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

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, in the following months the country had to face four new harsh waves of contagion. As of January 1, 2025, 198,638 deaths caused by COVID-19 were reported by the authorities, of which approximately 48.7 thousand in the region of Lombardy, 20.1 thousand in the region of Emilia-Romagna, and roughly 17.6 thousand in Veneto, the regions mostly hit. The total number of cases reported in the country 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 counted about 2.9 million cases. Italy's death toll was one of the most tragic in the world. In the last months, however, the country saw the end to this terrible situation: as of November 2023, 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.

Context

This is the Italian Coronavirus data repository from the Dipartimento della Protezione Civile . This dataset was created in response to the Coronavirus public health emergency in Italy and includes COVID-19 cases reported by region

Sample Queries

Dati Italia COVID-19: Which provinces in Italy have the most confirmed cases? Find which Italian provinces have the highest number of confirmed COVID-19 cases as of yesterday. SELECT covid19.province_name AS province, covid19.region_name AS region, confirmed_cases FROM bigquery-public-data.covid19_italy.data_by_province covid19 WHERE EXTRACT(date from DATE) = DATE_SUB(CURRENT_DATE(),INTERVAL 1 day) ORDER BY confirmed_cases desc

Sample Query 2

What percentage of tests performed have resulted in confirmed cases by region? This query determines what percent of tests performed are made up by confirmed cases. SELECT covid19.region_name AS region, total_confirmed_cases, tests_performed, ROUND(total_confirmed_cases/tests_performed*100,2) AS percent_tests_confirmed_cases FROM bigquery-public-data.covid19_italy.data_by_region covid19 WHERE EXTRACT(date from DATE) = DATE_SUB(CURRENT_DATE(),INTERVAL 1 day) ORDER BY percent_tests_confirmed_cases desc

As of January 1, 2025, Rome (Lazio) was the Italian province which registered the highest number of coronavirus (COVID-19) cases in the country. Milan (Lombardy) came second in this ranking, while Naples (Campania) and Turin (Piedmont) followed. These four areas are also the four most populated provinces in Italy. The region of Lombardy was the mostly hit by the spread of the virus, recording almost one sixth of all coronavirus cases in the country. The provinces of Milan and Brescia accounted for a large part of this figure. For a global overview, visit Statista's webpage exclusively dedicated to coronavirus, its development, and its impact.

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.

In past 24 hours, Italy, Europe had N/A new cases, N/A deaths and N/A recoveries.

Background: Coronavirus Disease 2019 (COVID-19) is currently a global public health threat. Outside of China, Italy is one of the countries suffering the most with the COVID-19 epidemic. It is important to predict the epidemic trend of the COVID-19 epidemic in Italy to help develop public health strategies.Methods: We used time-series data of COVID-19 from Jan 22 2020 to Apr 02 2020. An infectious disease dynamic extended susceptible-infected-removed (eSIR) model, which covers the effects of different intervention measures in dissimilar periods, was applied to estimate the epidemic trend in Italy. The basic reproductive number was estimated using Markov Chain Monte Carlo methods and presented using the resulting posterior mean and 95% credible interval (CI). Hunan, with a similar total population number to Italy, was used as a comparative item.Results: In the eSIR model, we estimated that the mean of basic reproductive number for COVID-19 was 4.34 (95% CI, 3.04–6.00) in Italy and 3.16 (95% CI, 1.73–5.25) in Hunan. There would be a total of 182 051 infected cases (95%CI:116 114–274 378) under the current country blockade and the endpoint would be Aug 05 in Italy.Conclusion: Italy's current strict measures can efficaciously prevent the further spread of COVID-19 and should be maintained. Necessary strict public health measures should be implemented as soon as possible in other European countries with a high number of COVID-19 cases. The most effective strategy needs to be confirmed in further studies.

Italy recorded 190080 Coronavirus Deaths since the epidemic began, according to the World Health Organization (WHO). In addition, Italy reported 25828252 Coronavirus Cases. This dataset includes a chart with historical data for Italy Coronavirus Deaths.

Daily information on the spread of the COVID-19 epidemic in Italy (over time and by location) and on the characteristics of the reported cases. They are provided in the form of charts, maps and tables, or in the form of bulletins providing a more in-depth analysis of the gathered information.

New Covid cases per month in Italy, March, 2023 The most recent value is 105818 new Covid cases as of March 2023, a decline compared to the previous value of 119423 new Covid cases. Historically, the average for Italy from February 2020 to March 2023 is 676192 new Covid cases. The minimum of 885 new Covid cases was recorded in February 2020, while the maximum of 4944057 new Covid cases was reached in January 2022. | TheGlobalEconomy.com

Italy recorded 4081902 Coronavirus Recovered since the epidemic began, according to the World Health Organization (WHO). In addition, Italy reported 135178 Coronavirus Deaths. This dataset includes a chart with historical data for Italy Coronavirus Recovered.

Updated with cases as of April 6st, 1830 hrs

Check the completely interactive Uber-KeplerGL map of the cases as shown in the image below

Context

Coronavirus Emergency: Nation-wide Quarantine

10th Match 2020, Italian Prime Minister Giuseppe Conte announced the extension of Italy's emergency coronavirus measures, which include travel restrictions and a ban on public gatherings, from 15 provinces to the entire nation. Italy is by far the most affected country outside China with thousands of cases and hundreds of deaths.

The Department of Civil Protection of Italy has taken actions to keep citizens well informed on the spread of the virus while the country is in lockdown. The department has released an interactive geographical dashboard to monitor the crisis [Desktop] [Mobile] and is updated every day at 18:30 after the department's press conference.

https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F1396051%2Fefc24e6ff01f03289c957e1dd4790c3a%2Fmy_keplergl_map%20html.png?generation=1584807526886981&alt=media" alt="">

Inspiration

This Kaggle dataset is created only to make it easy for the community to draw further and useful insights from the data.

This inspiration to put this data on Kaggle is not only to draw raw statistics on cases and deaths but to mine more useful data that could be actively used right now. How?

Leveraging the longitude and latitude information of cases, visualizing them with the distinction between old and new cases along with the temporal information would give better insight into the spread of the virus in a much-magnified perspective. This could be very helpful for the locals to avoid going through those regions

Content

This dataset currently provides national, provincial, and regional data of the CoVID-19 cases in Italy. Check out the script to used to convert the original json files and the started notebook in the kernels.

The time-series data starts from 24th February 2020 till the epidemic ends.

Context

To inform citizens and make the collected data available, the Department of Civil Protection has developed an interactive geographic dashboard accessible at the addresses http://arcg.is/C1unv (desktop version) and http://arcg.is/081a51 (mobile version) and makes available, with CC-BY-4.0 license, the following information updated daily at 18:30 (after the Head of Department press conference). For more detail, see https://github.com/pcm-dpc/COVID-19.

Content

COVID-19 data Italy

National trend Json data Provinces data Regions data Summary cards Areas Repository structure COVID-19 / │ ├── national-trend / │ ├── dpc-covid19-eng-national-trend-yyyymmdd.csv ├── areas / │ ├── geojson │ │ ├── dpc-covid19-ita-aree.geojson │ ├── shp │ │ ├── dpc-covid19-eng-areas.shp ├── data-provinces / │ ├── dpc-covid19-ita-province-yyyymmdd.csv ├── data-json / │ ├── dpc-covid19-eng - *. Json ├── data-regions / │ ├── dpc-covid19-eng-regions-yyyymmdd.csv ├── summary-sheets / │ ├── provinces │ │ ├── dpc-covid19-ita-scheda-province-yyyymmdd.pdf │ ├── regions │ │ ├── dpc-covid19-eng-card-regions-yyyymmdd.pdf

Data by Region Directory: data-regions Daily file structure: dpc-covid19-ita-regions-yyyymmdd.csv (dpc-covid19-ita-regions-20200224.csv) Overall file: dpc-covid19-eng-regions.csv An overall JSON file of all dates is made available in the "data-json" folder: dpc-covid19-eng-regions.json

Data by Province Directory: data-provinces Daily file structure: dpc-covid19-ita-province-yyyymmdd.csv (dpc-covid19-ita-province-20200224.csv) Overall file: dpc-covid19-ita-province.csv

Acknowledgements

Banner photo by CDC on Unsplash

Data from https://github.com/pcm-dpc/COVID-19 released under a CC 4.0 license. See https://github.com/pcm-dpc/COVID-19 for more detail.

Context

This data was gathered as part of the data mining project for the General Assembly Data Science course. using the API from https://rapidapi.com/astsiatsko/api/coronavirus-monitor .

Covid-19

The Covid-19 is a contagious coronavirus that hailed from Wuhan, China. This new strain of the virus has strike fear in many countries as cities are quarantined and hospitals are overcrowded. This dataset will help us understand how Covid-19 in Italy.

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.

### High Light: - Spread to various overtime in Italy - Try to predict the spread of COVID-19 ahead of time to take preventive measures

Content

• id: id number
• total_cases: the total number of cases have the coronavirus
• new_cases: the number of new cases with coronavirus in this day and time
• active_cases: Number of active cases with coronavirus
• total_deaths: the total deaths numbers by a coronavirus
• new_deaths: the number of new deaths in this day and time
• total_recovered: the number of recovered from the coronavirus
• serious_critical: numbe of the people have the coronavirus in serious critical
• total_cases_per1m: the number of confirmed cases per 1 million people than China
• record_date: Date of notification - YYYY-MM-DD HH:MM:SS

Inspiration

https://www.livescience.com/why-italy-coronavirus-deaths-so-high.html

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.

Italy MH: COVID-2019: Number of Cases: To-Date: Hospitalized Patients (HP) data was reported at 1,315.000 Person in 08 Jan 2025. This records a decrease from the previous number of 1,332.000 Person for 01 Jan 2025. Italy MH: COVID-2019: Number of Cases: To-Date: Hospitalized Patients (HP) data is updated daily, averaging 7,076.000 Person from Mar 2020 (Median) to 08 Jan 2025, with 815 observations. The data reached an all-time high of 34,697.000 Person in 23 Nov 2020 and a record low of 543.000 Person in 08 May 2024. Italy MH: COVID-2019: Number of Cases: To-Date: Hospitalized Patients (HP) data remains active status in CEIC and is reported by Ministry of Health. The data is categorized under High Frequency Database’s Disease Outbreaks – Table IT.D001: Ministry of Health: Coronavirus Disease 2019 (COVID-2019).

The dataset used in this paper is the COVID-19 data from Italy, downloaded from the Italian Ministry for Health free repository.

The number of COVID-19 vaccination doses administered in Italy rose to 143854436 as of Oct 27 2023. This dataset includes a chart with historical data for Italy Coronavirus Vaccination Total.

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.

A live version of the data record, which will be kept up-to-date with new estimates, can be downloaded from the Humanitarian Data Exchange: https://data.humdata.org/dataset/covid-19-mobility-italy.

If you find the data helpful or you use the data for your research, please cite our work:

Pepe, E., Bajardi, P., Gauvin, L., Privitera, F., Lake, B., Cattuto, C., & Tizzoni, M. (2020). COVID-19 outbreak response, a dataset to assess mobility changes in Italy following national lockdown. Scientific Data 7, 230 (2020).

The data record is structured into 4 comma-separated value (CSV) files, as follows:

id_provinces_IT.csv. Table of the administrative codes of the 107 Italian provinces. The fields of the table are:

COD_PROV is an integer field that is used to identify a province in all other data records;

SIGLA is a two-letters code that identifies the province according to the ISO_3166-2 standard (https://en.wikipedia.org/wiki/ISO_3166-2:IT);

DEN_PCM is the full name of the province.

OD_Matrix_daily_flows_norm_full_2020_01_18_2020_04_17.csv. The file contains the daily fraction of users’ moving between Italian provinces. Each line corresponds to an entry of matrix (i, j). The fields of the table are:

p1: COD_PROV of origin,

p2: COD_PROV of destination,

day: in the format yyyy-mm-dd.

median_q1_q3_rog_2020_01_18_2020_04_17.csv. The file contains median and interquartile range (IQR) of users’ radius of gyration in a province by week. Each entry of the table fields of the table are:

COD_PROV of the province;

SIGLA of the province;

DEN_PCM of the province;

week: median value of the radius of gyration on week week, with week in the format dd/mm-DD/MM where dd/mm and DD/MM are the first and the last day of the week, respectively.

week Q1 first quartile (Q1) of the distribution of the radius of gyration on week week,

week Q3 third quartile (Q3) of the distribution of the radius of gyration on week week,

average_network_degree_2020_01_18_2020_04_17.csv. The file contains daily time-series of the average degree 〈k〉 of the proximity network. Each entry of the table is a value of 〈k〉 on a given day. The fields of the table are:

COD_PROV of the province;

SIGLA of the province;

DEN_PCM of the province;

day in the format yyyy-mm-dd.

ESRI shapefiles of the Italian provinces updated to the most recent definition are available from the website of the Italian National Office of Statistics (ISTAT): https://www.istat.it/it/archivio/222527.