Since the spread of the coronavirus (COVID-19) in Italy, started in February 2020, many people who contracted the infection died. The number of deaths amounted to 198,683 as of January 8, 2025. On December 3, 2020, 993 patients died, the highest daily toll since the start of the pandemic. The region with the highest number of deaths was Lombardy, which is also the region that registered the highest number of coronavirus 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, roughly 85 percent of the total Italian population was fully vaccinated. For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

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.

After entering Italy, coronavirus (COVID-19) has been spreading fast. An analysis of the individuals who died after contracting the virus revealed that the vast majority of deaths occurred among the elderly. As of May, 2023, roughly 85 percent were patients aged 70 years and older.

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 May 2023, roughly 84.7 percent of the total Italian population was fully vaccinated.

As of May, 2023, the total number of cases reported in the country were over 25.8 million. The North of the country was the mostly hit area, and the region with the highest number of cases was Lombardy.

For a global overview visit Statista's webpage exclusively dedicated to coronavirus, its development, and its impact.

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.

As of January 1, 2025, the total number of coronavirus (COVID-19) cases in Italy amounted to over 26.9 million, approximately 218,000 of which were active cases. Moreover, the number of people who recovered or were discharged from hospital after contracting the virus reached over 26.5 million, while the number of deceased was equal to 198,638. For a global overview, visit Statista's webpage exclusively dedicated to coronavirus, its development, and its impact.

The spread of coronavirus (COVID-19) in Italy has hit every age group uniformly and claimed over 190 thousand lives since it entered the country. As the chart shows, however, mortality rate appeared to be much higher for the elderly patient. In fact, for people between 80 and 89 years of age, the fatality rate was 6.1 percent. For patients older than 90 years, this figure increased to 12.1 percent. On the other hand, the death rate for individuals under 60 years of age was well below 0.5 percent. Overall, the mortality rate of coronavirus in Italy was 0.7 percent.

Italy's death toll was one of the most tragic in the world. In the last months, however, the country started to see the end of this terrible situation: as of May 2023, roughly 84.7 percent of the total Italian population was fully vaccinated.

Since the first case was detected at the end of January in Italy, coronavirus has been spreading fast. As of May, 2023, the authorities reported over 25.8 million cases in the country. The area mostly hit by the virus is the North, in particular the region of Lombardy.

For a global overview visit Statista's webpage exclusively dedicated to coronavirus, its development, and its impact.

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.

This is that Dataset of covid-19 of Total deaths and Total Cases in 11 countries (Australia, United States, Indonesia, Pakistan, Bangladesh, Russia, United Kingdom, South Africa, Brazil, Italy and India) for comparison that how covid-19 impact these countries from 1st March 2020 to 1st March 2022, Monthly wise.

Data taken from WHO Website.

Data is based on accumulation means the cases of previous month are add to the new month and in the last row of Dataset contain the Total of all.

Summary of the total cases and infections and deaths amongst hospital workers in Hubei province, China and Italy.

Italy Coronavirus Cases by Age group and Sex (ICCAS)

This repository contains datasets about the number of Italian Sars-CoV-2 confirmed cases and deaths disaggregated by age group and sex. The data is (automatically) extracted from pdf reports (like this) published by Istituto Superiore di Sanità (ISS) two times a week. A link to the most recent report can be found in this page under section "Documento esteso".

PDF reports are usually published on Tuesday and Friday and contains data updated to the 4 p.m. of the day day before their release.

I wrote a script that is runned periodically in order to automatically update this repository when a new report is published. The code is hosted in a separate repository.

For feedback and issues refers to the GitHub repository.

Data folder structure

The data folder is structured as follows: data ├── by-date │ └── iccas_{date}.csv Dataset with cases/deaths updated to 4 p.m. of {date} └── iccas_full.csv Dataset with data from all reports (by date) The full dataset is obtained by concatenating all datasets in by-date and has an additional date column. If you use pandas, I suggest you to read this dataset using a multi-index on the first two columns: python import pandas as pd df = pd.read_csv('iccas_full.csv', index_col=(0, 1)) # ('date', 'age_group')

NOTE: {date} is the date the data refers to, NOT the release date of the report it was extracted from: as written above, a report is usually released with a day of delay. For example, iccas_2020-03-19.csv contains data relative to 2020-03-19 which was extracted from the report published in 2020-03-20.

Dataset details

Each dataset in the by-date folder contains the same data you can find in "Table 1" of the corresponding ISS report. This table contains the number of confirmed cases, deaths and other derived information disaggregated by age group (0-9, 10-19, ..., 80-89, >=90) and sex.

WARNING: the sum of male and female cases is not equal to the total number of cases, since the sex of some cases is unknown. The same applies to deaths.

Below, {sex} can be male or female.

All columns that can be computed from absolute counts of cases and deaths (bottom half of the table above) were all re-computed to increase precision.

The spread of coronavirus (COVID-19) in Italy has not hit uniformly people of every age, as about 60 percent of the individuals infected with the virus were under 50 years old. However, deaths occurred mostly among the elderly. The virus has claimed approximately 190 thousand lives, but, as the chart shows, roughly 85 percent of the victims were older people, aged 70 years or more. People between 80 and 89 years were the most affected, with roughly 76 thousand deaths within this age group.

Number of total cases Since the first case was detected, coronavirus has spread quickly across Italy. As of April 2023, authorities have reported over 25.8 million cases in the country. This figure includes the deceased, the recovered, and current active cases. COVID recoveries represent the vast majority, reaching approximately 25.5 million.

Regional differences In terms of COVID cases, Lombardy has been the hardest hit region, followed by the regions of Campania, and Veneto. Likewise, in terms of deaths, Lombardy was the region with the highest number, with roughly 46 thousand losses. On the other hand, this is also the region with the highest number of COVID-19 vaccine administered doses, with a figure of approximately 25.5 million.

For a global overview visit Statista's webpage exclusively dedicated to coronavirus, its development, and its impact.

Objectives: To describe the monthly distribution of COVID-19 hospitalisations, deaths and case-fatality rates (CFR) in Lombardy (Italy) throughout 2020.Methods: We analysed de-identified hospitalisation data comprising all COVID-19-related admissions from 1 February 2020 to 31 December 2020. The overall survival (OS) from time of first hospitalisation was estimated using the Kaplan-Meier method. We estimated monthly CFRs and performed Cox regression models to measure the effects of potential predictors on OS.Results: Hospitalisation and death peaks occurred in March and November 2020. Patients aged ≥70 years had an up to 180 times higher risk of dying compared to younger patients [70–80: HR 58.10 (39.14–86.22); 80–90: 106.68 (71.01–160.27); ≥90: 180.96 (118.80–275.64)]. Risk of death was higher in patients with one or more comorbidities [1: HR 1.27 (95% CI 1.20–1.35); 2: 1.44 (1.33–1.55); ≥3: 1.73 (1.58–1.90)] and in those with specific conditions (hypertension, diabetes).Conclusion: Our data sheds light on the Italian pandemic scenario, uncovering mechanisms and gaps at regional health system level and, on a larger scale, adding to the body of knowledge needed to inform effective health service planning, delivery, and preparedness in times of crisis.

Context

The novel coronavirus that has infected more than 79,551 people worldwide (as of time of writing this context) is spreading rapidly, and independently, in countries outside of China, including Italy, South Korea, and Iran. The viral illness is being diagnosed among hundreds of people in South Korea, Italy and Iran who have no connection to China.

Content

In the notebook I use the time series data. Time series data columns are described in the column description.

Acknowledgements

Thanks to the Johns Hopkins University for providing this data-set for educational purposes. https://github.com/CSSEGISandData/COVID-19

Inspiration

To visualize COVID-19 spread world wide.

Italy was the first European country to be significantly impacted by the COVID-19 pandemic. The lack of similar previous experiences and the initial uncertainty regarding the new virus resulted in an unpredictable health crisis with 243,506 total confirmed cases and 34,997 deaths between February and July 2020. Despite the panorama of precariousness and the impelling calamity, the country successfully managed many aspects of the early stages of the health and socio-economic crisis. Nevertheless, many disparities can be identified at the regional level. The study aims to determine which aspects of regional management were considered more important by the citizens regarding economic and health criteria. A survey was designed to gather responses from the population on the Italian regions’ response and provide a ranking of the regions. The 29-item online survey was provided to 352 individuals, and the collected data were analyzed using the Analytic Hierarchy Process methodology. The results show a general agreement in considering of greater relevance the healthcare policies rather than the economic countermeasures adopted by regional governments. Our analysis associated a weight of 64% to the healthcare criteria compared to the economic criteria with a weight of 36%. In addition to the results obtained from the Analytic Hierarchy Process, the sample’s composition was analyzed to provide an overall assessment of the Italian regions. To do so, we collected objective data for each region and multiplied them by the overall weight obtained for each sub-criteria. Looking at the propensity to vaccination or the belief in a relation between COVID-19 and 5G according to age and educational qualification helps understand how public opinion is structured according to cultural and anthropological differences.

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.

Over the course of 2020, 75,891 deaths caused by COVID-19 were reported to the authorities in Italy. In total, the number of deaths in the country surpassed 746 thousand, the highest figure registered since World War II. This statistic shows the percentage change in the number of deaths per age group of the individuals who died, comparing figures for 2020 with the average of deaths in the same period between 2015 and 2019. The three periods considered correspond to three main stages of 2020 in Italy: the pre-COVID-19 months, the first wave, and the second wave. It is possible to see how COVID-19 impacted the different age groups disproportionately. The number of deaths recorded among individuals between zero and 49 years old, in fact, was even consistently less than the 2015-2019 average across 2020. On the other hand, during the first and second wave of infections, the number of deaths registered among people aged 80 years or more was 36 percent higher than the 2015-2019 average.

Baseline characteristics of COVID-19 patients hospitalized in the region of Lombardy, Italy, during the first COVID-19 wave (Feb-May 2020).

Italy was the first European country to be significantly impacted by the COVID-19 pandemic. The lack of similar previous experiences and the initial uncertainty regarding the new virus resulted in an unpredictable health crisis with 243,506 total confirmed cases and 34,997 deaths between February and July 2020. Despite the panorama of precariousness and the impelling calamity, the country successfully managed many aspects of the early stages of the health and socio-economic crisis. Nevertheless, many disparities can be identified at the regional level. The study aims to determine which aspects of regional management were considered more important by the citizens regarding economic and health criteria. A survey was designed to gather responses from the population on the Italian regions’ response and provide a ranking of the regions. The 29-item online survey was provided to 352 individuals, and the collected data were analyzed using the Analytic Hierarchy Process methodology. The results show a general agreement in considering of greater relevance the healthcare policies rather than the economic countermeasures adopted by regional governments. Our analysis associated a weight of 64% to the healthcare criteria compared to the economic criteria with a weight of 36%. In addition to the results obtained from the Analytic Hierarchy Process, the sample’s composition was analyzed to provide an overall assessment of the Italian regions. To do so, we collected objective data for each region and multiplied them by the overall weight obtained for each sub-criteria. Looking at the propensity to vaccination or the belief in a relation between COVID-19 and 5G according to age and educational qualification helps understand how public opinion is structured according to cultural and anthropological differences.

On March 10, 2023, the Johns Hopkins Coronavirus Resource Center ceased its collecting and reporting of global COVID-19 data. For updated cases, deaths, and vaccine data please visit the following sources: World Health Organization (WHO)For more information, visit the Johns Hopkins Coronavirus Resource Center.-- Esri COVID-19 Trend Report for 3-9-2023 --0 Countries have Emergent trend with more than 10 days of cases: (name : # of active cases) 41 Countries have Spreading trend with over 21 days in new cases curve tail: (name : # of active cases)Monaco : 13, Andorra : 25, Marshall Islands : 52, Kyrgyzstan : 79, Cuba : 82, Saint Lucia : 127, Cote d'Ivoire : 148, Albania : 155, Bosnia and Herzegovina : 172, Iceland : 196, Mali : 198, Suriname : 246, Botswana : 247, Barbados : 274, Dominican Republic : 304, Malta : 306, Venezuela : 334, Micronesia : 346, Uzbekistan : 356, Afghanistan : 371, Jamaica : 390, Latvia : 402, Mozambique : 406, Kosovo : 412, Azerbaijan : 427, Tunisia : 528, Armenia : 594, Kuwait : 716, Thailand : 746, Norway : 768, Croatia : 847, Honduras : 1002, Zimbabwe : 1067, Saudi Arabia : 1098, Bulgaria : 1148, Zambia : 1166, Panama : 1300, Uruguay : 1483, Kazakhstan : 1671, Paraguay : 2080, Ecuador : 53320 Countries may have Spreading trend with under 21 days in new cases curve tail: (name : # of active cases)61 Countries have Epidemic trend with over 21 days in new cases curve tail: (name : # of active cases)Liechtenstein : 48, San Marino : 111, Mauritius : 742, Estonia : 761, Trinidad and Tobago : 1296, Montenegro : 1486, Luxembourg : 1540, Qatar : 1541, Philippines : 1915, Ireland : 1946, Brunei : 2010, United Arab Emirates : 2013, Denmark : 2111, Sweden : 2149, Finland : 2154, Hungary : 2169, Lebanon : 2208, Bolivia : 2838, Colombia : 3250, Switzerland : 3321, Peru : 3328, Slovakia : 3556, Malaysia : 3608, Indonesia : 3793, Portugal : 4049, Cyprus : 4279, Argentina : 5050, Iran : 5135, Lithuania : 5323, Guatemala : 5516, Slovenia : 5689, South Africa : 6604, Georgia : 7938, Moldova : 8082, Israel : 8746, Bahrain : 8932, Netherlands : 9710, Romania : 12375, Costa Rica : 12625, Singapore : 13816, Serbia : 14093, Czechia : 14897, Spain : 17399, Ukraine : 19568, Canada : 24913, New Zealand : 25136, Belgium : 30599, Poland : 38894, Chile : 41055, Australia : 50192, Mexico : 65453, United Kingdom : 65697, France : 68318, Italy : 70391, Austria : 90483, Brazil : 134279, Korea - South : 209145, Russia : 214935, Germany : 257248, Japan : 361884, US : 6440500 Countries may have Epidemic trend with under 21 days in new cases curve tail: (name : # of active cases) 54 Countries have Controlled trend: (name : # of active cases)Palau : 3, Saint Kitts and Nevis : 4, Guinea-Bissau : 7, Cabo Verde : 8, Mongolia : 8, Benin : 9, Maldives : 10, Comoros : 10, Gambia : 12, Bhutan : 14, Cambodia : 14, Syria : 14, Seychelles : 15, Senegal : 16, Libya : 16, Laos : 17, Sri Lanka : 19, Congo (Brazzaville) : 19, Tonga : 21, Liberia : 24, Chad : 25, Fiji : 26, Nepal : 27, Togo : 30, Nicaragua : 32, Madagascar : 37, Sudan : 38, Papua New Guinea : 38, Belize : 59, Egypt : 60, Algeria : 64, Burma : 65, Ghana : 72, Haiti : 74, Eswatini : 75, Guyana : 79, Rwanda : 83, Uganda : 88, Kenya : 92, Burundi : 94, Angola : 98, Congo (Kinshasa) : 125, Morocco : 125, Bangladesh : 127, Tanzania : 128, Nigeria : 135, Malawi : 148, Ethiopia : 248, Vietnam : 269, Namibia : 422, Cameroon : 462, Pakistan : 660, India : 4290 41 Countries have End Stage trend: (name : # of active cases)Sao Tome and Principe : 1, Saint Vincent and the Grenadines : 2, Somalia : 2, Timor-Leste : 2, Kiribati : 8, Mauritania : 12, Oman : 14, Equatorial Guinea : 20, Guinea : 28, Burkina Faso : 32, North Macedonia : 351, Nauru : 479, Samoa : 554, China : 2897, Taiwan* : 249634 -- SPIKING OF NEW CASE COUNTS --20 countries are currently experiencing spikes in new confirmed cases:Armenia, Barbados, Belgium, Brunei, Chile, Costa Rica, Georgia, India, Indonesia, Ireland, Israel, Kuwait, Luxembourg, Malaysia, Mauritius, Portugal, Sweden, Ukraine, United Kingdom, Uzbekistan 20 countries experienced a spike in new confirmed cases 3 to 5 days ago: Argentina, Bulgaria, Croatia, Czechia, Denmark, Estonia, France, Korea - South, Lithuania, Mozambique, New Zealand, Panama, Poland, Qatar, Romania, Slovakia, Slovenia, Switzerland, Trinidad and Tobago, United Arab Emirates 47 countries experienced a spike in new confirmed cases 5 to 14 days ago: Australia, Austria, Bahrain, Bolivia, Brazil, Canada, Colombia, Congo (Kinshasa), Cyprus, Dominican Republic, Ecuador, Finland, Germany, Guatemala, Honduras, Hungary, Iran, Italy, Jamaica, Japan, Kazakhstan, Lebanon, Malta, Mexico, Micronesia, Moldova, Montenegro, Netherlands, Nigeria, Pakistan, Paraguay, Peru, Philippines, Russia, Saint Lucia, Saudi Arabia, Serbia, Singapore, South Africa, Spain, Suriname, Thailand, Tunisia, US, Uruguay, Zambia, Zimbabwe 194 countries experienced a spike in new confirmed cases over 14 days ago: Afghanistan, Albania, Algeria, Andorra, Angola, Antigua and Barbuda, Argentina, Armenia, Australia, Austria, Azerbaijan, Bahamas, Bahrain, Bangladesh, Barbados, Belarus, Belgium, Belize, Benin, Bhutan, Bolivia, Bosnia and Herzegovina, Botswana, Brazil, Brunei, Bulgaria, Burkina Faso, Burma, Burundi, Cabo Verde, Cambodia, Cameroon, Canada, Central African Republic, Chad, Chile, China, Colombia, Comoros, Congo (Brazzaville), Congo (Kinshasa), Costa Rica, Cote d'Ivoire, Croatia, Cuba, Cyprus, Czechia, Denmark, Djibouti, Dominica, Dominican Republic, Ecuador, Egypt, El Salvador, Equatorial Guinea, Eritrea, Estonia, Eswatini, Ethiopia, Fiji, Finland, France, Gabon, Gambia, Georgia, Germany, Ghana, Greece, Grenada, Guatemala, Guinea, Guinea-Bissau, Guyana, Haiti, Honduras, Hungary, Iceland, India, Indonesia, Iran, Iraq, Ireland, Israel, Italy, Jamaica, Japan, Jordan, Kazakhstan, Kenya, Kiribati, Korea - South, Kosovo, Kuwait, Kyrgyzstan, Laos, Latvia, Lebanon, Lesotho, Liberia, Libya, Liechtenstein, Lithuania, Luxembourg, Madagascar, Malawi, Malaysia, Maldives, Mali, Malta, Marshall Islands, Mauritania, Mauritius, Mexico, Micronesia, Moldova, Monaco, Mongolia, Montenegro, Morocco, Mozambique, Namibia, Nauru, Nepal, Netherlands, New Zealand, Nicaragua, Niger, Nigeria, North Macedonia, Norway, Oman, Pakistan, Palau, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Poland, Portugal, Qatar, Romania, Russia, Rwanda, Saint Kitts and Nevis, Saint Lucia, Saint Vincent and the Grenadines, Samoa, San Marino, Sao Tome and Principe, Saudi Arabia, Senegal, Serbia, Seychelles, Sierra Leone, Singapore, Slovakia, Slovenia, Solomon Islands, Somalia, South Africa, South Sudan, Spain, Sri Lanka, Sudan, Suriname, Sweden, Switzerland, Syria, Taiwan*, Tajikistan, Tanzania, Thailand, Timor-Leste, Togo, Tonga, Trinidad and Tobago, Tunisia, Turkey, Tuvalu, US, Uganda, Ukraine, United Arab Emirates, United Kingdom, Uruguay, Uzbekistan, Vanuatu, Venezuela, Vietnam, West Bank and Gaza, Yemen, Zambia, Zimbabwe Strongest spike in past two days was in US at 64,861 new cases.Strongest spike in past five days was in US at 64,861 new cases.Strongest spike in outbreak was 424 days ago in US at 1,354,505 new cases. Global Total Confirmed COVID-19 Case Rate of 8620.91 per 100,000Global Active Confirmed COVID-19 Case Rate of 37.24 per 100,000Global COVID-19 Mortality Rate of 87.69 per 100,000 21 countries with over 200 per 100,000 active cases.5 countries with over 500 per 100,000 active cases.3 countries with over 1,000 per 100,000 active cases.1 country with over 2,000 per 100,000 active cases.Nauru is worst at 4,354.54 per 100,000.

What impact has the COVID-19 pandemic had on Italians' attitudes, opinions, and behaviors? From this question, the ResPOnsE COVID-19 project (Response of Italian Public Opinion to the COVID-19 Emergency) was developed starting in March 2020, with the aim of building a research infrastructure for the daily monitoring of public opinion during the COVID-19 emergency. The collection of daily information through online interviews (CAWI) to a sample reflecting the distribution of the Italian population by gender and area of residence was divided into four surveys that took place between April 2020 and December 2021, for a total of more than 30,000 interviews. The infrastructure was designed by the spsTREND "Hans Schadee" laboratory in collaboration with the SWG institute, as part of the "Departments of Excellence 2018-2022" project promoted by the Ministry of University and Research and is supported by funding from the Cariplo Foundation. Overall Research Design The four waves of ResPOnsE COVID-19 are distributed as follows. First wave: from April 6 to July 6, 2020 (~15000 cases, RR=46,6%) Second wave: from December 21, 2020 to January 2, 2021 (~3000 cases, RR=47%) Third wave: from March 17 to June 16, 2021 (~9300 cases, RR=76.9%) Fourth wave: from November 10 to December 22, 2021 (~3000 cases, RR=67.1%) Rolling Cross-Section and Panel Design The first, third, and fourth waves collect interviews through a Rolling Cross-Section (RCS) design, that is consecutive daily samples for a relatively long period (in this case 2 to 3 months). In addition, about 60% of subjects were interviewed twice between the first and third or fourth wave, thus allowing longitudinal analysis of intra-individual variations that occurred between 2020 and 2021. An RCS survey can be viewed as a cross-sectional survey of a single sample that is, however, "sliced" into many equivalent small subgroups that are released on consecutive days. On the day of release, individuals belonging to a particular sub-group are invited to participate in the survey. The distinguishing feature of the RCS design, however, is that these individuals can also respond in the days following the delivery of the invitation. Hence comes the term "rolling" meaning that the overall sample "rolls" through the days of the survey, making time (days) a random variable. The daily samples are mutually independent and the estimates derived for each are comparable. In this way, the RCS design is optimal for studying trends in the case of time-varying phenomena. For details, see the articles by Vezzoni et al. (2020) and Biolcati et al. (2021). Questionnaire structure The questionnaire administered in the ResPOnsE COVID-19 survey consists of a main questionnaire, containing a core set of questions repeated in each of the four surveys, and one or more thematic modules that may change with each survey. The main questionnaire consists of eleven thematic sections covering the entire survey period. Most of the questions in the questionnaire were repeated in the four surveys, while some questions were eliminated/changed or new ones were introduced in the transition to a new survey. Covering the entire survey period, the basic module is particularly suitable for diachronic analysis, while the structure of the thematic modules, usually collected over a few weeks, suggests an analysis of them with a cross-sectional approach. Source questionnaires in Italian are available for download. The sample The target population consists of Italian residents aged 18 years and older. In the RCS waves, on average, between 100 and 150 interviews were conducted each day, corresponding to about 1,000 interviews per week for the first survey and about 700 for the third and fourth surveys (the interviews in the second survey were actually concentrated in a single week), for a total of 31,122 interviews. Given time and resource constraints, probabilistic sampling could not be used. Instead, the samples are drawn from an online community of a commercial research institute (SWG SpA). To correct against expected bias, the sample is stratified by ISTAT macro-area of residence and composed of quotas defined by gender and age. Weights have also been created for carryover to the population. Detailed instructions on using the weights can be downloaded together with the data files. The survey also includes a panel component: about 60 percent of subjects were interviewed twice between the first, third, and fourth waves. Over-sampling was also conducted for the Lombardy region, for which 1124 additional cases are available in the third wave Macro level data The cumulative data file also includes official macro-level variables capturing daily information on the health emergency, such as the number of people infected by COVID-19 and the number of deaths due to COVID-19 at the national and regional level on the day of the interview. The macro-level variables were extracted here:...