Department of Computer Science and Engineering, University of Bologna, 40127 Bologna, Italy.
Sensors (Basel). 2020 Dec 19;20(24):7319. doi: 10.3390/s20247319.
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.
2020 年 2 月 21 日，一场最初集中在伦巴第地区、随后感染了一些周边地区的剧烈 COVID-19 疫情在意大利爆发。此后不久，即 3 月 9 日，意大利政府对其公民实施了严格限制，包括禁止前往该国其他地区。没有旅行，就没有病毒传播。许多地区，如意大利南部地区，就幸免于难。然后，在 2020 年 6 月，迫于经济重启的压力，许多封锁措施被放宽，包括取消了对地区间旅行的禁令。结果，病毒从北到南传播了数百公里，从没有感染的地区，到接待来自感染地区的游客的地区，都受到了感染。这导致感染人数急剧增加；也就是说，与 7 月初和 9 月中旬的测量结果相比，几乎所有意大利地区的新增阳性病例的日计数都显著增加。在确认意大利国内旅游对病毒传播的影响后，本研究比较了三种越来越复杂的计算模型（线性、负二项回归和认知），目的是确定哪一种模型能更好地关联 2020 年夏季意大利游客流量与全国 COVID-19 病例再次出现之间的关系。结果表明，认知模型比其他模型更有潜力，但也有相关的局限性。这些模型应被视为研究这一现象的一个重要起点，即使仍有进一步发展的空间，直到它们能够捕捉到这种疾病的各种复杂传播模式。
