ArticleSensors (Basel, Switzerland)2020
A Cross-Regional Analysis of the COVID-19 Spread during the 2020 Italian Vacation Period: Results from Three Computational Models Are Compared.
Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Public holidays increased the transmission of COVID-19 in Japan, 2020-2021: a mathematical modelling study.Epidemiology and health · 2024Article
- Review
- An agent-based model to assess large-scale COVID-19 vaccination campaigns for the Italian territory: The case study of Lombardy region.Computer methods and programs in biomedicine · 2022Article
- Did the Tokyo Olympic Games enhance the transmission of COVID-19? An interpretation with machine learning.Computers in biology and medicine · 2022Article
- Tracking machine learning models for pandemic scenarios: a systematic review of machine learning models that predict local and global evolution of pandemics.Network modeling and analysis in health informatics and bioinformatics · 2022Review
- Predictive analytics of COVID-19 cases and tourist arrivals in ASEAN based on covid-19 cases.Health and technology · 2022Article
- Reopening Italy's schools in September 2020: a Bayesian estimation of the change in the growth rate of new SARS-CoV-2 cases.BMJ open · 2021Article
- From Isolation to Containment: Perceived Fear of Infectivity and Protective Behavioral Changes during the COVID-19 Vaccination Campaign.International journal of environmental research and public health · 2021Article
- Modeling of Vaccination and Contact Tracing as Tools to Control the COVID-19 Outbreak in Spain.Vaccines · 2021Article
- A Statistical Analysis of Death Rates in Italy for the Years 2015-2020 and a Comparison with the Casualties Reported from the COVID-19 Pandemic.Infectious disease reports · 2021Article
- Explaining covid-19 performance: what factors might predict national responses?BMJ (Clinical research ed.) · 2021Article
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Authors and funding
2 authors.
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Abstract
On 21 February 2020, a violent COVID-19 outbreak, which was initially concentrated in Lombardy before infecting some surrounding regions exploded in Italy. Shortly after, on 9 March, the Italian Government imposed severe restrictions on its citizens, including a ban on traveling to other parts of the country. No travel, no virus spread. Many regions, such as those in southern Italy, were spared. Then, in June 2020, under pressure for the economy to reopen, many lockdown measures were relaxed, including the ban on interregional travel. As a result, the virus traveled for hundreds of kilometers, from north to south, with the effect that areas without infections, receiving visitors from infected areas, became infected. This resulted in a sharp increase in the number of infected people; i.e., the daily count of new positive cases, when comparing measurements from the beginning of July to those from at the middle of September, rose significantly in almost all the Italian regions. Upon confirmation of the effect of Italian domestic tourism on the virus spread, three computational models of increasing complexity (linear, negative binomial regression, and cognitive) have been compared in this study, with the aim of identifying the one that better correlates the relationship between Italian tourist flows during the summer of 2020 and the resurgence of COVID-19 cases across the country. Results show that the cognitive model has more potential than the others, yet has relevant limitations. The models should be considered as a relevant starting point for the study of this phenomenon, even if there is still room to further develop them up to a point where they become able to capture all the various and complex spread patterns of this disease.
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