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, 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.

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.

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.

Activation time (UTC): 2020-04-05 22:46:00
Event time (UTC): 2020-04-06 08:00:00
Event type: Epidemic (Viral disease)

Activation reason:
Italy is currently facing a serious situation related to the Covid-19. The Head of the Civil Protection Department has been nominated as national emergency Coordinator and the entire National System has been activated to face the Emergency. From the first day of March, the entire Italian territory has been put on lock-down and further initiatives are being implemented to limit the spread of the disease. The Civil Protection needs to map all the temporary health facilities (such as triage facilities, field hospitals and so on) as well the gathering places in order to have a clear understanding of the current situation of the territory for the subsequent monitoring of activities and public spaces during the emergency.

Reference products: 8
Delineation products: 7
Grading products: 0

Copernicus Emergency Management Service - Mapping is a service funded by European Commission aimed at providing actors in the management of natural and man-made disasters, in particular Civil Protection Authorities and Humanitarian Aid actors, with mapping products based on satellite imagery.

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.

Additional file 2.

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.

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

Italy was the first and hardest-hit Western nation by the coronavirus pandemic (COVID-19). The identification of the first case, on 20th February, created widespread panic as residents in Italy began stockpiling food. Social media posts pictured near empty supermarket aisles. Soon after, this rush to hoard food spread across many other European nations. But those rushing to the supermarkets were the fortunate ones who could afford to do so. On 30th March, Pope Francis noted: ‘We’re beginning to see people who are hungry because they can’t work’,1 and pleaded for help. COVID-19 and the lockdown have placed the global economy under tremendous strain but are also increasing the threat of longer term food insecurity. Notwithstanding problems of cross-national data comparability, it is clear that food insecurity is already widespread in many high-income countries.2 In the aftermath of the global financial crisis in 2008, an estimated 13.5 million European households were tipped into food insecurity,3 while the current recession is already much deeper and is expected to last longer.4,5,6

The Excel file contains the data for the paper "Fear of infection and the common good: COVID-19 and the first Italian lockdown". This paper is currently under review. The original data came from the paper "Flesia L, Monaro M, Mazza C, Fietta V, Colicino E, Segatto B, et al. Predicting Perceived Stress Related to the Covid-19 Outbreak through Stable Psychological Traits and Machine Learning Models. J Clin Med. 2020;9(10)."

The central focus of this research is the fast and crucial impact of the COVID-19 pandemic on a crucial psychological, relational, and political construct: trust. We investigate how the consequences of the pandemic, in terms of healthcare, state intervention and impositions, and daily life and habits, have affected trust in public institutions in Italy, at the time when the contagion was rapidly spreading in the country (early March 2020). In this survey, addressed to 4260 Italian citizens, we analyzed and measured such impact, focusing on various aspects of trust. This attention to multiple dimensions of trust constitutes the key conceptual advantage of this research, since trust is a complex and layered construct, with its own internal dynamics. In particular, the analysis focuses on how citizens attribute trust to Public Authorities, in relation to the management of the health crisis: with regard to the measures and guidelines adopted, the purposes pursued, the motivations that determine them, their capacity for involvement, and their effectiveness for the containment of the virus itself. A pandemic creates a bilateral need for trust, both in Public Authorities (they have to rely on citizens’ compliance and must try to promote and maintain their trust in order to be effective) and in citizens, since they need to feel that somebody can do something, can (has the power to) protect them, to act at the needed collective level. We are interested to explore how this need for trust affects the attributional process, regarding both attitudes and the corresponding decisions and actions. The most striking result of this survey is the very high level of institutional trust expressed by respondents: 75% of them trust Italian public authorities to be able to deal with the COVID-19 emergency. This is in sharp contrast with the relatively low levels of institutional trust characteristic of Italy, both historically and in recent surveys. Moreover, the survey allowed the discrimination of several potential predictors for trust, thus emphasizing factors that, during this crisis, are exhibiting an anomalous impact on trust.

BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been responsible for the coronavirus disease 2019 (COVID-19) pandemic, which started as a severe pneumonia outbreak in Wuhan, China, in December 2019. Italy has been the first European country affected by the pandemic, registering a total of 300,363 cases and 35,741 deaths until September 24, 2020. The geographical distribution of SARS-CoV-2 in Italy during early 2020 has not been homogeneous, including regions severely affected as well as administrative areas being only slightly interested by the infection. Among the latter, Sardinia represents one of the lowest incidence areas likely due to its insular nature.MethodsNext-generation sequencing of a small number of complete viral genomes from clinical samples and their virologic and phylogenetic characterization was performed.ResultsWe provide a first overview of the SARS-CoV-2 genomic diversity in Sardinia in the early phase of the March–May 2020 pandemic based on viral genomes isolated in the most inner regional hospital of the island. Our analysis revealed a remarkable genetic diversity in local SARS-CoV-2 viral genomes, showing the presence of at least four different clusters that can be distinguished by specific amino acid substitutions. Based on epidemiological information, these sequences can be linked to at least eight different clusters of infection, four of which likely originates from imported cases. In addition, the presence of amino acid substitutions that were not previously reported in Italian patients has been observed, asking for further investigations in a wider population to assess their prevalence and dynamics of emergence during the pandemic.ConclusionThe present study provides a snapshot of the initial phases of the SARS-CoV-2 infection in inner area of the Sardinia Island, showing an unexpected genomic diversity.

Background: Previous studies during SARS and Ebola pandemics have shown that quarantine is associated with several negative psychological effects, such as post-traumatic stress symptoms, confusion, and anger. These conditions may affect the course of many diseases, including migraine. Although it is possible that the quarantine measures for the current COVID-19 pandemic affect migraine burden, no information is currently available on this issue.Aim: In this study, we aimed to: (1) explore the possible changes in migraine frequency, severity, and days with acute medication intake during quarantine period; (2) evaluate possible differences in migraine outcomes in consideration of lifestyle changes, emotions, pandemic diffusion, and COVID-19 infection.Methods: We interviewed patients who were included in the observational Italian Headache Registry (Registro Italiano Cefalee, RICE), retrospectively collecting information on main headache features, lifestyle factors, emotions, individual infection status, and perception of COVID-19 for 2 months before (pre-quarantine) and after the beginning of the quarantine (quarantine). Inclusion criteria were: age > 18, diagnosis of migraine without aura, migraine with aura and chronic migraine, last in-person visit more than 3 months preceding the beginning of quarantine.Results: A total of 433 migraine subjects agreed to be interviewed. We found an overall reduction in headache frequency (9.42 ± 0.43 days with headache vs. 8.28 ± 0.41) and intensity (6.57 ± 0.19 vs. 6.59 ± 0.21) during the quarantine, compared to pre-quarantine. There was a correlation between improvement and number of days of stay-at-home. When results were stratified for geographic area, we found a tendency toward worsening of headache frequency in northern Italy. Disgust regarding viral infection corresponded to a minor improvement in migraine.Conclusions: Migraine patients showed a mild improvement of migraine features, probably attributable to resilient behavior toward pandemic distress. Disgust regarding the contagion whereas potentially favoring defensive behavior, could potentially worsen migraine. The spontaneous limitation of migraine burden during quarantine could favor patient follow-up via the use of telemedicine visits, reliable diaries, and frequent remote contacts.

Present data are useful to investigate how the COVID-19 pandemic affected people’s mental health. The data were collected in Italy between April 1st and April 20th, 2020. The respondents participated in an online survey using the Qualtrics platform.

The ongoing pandemic of COVID-19 has forced governments to impose a lockdown, and many people have suddenly found themselves having to reduce their social relations drastically. Given the exceptional nature of similar situations, only a few studies have investigated the negative psychological effects of forced social isolation and how they can be mitigated in a real context. In the present study, we investigated whether the amount of digital communication technology use for virtual meetings (i.e., voice and video calls, online board games and multiplayer video games, or watching movies in party mode) during the lockdown promoted the perception of social support, which in itself mitigated the psychological effects of the lockdown in Italy. Data were collected in March 2020 (N = 465), during the lockdown imposed to reduce the COVID-19 spread. The results indicated that the amount of digital technology use reduced feelings of loneliness, anger/irritability, and boredom and increased belongingness via the perception of social support. The present study supported the positive role of digital technologies in maintaining meaningful social relationships even during an extreme situation such as a lockdown. Implications such as the need to reduce the digital divide and possible consequences of the ongoing pandemic are discussed.

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.

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.

Efforts to contain the spread of the coronavirus emphasize the central role of citizens’ compliance with self-protective behaviors. Understanding the processes underlying the decision to self-protect is, therefore, essential for effective risk communication during the COVID-19 pandemic. In the present study, we investigate the determinants of perceived threat and engagement in self-protective measures in the United Kingdom, Italy, and Austria during the first wave of the pandemic. The type of disease (coronavirus vs. seasonal flu) and the type of numerical information regarding the disease (number of recovered vs. number of dead) were manipulated. Participants’ cognitive and emotional risk assessment as well as self-reported engagement in protective behaviors were measured. Results show that worry was the best predictor of perceived threat in all countries. Moreover, a path analysis revealed that worry and perceived threat serially mediated the effect of type of disease on engagement in self-protective behaviors. The numerical framing manipulation did not significantly impact behavior but had a direct effect on worry and an indirect effect on perceived threat. These results are in line with theoretical accounts that identify emotions as a central determinant for risk perception. Moreover, our findings also suggest that effective risk communication during the COVID-19 pandemic should not stress comparisons to other, well-known viral diseases, as this can ultimately reduce self-protective behaviors.

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.