After entering Italy, the coronavirus (COVID-19) spread fast. The strict lockdown implemented by the government during the Spring 2020 helped to slow down the outbreak. However, the country had to face four new harsh waves of contagion. As of January 1, 2025, the total number of cases reported by the authorities reached over 26.9 million. The north of the country was mostly hit, and the region with the highest number of cases was Lombardy, which registered almost 4.4 million of them. The north-eastern region of Veneto and the southern region of Campania followed in the list. When adjusting these figures for the population size of each region, however, the picture changed, with the region of Veneto being the area where the virus had the highest relative incidence. Coronavirus in Italy Italy has been among the countries most impacted by the coronavirus outbreak. Moreover, the number of deaths due to coronavirus recorded in Italy is significantly high, making it one of the countries with the highest fatality rates worldwide, especially in the first stages of the pandemic. In particular, a very high mortality rate was recorded among patients aged 80 years or older. Impact on the economy The lockdown imposed during the Spring 2020, and other measures taken in the following months to contain the pandemic, forced many businesses to shut their doors and caused industrial production to slow down significantly. As a result, consumption fell, with the sectors most severely hit being hospitality and tourism, air transport, and automotive. Several predictions about the evolution of the global economy were published at the beginning of the pandemic, based on different scenarios about the development of the pandemic. According to the official results, it appeared that the coronavirus outbreak had caused Italy’s GDP to shrink by approximately nine percent in 2020.

The first two cases of the new coronavirus (COVID-19) in Italy were recorded between the end of January and the beginning of February 2020. Since then, the number of cases in Italy increased steadily, reaching over 26.9 million as of January 8, 2025. The region mostly hit by the virus in the country was Lombardy, counting almost 4.4 million cases. On January 11, 2022, 220,532 new cases were registered, which represented the biggest daily increase in cases in Italy since the start of the pandemic. The virus originated in Wuhan, a Chinese city populated by millions and located in the province of Hubei. More statistics and facts about the virus in Italy are available here.For a global overview, visit Statista's webpage exclusively dedicated to coronavirus, its development, and its impact.

Temporal parameters of the outbreak in Italy and corresponding temporal parameters in the model.

Identifying changes in the reproduction number, rate of spread, and doubling time during the course of the COVID-19 outbreak whilst accounting for potential biases due to delays in case reporting both nationally and subnationally in Italy. These results are impacted by changes in testing effort, increases and decreases in testing effort will increase and decrease reproduction number estimates respectively.

The coronavirus (COVID-19) outbreak caused massive troubles in Italy. As the graph shows, the spread of the virus put hospitals and medical staff under a lot of pressure. As of January 8, 2025, approximately 1,300 patients were hospitalized in Italy because of COVID-19. The highest figure since the start of the pandemic was registered on November 23, 2020, when 34,697 individuals were being treated in hospitals for COVID-19-related reasons. The resilience of the Italian healthcare system and the limited capacity of hospitals were among the most challenging issues facing authorities. In the last months, however, the country saw the end of this terrible situation: as of November 2023, roughly 85 percent of the total Italian population was fully vaccinated. For a global overview, visit Statista's webpage exclusively dedicated to coronavirus, its development, and its impact.

Analysis of ‘COVID-19 in Italy’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/sudalairajkumar/covid19-in-italy on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Context

Coronaviruses are a large family of viruses which may cause illness in animals or humans. In humans, several coronaviruses are known to cause respiratory infections ranging from the common cold to more severe diseases such as Middle East Respiratory Syndrome (MERS) and Severe Acute Respiratory Syndrome (SARS). The most recently discovered coronavirus causes coronavirus disease COVID-19 - WHO

People can catch COVID-19 from others who have the virus. This has been spreading rapidly around the world and Italy is one of the most affected country.

On March 8, 2020 - Italy’s prime minister announced a sweeping coronavirus quarantine early Sunday, restricting the movements of about a quarter of the country’s population in a bid to limit contagions at the epicenter of Europe’s outbreak. - TIME

Content

This dataset is from https://github.com/pcm-dpc/COVID-19 collected by Sito del Dipartimento della Protezione Civile - Emergenza Coronavirus: la risposta nazionale

This dataset has two files

• covid19_italy_province.csv - Province level data of COVID-19 cases
• covid_italy_region.csv - Region level data of COVID-19 cases

Acknowledgements

Data is collected by Sito del Dipartimento della Protezione Civile - Emergenza Coronavirus: la risposta nazionale and is uploaded into this github repo.

Dashboard on the data can be seen here. Picture courtesy is from the dashboard.

Inspiration

Insights on * Spread to various regions over time * Try to predict the spread of COVID-19 ahead of time to take preventive measures

--- Original source retains full ownership of the source dataset ---

During COVID-19 emergency the majority of health structures in Europe saturated or nearly saturated their structural availabilities already in the first weeks of the epidemic period especially in some regions of Italy and Spain. The aim of this study is to analyse the efficiency in the management of hospital beds before the COVID-19 outbreak at regional level in France, Germany, Italy and Spain. This analysis can indicate a reference point for future analysis on resource management in emergency periods and help hospital managers, emergency planners as well as policy makers to put in place a rapid and effective response to an emergency situation. The results of this study clearly underline that France and Germany could rely on the robust structural components of the hospital system, compared to Italy and Spain. Presumably, this might have an impact on the efficacy in the management of the COVID-19 diffusion. In particular, the high availability of beds in the majority of the France regions paired with by the low occupancy rate and high turnover interval led these regions to have a high number of available beds. Consider also that this country generally manages complex cases. A similar structural component is present in the German regions where the number of available beds is significantly higher than in the other countries. The impact of the COVID-19 was completely different in Italy and Spain that had to deal with a relevant large number of patients relying on a reduced number of both hospital beds and professionals. A further critical factor compared to France and Germany concerns the dissimilar distribution of cases across regions. Even if in these countries the hospital beds were efficiently managed, the concentration of hospitalized patients and the scarcity of beds have put pressure on the hospital systems.

Italy went through five coronavirus waves during the pandemic. As of January 8, 2025, the number of active coronavirus cases in the country was equal to approximately 203,305. On January 23, 2022, there were 2,734,906 active infections in Italy, the highest figure since the start of the pandemic. Furthermore, the total number of cases (including active cases, recoveries, and deaths) in Italy reached 26.9 million, with the region mostly hit by the virus in the country being Lombardy. Despite this notably high number of infections, deaths and hospitalizations remain rather low, thanks to a very high vaccination rate. The virus originated in Wuhan, a Chinese city populated by millions and located in the province of Hubei. More statistics and facts about the virus in Italy are available here.For a global overview, visit Statista's webpage exclusively dedicated to coronavirus, its development, and its impact.

In Italy, the epidemiological surveillance of West Nile virus (WNV) infections in humans is regulated by the “National prevention, surveillance and response plan for arboviral diseases (PNA) 2020-2025“. The document integrates veterinary (animal and entomological) surveillance of West Nile virus (WNV) - essential for risk estimation - and human cases into a single plan.

Surveillance of imported and local human infections is carried out all year round throughout the country, and between early May and late November in Regions where an endemic area has been identified. In these areas the surveillance of human cases must be strengthened and special attention must be paid to the diagnosis of WNV disease in the population. The reporting system also collects positivities for WNV detected in donors of blood, blood derivatives and organs, tissues and cells, with a view to the application of specific preventive measures and any febrile clinical forms found in the country.

Human surveillance is coordinated at national level by the Istituto Superiore di Sanità (ISS) and the Ministry of Health, which transmits the data to the European Commission and the ECDC. The Regions, in full autonomy, define the regulatory-programmatic documents for epidemiological and laboratory surveillance on their territory and transmit the data to the ISS and the Ministry. The Department of Infectious Diseases of the Istituto Superiore di Sanità, with the coordination of Office V of the Directorate General for Prevention of the Ministry of Health and in collaboration with the Centre for the Study of Exotic Diseases (Cesme) of the Experimental Zooprophylactic Institute of Abruzzo and Molise 'Giuseppe Caporale' (IZS Teramo), publishes the data of the surveillance system in a periodical bulletin.

In order to inform citizens and make the collected data available, which is only useful for communication and information purposes, the following information is made available under the CC-BY-4.0 licence

• National evolution data
• Regional data
• Provincial data
• Summary bulletins

The complete list of bulletins is available at the following link: https://www.epicentro.iss.it/westnile/bollettino

Italy is one of the first European epicenters of the COVID-19 pandemic. In attempts to hinder the spread of the novel coronavirus disease, Italian government hardened protective measures, from quarantine to lockdown, impacting millions of lives dramatically. Amongst the enacted restrictions, all non-essential activities were prohibited as well as all outdoor activities banned. However, at the first spur of the outbreak, for about a dozen of days, physical and sports activities were permitted, while maintaining social distancing. In this timeframe, by administering measures coming from self-determination theory and theory of planned behavior and anxiety state, in an integrated approach, we investigated the prevalence of these activities by testing, via a Structural Equation Model, the influence of such psychosocial variables on the intention to preserve physical fitness during the healthcare emergency. Through an adequate fit of the hypothesized model and a multi-group analysis, we compared the most COVID-19 hit Italian region – Lombardy – to the rest of Italy, finding that anxiety was significantly higher in the Lombardy region than the rest of the country. In addition, anxiety negatively influenced the intention to do physical activity. Giving the potential deleterious effects of physical inactivity due to personal restrictions, these data may increase preparedness of public health measures and attractiveness of recommendations, including on the beneficial effects of exercise, under circumstances of social distancing to control an outbreak of a novel infectious disease.

The dataset reports the data collected in the Italian Ministry of Health website regarding the availability of hospital beds as well as the number of discharges and inpatient days. Data are distributed by hospital structure, year (2010 and 2017) and discipline. Additional sheets are included to report the hospital bed management indicators computed to assess the efficiency in the ordinary hospital bed management in Italy before the COVID-19 outbreak.

Last available raw data published by the Ministry of Health are available here: http://www.salute.gov.it/portale/documentazione/p6_2_8_1_1.jsp?lingua=italiano&id=6

Italy is one of the first European epicenters of the COVID-19 pandemic. In attempts to hinder the spread of the novel coronavirus disease, Italian government hardened protective measures, from quarantine to lockdown, impacting millions of lives dramatically. Amongst the enacted restrictions, all non-essential activities were prohibited as well as all outdoor activities banned. However, at the first spur of the outbreak, for about a dozen of days, physical and sports activities were permitted, while maintaining social distancing. In this timeframe, by administering measures coming from self-determination theory and theory of planned behavior and anxiety state, in an integrated approach, we investigated the prevalence of these activities by testing, via a Structural Equation Model, the influence of such psychosocial variables on the intention to preserve physical fitness during the healthcare emergency. Through an adequate fit of the hypothesized model and a multi-group analysis, we compared the most COVID-19 hit Italian region – Lombardy – to the rest of Italy, finding that anxiety was significantly higher in the Lombardy region than the rest of the country. In addition, anxiety negatively influenced the intention to do physical activity. Giving the potential deleterious effects of physical inactivity due to personal restrictions, these data may increase preparedness of public health measures and attractiveness of recommendations, including on the beneficial effects of exercise, under circumstances of social distancing to control an outbreak of a novel infectious disease.

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BackgroundThe COVID-19 pandemic has profoundly impacted societies, influencing countries' Health Emergency and Disaster Risk Management (H-EDRM) systems. By taking Italy as a case study, this research aimed to investigate the response to the COVID-19 pandemic, focusing on the changes made to the existing H-EDRM system, with an emphasis on human resources, health service delivery, and logistics and the forward-looking strategies for the next health emergencies and disasters.MethodsWe performed a retrospective observational case study using qualitative methodology. Data was collected via semi-structured interviews and analyzed considering the World Health Organization (WHO) H-EDRM framework. Multiple interviewees were selected to obtain a holistic perspective on the Italian response to COVID-19. Stakeholders from five different sectors (policy-making, hospital, primary care, third sector, lay community) from three of the most impacted Italian regions (Piemonte, Lombardia, and Veneto) were interviewed, for a total of 15 respondents.ResultsResults on human resources revolved around the following main themes: personnel, training, occupational health, and multidisciplinary work; results on health service delivery encompassed the following main themes: public health, hospital, and primary care systems; results on logistics dealt with the following themes: infrastructures, supplies, transports, and communication channels. Lessons learned stressed on the importance of considering pragmatic disaster preparedness strategies and the need for cultural and structural reforms. Stakeholders mentioned several implications for the post-pandemic H-EDRM system in Italy.ConclusionsFindings highlight that the interconnection of sectors is key in overcoming pandemic-related challenges and for future disaster preparedness. The implications for the Italian H-EDRM system can inform advancements in disaster management in Italy and beyond.

Analysis of ‘SARS-CoV-2 ITALY (UPDATED!) ’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/snocco/sarscov2-italy-updated on 28 January 2022.

--- Dataset description provided by original source is as follows ---

Context

I want to share with you the dataset concerning the COVID-19 pandemic, updated day by day, so that I can offer you an in-depth logical and graphic analysis on the evolution of the pandemic in Italy.

Content

Inside there are 3 datasets: - covidAndamentoNazionale.csv - covidAndamentoRegionale.csv - covidAndamentoProviciale.csv

Acknowledgements

Thanks to all those who work at all levels to fight this pandemic. And... Thanks to Umberto Rosini for making this data available

Inspiration

I enjoy data analytics and I love sharing my passion with other people. Also, I always like to learn, and so I thank you for the comparison.

--- Original source retains full ownership of the source dataset ---

Data on cases of COVID per day as provided by ECDC were trimmed off other countries except China and Italy. (XLSX)

As of January 1, 2025, the number of active coronavirus (COVID-19) infections in Italy was approximately 218,000. Among these, 42 infected individuals were being treated in intensive care units. Another 1,332 individuals infected with the coronavirus were hospitalized with symptoms, while approximately 217,000 thousand were in isolation at home. The total number of coronavirus cases in Italy reached over 26.9 million (including active cases, individuals who recovered, and individuals who died) as of the same date. The region mostly hit by the spread of the virus was Lombardy, which counted almost 4.4 million cases.For a global overview, visit Statista's webpage exclusively dedicated to coronavirus, its development, and its impact.

Forward stepwise linear regression.

We developed a model that tries to describe the dynamics of the spread of a disease among a population, in particular the progress of infected active cases. The model is then applied to describe Italy CoViD-19 outbreak and subsequently, we tried to predict possible scenarios.

Objectives: One of the largest clusters of Covid-19 infections was observed in Italy. The population was forced to home confinement, exposing individuals to increased risk for insomnia, which is, in turn, associated with depression and anxiety. Through a cross-sectional online survey targeting all Italian adult population (≥18 yrs), insomnia prevalence and its interactions with relevant factors were investigated.Methods: The survey was distributed from 1st April to 4th May 2020. We collected information on insomnia severity, depression, anxiety, sleep hygiene behaviors, dysfunctional beliefs about sleep, circadian preference, emotion regulation, cognitive flexibility, perceived stress, health habits, self-report of mental disorders, and variables related to individual difference in life changes due to the pandemic's outbreak.Results: The final sample comprised 1,989 persons (38.4 ± 12.8 yrs). Prevalence of clinical insomnia was 18.6%. Results from multivariable linear regression showed that insomnia severity was associated with poor sleep hygiene behaviors [β = 0.11, 95% CI (0.07–0.14)]; dysfunctional beliefs about sleep [β = 0.09, 95% CI (0.08–0.11)]; self-reported mental disorder [β = 2.51, 95% CI (1.8–3.1)]; anxiety [β = 0.33, 95% CI (0.25–0.42)]; and depression [β = 0.24, 95% CI (0.16–0.32)] symptoms.Conclusion: An alarming high prevalence of clinical insomnia was observed. Results suggest that clinical attention should be devoted to problems of insomnia in the Italian population with respect to both prevention and treatment.