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

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

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.

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.

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.

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

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.

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.

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.

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.

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.

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. More information on the data repository is available here . For additional information on Italy’s situation tracking and reporting, see the department’s Coronavirus site and interactive dashboard . This public dataset is hosted in Google BigQuery and is included in BigQuery's 1TB/mo of free tier processing. This means that each user receives 1TB of free BigQuery processing every month, which can be used to run queries on this public dataset. Watch this short video to learn how to get started quickly using BigQuery to access public datasets. What is BigQuery . This dataset is hosted in both the EU and US regions of BigQuery. See the links below for the appropriate dataset copy: US region EU region This dataset has significant public interest in light of the COVID-19 crisis. All bytes processed in queries against this dataset will be zeroed out, making this part of the query free. Data joined with the dataset will be billed at the normal rate to prevent abuse. After September 15, queries over these datasets will revert to the normal billing rate.

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

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

Since the spread of the coronavirus (COVID-19) in Italy started in February 2020, the number of cases has increased daily. However, the vast majority of people who contracted the virus have recovered. As of January 8, 2025, the number of individuals who recovered from coronavirus in Italy reached over 26.5 million. Conversely, the number of deaths also kept increasing, reaching over 198.6 thousand. When looking at the regional level, the region with the highest number of recoveries was Lombardy. The region, however, registered the highest number of coronavirus cases in the country. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

Dataset

This dataset was created by Usama Raheem

Released under Database: Open Database, Contents: Database Contents

Contents

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.

Case data from 02-24-2020 to 08-16-2020, this data repository stores COVID-19 virus case data for Italy, including daily case data, summary data, and base map. Each zip file contains weekly case data from Monday to Sunday.

The data are related to Tuscany and its provinces. They covered the period from 24/2/2020 to 15/6/2022 and they were updated daily.

Two tables were created: one with data from the entire Tuscany and the other with data from each province within Tuscany (AR, FI, GR, LI, LU, MS, PI, PO, PT, SI) and each medical district of the region (aslCENTRO,aslNO,aslSE).

Inspiration

You can perform an exploratory data analysis of the data, working with Pandas or Numpy.

Interesting visualizations can be performed too using, for instance, Python libraries to plot the data of the number of deaths, dismissed patients, total and current positives, recoveries etc.

It might be useful to plot the data in time, working with different date formats too and conducting a time series analysis.

Moreover, this dataset is very good to practice queries using SQL or Pandas.

Remember to upvote if you found the dataset useful :).

Collection methodology

The data were fetched from the following link: https://dati.toscana.it/dataset/open-data-covid19.

The rows from provinces were separated from the rows related to Tuscany region and some columns were removed from the catalogue since they didn't contain any data. Furthermore, some columns were transformed from floats to integers, missing values were filled with the integer '0' and the headers were translated to English.