Factor structure and psychometric proprieties of the COVID-19 prevention behaviours (COV19-PB) scale.

We sought to test the COVID19-PB scale's psychometric properties and its dimensionality in a sample composed of 1107 Italian adults aged from 18 to 80 years (M = 39.59; SD = 16.36), 75% (n = 830) females, and 25% (n = 277) males. Exploratory, Confirmatory factor analysis and parallel analysis were used to validate the instrument that resulted from the Ebola Virus protective behaviours scale adaptation. Fear of covid-19 and a 1-item level of adherence to the Covid-19 protection scale were used to test the measure's convergent validity. A four-factor structure emerged from exploratory and confirmatory factor analysis: direct avoidance, avoidance of public spaces, avoidance of social interaction, and talking about the virus as protection. COVID-19 PB was a valuable measure to assess individuals' competencies in assuming correct behaviours during the pandemic.

Comparing Emotion and Sentiment Analysis Tools on Italian anti-vaccination for COVID-19 posts

Since the beginning of the vaccination campaign against Covid-19 in our country, resistance to vaccination has emerged on the part of a not negligible portion of the Italian population. Emotions (such as sadness, fear, etc.) and the polarity (positive/negative) of an opinion published on social media are essential for analyzing people's position towards a topic. For this reason, we applied two Natural Language Processing tools, FEEL-IT and SentIta, to a few thousands of social networks posts against the COVID-19 vaccine or specifically the booster shot. We find out some significant insights about the prevalent emotions among users and propose to combine the outputs of the tools in order to increase the classification performance of an opinion according to three possible sentiments (positive/neutral/negative). © 2022 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

From the First to the Second Wave of COVID-19: Anxiety, De-Pressive, and Post-Traumatic Stress Symptoms in the Italian Population.

In the early stages of the COVID-19 outbreak, high rates of clinically relevant anxiety, depression, and post-traumatic stress symptoms (PTSS) have been reported in the Italian population. The persistence of the pandemic and related restrictive measures highlight the need for a reassessment of psychopathological symptoms. The present longitudinal study consisted of two evaluations conducted during the two waves of infection. Participants were asked to complete the State-Trait Anxiety Inventory-Form Y1 (STAI Y1), the Beck Depression Inventory (BDI-II), and the PTSD Checklist for DSM-5 (PCL-5). There were no significant differences in depressive symptoms and PTSS scores reported by participants between T0 and T1, with single-case analysis revealing that in 71% and 69% of the participants, depressive symptoms and PTSS symptoms, respectively, remained stable during this period. On the contrary, mean scores comparison showed a significant decrease in anxiety levels, with 19% of participants in whom anxiety symptoms improved at single-case analysis. Taken together, these results suggest that depressive symptoms and PTSS not only occurred in a high percentage of participants but also tended to remain stable over time, thus warranting the importance of large-scale psychological screening and interventions to prevent the chronicization of these symptoms and their evolution to psychopathological disorders.

Burden of COVID-19 and Vaccination Coverage in the Italian Population as of October 2021.

Following the pandemic scenario, researchers from all over the world, including Italians, have undertaken fervent research activity using the epidemiological data available on the sites of government and national and international research institutes. The objectives of our study were: (1) to analyze the load and trend of the COVID-19 pandemic in Italy, from the beginning to October 2021; (2) to analyze vaccination coverage by age groups and types of vaccines administered and check how the vaccination campaign has influenced the course of the disease and deaths; (3) to evaluate the Italian situation in the European context, comparing the incidence and mortality of Italy with respect to European countries; (4) finally, to evaluate how much vaccination coverage may have had an effect on mortality in the various European countries. Databases were structured to archive Italian and European COVID-19 data provided by Our World in Data, and data came from the Ministry of Health, to evaluate percentage of vaccines administered. The monthly trend of the cumulative incidence per 100,000 inhabitants in the period January 2020-October 2021 was evaluated. It is important to underline 3 peaks of incidence and mortality rates that occurred during the three waves of COVID-19: March-April-May 2020, October-November-December 2020, and March-April-May 2021. There is a slight increase in incidence in August 2021 and in mortality in September 2021. The three mortality rate peaks, related to the three waves of COVID-19, are always higher in Italy than in Europe, particularly in April 2020, December 2020, and March 2021. From May 2021 to October 2021, the mortality trend reversed, and it turned out to be higher in Europe than in Italy. Regarding vaccination, Italy currently has an important coverage, not only in the most fragile population, where it exceeds 90%, but also in the 12-19 age group, with percentages above 65%. The Pfizer/BioNTech vaccine was used widely in all age groups (first and second dose), with highest administration in 12-19 age groups and 80+, while the lowest was recorded in the 70-79 age group. In conclusion, these data confirm the importance of vaccination in the management of the COVID-19 pandemic.

Studying citizens' trust to monitor measures acceptance during covid-19 pandemic

Over the last year, the COVID-19 pandemic has strongly affected everyone's lives. An unprecedented situation, which required enormous sacrifices and very stringent limitations. Within this context, trust has played a crucial role: People decided to trust their institutions to tackle the pandemic and that trust made the strong restrictive measures effective. This work aims to study the response of the Italian population to the early stages of the pandemic. Making use of a survey addressed to 4260 Italian citizens, we realized an agent-based simulation to model and analyze citizen trust starting from its main cognitive sub-components, with particular reference to the dimensions of competence and willingness. The results of this work can be of great interest, both for understanding what happened in the past, but also for designing effective strategies in the future. © 2021 CEUR-WS. All rights reserved.

Differential mortality of infectious disease in Italian polities: COVID-19, past plague epidemics, and currently endemic respiratory disease.

Coronavirus disease 2019 (COVID-19) has harshly impacted Italy since its arrival in February 2020. In particular, provinces in Italy's Central and Northern macroregions have dealt with disproportionately greater case prevalence and mortality rates than those in the South. In this paper, we compare the morbidity and mortality dynamics of 16th and 17th century Plague outbreaks with those of the ongoing COVID-19 pandemic across Italian regions. We also include data on infectious respiratory diseases which are presently endemic to Italy in order to analyze the regional differences between epidemic and endemic disease. A Growth Curve Analysis allowed for the estimation of time-related intercepts and slopes across the 16th and 17th centuries. Those statistical parameters were later incorporated as criterion variables in multiple General Linear Models. These statistical examinations determined that the Northern macroregion had a higher intercept than the Southern macroregion. This indicated that provinces located in Northern Italy had historically experienced higher plague mortalities than Southern polities. The analyses also revealed that this geographical differential in morbidity and mortality persists to this day, as the Northern macroregion has experienced a substantially higher COVID-19 mortality than the Southern macroregion. These results are consistent with previously published analyses. The only other stable and significant predictor of epidemic disease mortality was foreign urban potential, a measure of the degree of interconnectedness between 16th and 17th century Italian cities. Foreign urban potential was negatively associated with plague slope and positively associated with plague intercept, COVID-19 mortality, GDP per capita, and immigration per capita. Its substantial contribution in predicting both past and present outcomes provides a temporal continuity not seen in any other measure tested here. Overall, this study provides compelling evidence that temporally stable geographical factors, impacting both historical and current foreign pathogen spread above and beyond other hypothesized predictors, underlie the disproportionate impact COVID-19 has had throughout Central and Northern Italian provinces.

Second wave of COVID-19 in Italy: Preliminary estimation of reproduction number and cumulative case projections.

The second wave of a novel coronavirus in Italy has caused 247,369 new cases and 1782 deaths only in October 2020. This significantly alarming infectious disease controlling board to impose again mitigation measures for controlling the epidemic growth. In this paper, we estimate the latest COVID-19 reproduction number (R_0) and project the epidemic size for the future 45 days. The R_0 value has calculated as 2.83 (95% CI: 1.5-4.2) and the cumulative incidences 100,015 (95% CI; 73,201-100,352), and daily incidences might be reached up to 15,012 (95% CI: 8234-16,197) respectively.

COVID-19 virus outbreak forecasting of registered and recovered cases after sixty day lockdown in Italy: A data driven model approach.

BACKGROUND: Till 31 March 2020, 105,792 COVID-19 cases were confirmed in Italy including 15,726 deaths which explains how worst the epidemic has affected the country. After the announcement of lockdown in Italy on 9 March 2020, situation was becoming stable since last days of March. In view of this, it is important to forecast the COVID-19 evaluation of Italy condition and the possible effects, if this lock down could continue for another 60 days. METHODS: COVID-19 infected patient data has extracted from the Italian Health Ministry website includes registered and recovered cases from mid February to end March. Adoption of seasonal ARIMA forecasting package with R statistical model was done. RESULTS: Predictions were done with 93.75% of accuracy for registered case models and 84.4% of accuracy for recovered case models. The forecasting of infected patients could be reach the value of 182,757, and recovered cases could be registered value of 81,635 at end of May. CONCLUSIONS: This study highlights the importance of country lockdown and self isolation in control the disease transmissibility among Italian population through data driven model analysis. Our findings suggest that nearly 35% decrement of registered cases and 66% growth of recovered cases will be possible.