paper developed an indicator derived from the prevalence of SARS-CoV-2 aiming to describe the time and spatial dynamics of the epidemic. Although the analysis was not applied to France due to the lack of data available, the comparative analysis among Spain and Italy highlighted some similarities and certain divergences, partially attributable to the features of each country‘s national demographic patterns and the peculiarities of applied health protocols. Finally, mortality during the first wave of the epidemic has been analysed for the three countries, demonstrating higher mortality index in Spain, although the reported number of SARS-CoV-2 declared deaths does not explain a portion of this mortality excess. [ABSTRACT FROM AUTHOR]

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]

Background: The novel coronavirus disease is an ongoing pandemic that started in China in December 2019. This paper is aimed at estimating the first two infections waves in Italy in relation to adopted health policies. Design and methods: We moved deaths of the Italian COVID-19 registry from recorded to infection date by the weighted moving average. We considered two infection fatality ratios related to the effective or saturated health system, we estimated the likely incidence curve from the resulting deaths and evaluated the curve shape before and after the national health policies. Results: From the 24th of February 2020 to the 7th of February 2021, we estimated 6,664,655 (4,639,221-9,325,138) cases distributed on two waves. Suitable daily infection fatality rates were 2.53% within the first wave and 1.15% within the second one. The first wave (February-July 2020) had its peak on the 14th of March 2020 (26,575). The second wave (August 2020-February 2021) was fatter with the peak on the 12th of November (60,425) and a hump in December before decreasing to 26,288 at the end. Adopted health policies were followed by changes in the curve rate. Conclusions: Tracing infection contacts and quarantining asymptomatic people reduced virus lethality in the second wave. Restriction on population mobility is effective within a suppression strategy, distance learning reduces contacts among families. Removal of restrictions should be implemented by sequential steps for avoiding a quick rising of incident cases. A reasonable public health daily goal to control both virus spread and lethality could be to find at least 87 cases for each death. [ABSTRACT FROM AUTHOR]

This paper investigates the heterogeneous impact of school closures during Covid-19 pandemic in Italy on academic performance across different schools, grades, subjects and groups of students. Our analysis utilises an innovative dataset that combines administrative data on standardised tests in grades 5 and 8 with a specifically-designed survey that collects information about teachers' practices between February and June 2020. Firstly, by employing a multilevel (mixed-effects) model, we estimate the extent of learning loss and examine its variability across schools, for students in primary and middle levels during the school year 2020/21. The findings confirm that learning loss has been considerable (between 0.05 and 0.27 SD) although heterogeneity across disciplines and grades exists – higher in English in grade 5, and in mathematics and reading in grade 8. Secondly, as a main contribution of the paper, we explore the mechanisms behind the substantial differences observed across schools, which can be explained by the ability of teachers in using digital tools and evaluating their students, as well as by the leadership role exerted by school principals. [ABSTRACT FROM AUTHOR]

Introduction: This paper aims to measure the performance of early detection methods, which are usually used for infectious diseases. Methodology: By using real data of confirmed Coronavirus cases from the Kingdom of Saudi Arabia and Italy, the moving epidemic method (MEM) and the moving average cumulative sums (Mov. Avg Cusum) methods are used in our simulation study. Results: Our results suggested that the CUSUM method outperforms the MEM in detecting the start of the Coronavirus outbreak. [ABSTRACT FROM AUTHOR]

In this paper, we present a new family of continuous distributions known as the type I half logistic Burr X-G. The proposed family's essential mathematical properties, such as quantile function (QuFu), moments (Mo), incomplete moments (InMo), mean deviation (MeD), Lorenz (Lo) and Bonferroni (Bo) curves, and entropy (En), are provided. Special models of the family are presented, including type I half logistic Burr X-Lomax, type I half logistic Burr X-Rayleigh, and type I half logistic Burr X-exponential. The maximum likelihood (MLL) and Bayesian techniques are utilized to produce parameter estimators for the recommended family using type II censored data. Monte Carlo simulation is used to evaluate the accuracy of estimates for one of the family's special models. The COVID-19 real datasets from Italy, Canada, and Belgium are analysed to demonstrate the significance and flexibility of some new distributions from the family. [ABSTRACT FROM AUTHOR]

Notable cross-country differences exist in the diffusion of the Covid-19 and in its lethality. Contact patterns in populations, and in particular intergenerational contacts, have been argued to be responsible for the most vulnerable, the elderly, getting infected more often and thus driving up mortality in some context, like in the southern European one. This paper asks a simple question: is it between whom contacts occur that matters or is it simply how many contacts people have? Due to the high number of confounding factors, it is extremely difficult to empirically assess the impact of single network features separately. This is why we rely on a simulation exercise in which we counterfactually manipulate single aspects of countries' age distribution and network structures. We disentangle the contributions of the kind and of the number of contacts while holding constant the age structure. More precisely, we isolate the respective effects of inter-age contact patterns, degree distribution and clustering on the virus propagation across age groups. We use survey data on face-to-face contacts for Great Britain, Italy, and Germany, to reconstruct networks that mirror empirical contact patterns in these three countries. It turns out that the number of social contacts (degree distribution) largely accounts for the higher infection rates of the elderly in the Italian context, while differences in inter-age contacts patterns are only responsible for minor differences. This suggests that policies specifically targeting inter-age contacts would be little effective. [ABSTRACT FROM AUTHOR]

While many efforts are currently devoted to vaccines development and administration, social distancing measures, including severe restrictions such as lockdowns, remain fundamental tools to contain the spread of COVID-19. A crucial point for any government is to understand, on the basis of the epidemic curve, the right temporal instant to set up a lockdown and then to remove it. Different strategies are being adopted with distinct shades of intensity. USA and Europe tend to introduce restrictions of considerable temporal length. They vary in time: a severe lockdown may be reached and then gradually relaxed. An interesting alternative is the Australian model where short and sharp responses have repeatedly tackled the virus and allowed people a return to near normalcy. After a few positive cases are detected, a lockdown is immediately set. In this paper we show that the Australian model can be generalized and given a rigorous mathematical analysis, casting strategies of the type short-term pain for collective gain in the context of sliding-mode control , an important branch of nonlinear control theory. This allows us to gain important insights regarding how to implement short-term lockdowns, obtaining a better understanding of their merits and possible limitations. Effects of vaccines administration in improving the control law's effectiveness are also illustrated. Our model predicts the duration of the severe lockdown to be set to maintain e.g. the number of people in intensive care under a certain threshold. After tuning our strategy exploiting data collected in Italy, it turns out that COVID-19 epidemic could be e.g. controlled by alternating one or two weeks of complete lockdown with one or two months of freedom, respectively. Control strategies of this kind, where the lockdown's duration is well circumscribed, could be important also to alleviate coronavirus impact on economy. [ABSTRACT FROM AUTHOR]

This paper considers the pattens of international collaboration by analysing publications on COVID‐19 published in the first 6 months of the pandemic. The data set comprised articles on COVID‐19 indexed in the Web of Science Core Collection (WoS CC) downloaded four times between 1 April 2020 and 1 June 2020. The analysis of 5,827 documents revealed that 128 countries, 23,127 authors, and 6,349 institutes published on the pandemic. The data reveal that the three main publishing countries were the USA, China, and England with Italy closely following. Although publication was widely spread, most of the institutions with the highest volume of output were in China. Network analysis showed growth in international cooperation with an average degree of country/region cooperation rising to 23.06 by 1 June. There was also a clear core‐periphery structure to international collaboration. Institutional collaboration was shown to be highly regionalized. The data reveal a high and growing incidence of international collaboration on the pandemic. [ABSTRACT FROM AUTHOR]

The study discusses the potential of e-Pharmacies and the new digital skills of pharmacists in the aftermath of the Sars-Cov2 pandemic. From this perspective, a sociological analysis of the digital role-set of pharmacists is developed, in order to highlight the opportunities and risks of the spreading of online pharmacies and their potential contribution to the delivery of new digital services for addressin Covid-19. The paper ends with some considerations on the importance of the sociological studies of "e-pharmacy encounters" in the current phase of Covid Age in Italy. [ABSTRACT FROM AUTHOR]

This paper aims to predict the economic resilience to crises of territories based on local pre-existing socioeconomic characteristics. Specifically, we consider the case of Italian municipalities during the first wave of the COVID-19 pandemic, leveraging a large-scale dataset of cardholders performing transactions in Point-of-Sales. Based on a set of machine learning classifiers, we show that network-based measures and variables related to the social, economic, demographic and environmental dimensions are relevant predictors of the economic resilience of Italian municipalities to the crisis. In particular, we find accurate classification performance both in balanced and un-balanced scenarios, as well as in the case we restrict the analysis to specific geographical areas. Our analysis predicts that territories with larger income per capita, soil consumption, concentration of real estate activities and commuting network centrality in terms of closeness and Pagerank constitute the set of most affected areas, experiencing the strongest reduction of economic activities during the COVID-19 pandemic. Overall, we provide an application of an early-warning system able to provide timely evidence to policymakers about the detrimental effects generated by natural disasters and severe crisis episodes, thus contributing to optimize public decision support systems. • We quantify economic resilience of Italian municipalities through bank transaction data. • We model territories with a set of socioeconomic and network-based covariates. • Machine learning classifiers accurately predict economic resilience. • We use SHAP values to identify most relevant predictors. [ABSTRACT FROM AUTHOR]

The author comments on a research paper on the prevalence, incidence and mortality of delirium in the COVID-19 disease, which references a study by S. C. Shao et al., published in a 2021 issue of "Age Ageing". Topics discussed include the characteristics of delirium, the challenges facing health professionals in managing delirium in patients with COVID-19, findings on its prevalence on admission and during hospitalization, and the study's implications for care for patients with delirium.

2019 Coronavirus disease (COVID-19) had a big impact in Italy, mainly concentrated in the northern part of the Country. All this was mainly due to similarities of this area with Wuhan in Hubei Province, according to geographical, environmental and socio-economic points of view. The basic hypothesis of this research was that the presence of atmospheric pollutants can generate stress on health conditions of the population and determine pre-conditions for the development of diseases of the respiratory system and complications related to them. In most cases the attention on environmental aspects is mainly concentrated on pollution, neglecting issues such as land management which, in some way, can contribute to reducing the impact of pollution. The reduction of land take and the decrease in the loss of ecosystem services can represent an important aspect in improving environmental quality. In order to integrate policies for environmental change and human health, the main factors analyzed in this paper can be summarized in environmental, climatic and land management. The main aim of this paper was to produce three different hazard scenarios respectively related to environmental, climatic and land management-related factors. A Spatial Analytical Hierarchy Process (AHP) method has been applied over thirteen informative layers grouped in aggregation classes of environmental, climatic and land management. The results of the health hazard maps show a disparity in the distribution of territorial responses to the pandemic in Italy. The environmental components play an extremely relevant role in the definition of the red zones of hazard, with a consequent urgent need to renew sustainable development strategies. The comparison of hazard maps related to different scenarios provides decision makers with tools to orient policy choices with a different degree of priority according to a place-based approach. In particular, the geospatial representation of risks could be a tool for legitimizing the measures chosen by decision-makers, proposing a renewed approach that highlights and takes account of the differences between the spatial contexts to be considered - Regions, Provinces, Municipalities - also in terms of climatic and environmental variables. • COVID-19 had a big impact in Italy, mainly in the northern part of the Country. • Reduction of land take and ecosystem services' loss improve environmental quality. • Environmental, climatic and land management can be leveraged for pandemic policies. • Geospatial representation of risks is a useful approach to support decision-makers. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic, caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), still remains a severe threat. At the time of writing this paper, the second infectious wave has caused more than 280,000 deaths all over the world. Italy was one of the first countries involved, with more than 200,000 people reported as infected and 30,000 deaths. There are no specific treatments for COVID-19 and the vaccine still remains somehow inconclusive. The world health community is trying to define and share therapeutic protocols in early and advanced clinical stages. However, numbers remain critical with a serious disease rate of 14%, ending with sepsis, acute respiratory distress syndrome (ARDS), multiple organ failure (MOF) and vascular and thromboembolic findings. The mortality rate was estimated within 2–3%, and more than double that for individuals over 65 years old; almost one patient in three dies in the Intensive Care Unit (ICU). Efforts for effective solutions are underway with multiple lines of investigations, and health authorities have reported success treating infected patients with donated plasma from survivors of the illness, the proposed benefit being protective antibodies formed by the survivors. Plasma transfusion, blood and stem cells, either autologous or allograft transplantation, are not novel therapies, and in this short paper, we propose therapeutic autologous plasma and peripheral blood stem cells as a possible treatment for fulminant COVID-19 infection. [ABSTRACT FROM AUTHOR]

Introduction: An infection by COVID-19 triggers a dangerous cytokine storm, so tocilizumab has been introduced in Italy as an agent blocking the cytokine storm. This paper aims to describe the one-year survival of ICU patients treated with tocilizumab. Methods: This observational study enrolled all patients confirmed to be infected by COVID-19 who were admitted to the ICU in our center. We offered tocilizumab to all non-septic patients if they did not present any contraindications. Results: We enrolled 68 ICU patients in our center on 72 occasions during the enrollment period; we excluded four patients due to study criteria. The one-year mortality hazard ratio of treated patients was 0.64, with a confidence interval of 0.31 to 1.19, with p = 0.169. Among the survivors, 32 of 35 patients answered the phone interview (14 patients in the treated group and 18 in the untreated group); overall, the effect of COVID-19 on quality of life was 58.14%. These effects were lower in the tocilizumab group, with p = 0.016 *. Conclusions: Our observational data follow the most relevant largest trial. Patients treated with tocilizumab had lower rates of new-onset symptoms later COVID-19 ICU hospitalizations. As reported by recent medical literature, the presence of these symptoms suggests that a follow-up program for these types of patients could be useful. [ABSTRACT FROM AUTHOR]

This paper investigates the spatio-temporal spread pattern of COVID-19 in Italy, during the first wave of infections, from February to October 2020. Disease mappings of the virus infections by using the Besag–York–Mollié model and some spatio-temporal extensions are provided. This modeling framework, which includes a temporal component, allows the studying of the time evolution of the spread pattern among the 107 Italian provinces. The focus is on the effect of citizens' mobility patterns, represented here by the three distinct phases of the Italian virus first wave, identified by the Italian government, also characterized by the lockdown period. Results show the effectiveness of the lockdown action and an inhomogeneous spatial trend that characterizes the virus spread during the first wave. Furthermore, the results suggest that the temporal evolution of each province's cases is independent of the temporal evolution of the other ones, meaning that the contagions and temporal trend may be caused by some province-specific aspects rather than by the subjects' spatial movements. [ABSTRACT FROM AUTHOR]

• Two-phase training algorithm able to boost the Machine Learning accuracy. • Accurate bankruptcy prediction up to 60 months by a Machine Learning algorithm. • Integration of the Machine Learning algorithm in a DSS for policy making. • Test of the DSS on the Italian SMEs, with a focus on the COVID-19 effects. In the field of detection and prediction of company defaults and bankruptcy, significant effort has been devoted to evaluating financial ratios as predictors using statistical models and machine learning techniques. This problem becomes crucially important when financial decision-makers are provided with predictions on which to act, based on the output of prediction models. However, research has shown that such predictors are sufficiently accurate in the short-term, with the focus mainly directed towards large and medium-large companies. In contrast, in this paper, we focus on mid- and long-term bankruptcy prediction (up to 60 months) targeting small and/or medium enterprises. The key contribution of this study is a substantial improvement of the prediction accuracy in the short-term (12 months) using machine learning techniques, compared to the state-of-the-art, while also making accurate mid- and long-term predictions (measure of the area under the ROC curve of 0.88 with a 60 month prediction horizon). Extensive computational tests on the entire set of companies in Italy highlight the efficiency and accuracy of the developed method, as well as demonstrating the possibility of using it as a tool for the development of strategies and policies for entire economic systems. Considering the recent COVID-19 pandemic, we show how our method can be used as a viable tool for large-scale policy-making. [ABSTRACT FROM AUTHOR]