Álvaro Cabana, Lorena Etcheverry, M. Fariello, P. Bermolen, Marcelo Fiori
{"title":"评估第二波COVID-19疫情中人员流动减少的影响","authors":"Álvaro Cabana, Lorena Etcheverry, M. Fariello, P. Bermolen, Marcelo Fiori","doi":"10.1109/CLEI53233.2021.9639974","DOIUrl":null,"url":null,"abstract":"By February 2021, Uruguay was experiencing the first wave of the COVID-19 pandemic, while many countries were already suffering the second wave. Several countries took various measures to prevent the saturation of the health system, ranging from closure of restaurants and suspension of classes to nighttime traffic restrictions. In this paper, we explore the effect of mobility restriction measures on the infection incidence in countries that are in some way similar to Uruguay: they have between one and twelve million inhabitants, a reasonable testing effort and they had the epidemic under control at some point. For these countries, we study mobility indexes provided by Google, an index on governmental measures compiled by the University of Oxford, and the daily new cases per 100,000 inhabitants. First, we observed that the mobility reported by Google is directly related to government measures: the higher the level of restrictive measures, the lower the mobility index. Then, we analyze the influence of mobility reduction on the growth/decrease speed of the 7-day average of new cases per 100,000 inhabitants (P7) and show that high levels of mobility reduction lead to a decrease in the index. Finally, we related the required duration of mobility restrictions with the P7 maximum and also point out the risk of lifting the measures too early.","PeriodicalId":6803,"journal":{"name":"2021 XLVII Latin American Computing Conference (CLEI)","volume":"6 1","pages":"1-10"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Assessing the impact of mobility reduction in the second wave of COVID-19\",\"authors\":\"Álvaro Cabana, Lorena Etcheverry, M. Fariello, P. Bermolen, Marcelo Fiori\",\"doi\":\"10.1109/CLEI53233.2021.9639974\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"By February 2021, Uruguay was experiencing the first wave of the COVID-19 pandemic, while many countries were already suffering the second wave. Several countries took various measures to prevent the saturation of the health system, ranging from closure of restaurants and suspension of classes to nighttime traffic restrictions. In this paper, we explore the effect of mobility restriction measures on the infection incidence in countries that are in some way similar to Uruguay: they have between one and twelve million inhabitants, a reasonable testing effort and they had the epidemic under control at some point. For these countries, we study mobility indexes provided by Google, an index on governmental measures compiled by the University of Oxford, and the daily new cases per 100,000 inhabitants. First, we observed that the mobility reported by Google is directly related to government measures: the higher the level of restrictive measures, the lower the mobility index. Then, we analyze the influence of mobility reduction on the growth/decrease speed of the 7-day average of new cases per 100,000 inhabitants (P7) and show that high levels of mobility reduction lead to a decrease in the index. Finally, we related the required duration of mobility restrictions with the P7 maximum and also point out the risk of lifting the measures too early.\",\"PeriodicalId\":6803,\"journal\":{\"name\":\"2021 XLVII Latin American Computing Conference (CLEI)\",\"volume\":\"6 1\",\"pages\":\"1-10\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-10-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 XLVII Latin American Computing Conference (CLEI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CLEI53233.2021.9639974\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 XLVII Latin American Computing Conference (CLEI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CLEI53233.2021.9639974","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
摘要
到2021年2月,乌拉圭正在经历COVID-19大流行的第一波,而许多国家已经遭受了第二波。几个国家采取了各种措施,从关闭餐馆和停课到夜间交通限制,以防止卫生系统饱和。在这篇论文中,我们探讨了行动限制措施对感染发生率的影响,这些国家在某种程度上与乌拉圭相似:它们有100万到1200万居民,有合理的检测工作,并且在某种程度上控制了疫情。对于这些国家,我们研究了谷歌(Google)提供的流动性指数、牛津大学(University of Oxford)编制的政府措施指数,以及每10万居民每日新增病例数。首先,我们观察到谷歌报告的流动性与政府措施直接相关:限制措施水平越高,流动性指数越低。然后,我们分析了流动性减少对每10万居民7天平均新增病例增长/减少速度的影响(P7),并表明流动性减少水平高导致指数下降。最后,我们将行动限制所需的持续时间与P7最大值联系起来,并指出过早解除措施的风险。
Assessing the impact of mobility reduction in the second wave of COVID-19
By February 2021, Uruguay was experiencing the first wave of the COVID-19 pandemic, while many countries were already suffering the second wave. Several countries took various measures to prevent the saturation of the health system, ranging from closure of restaurants and suspension of classes to nighttime traffic restrictions. In this paper, we explore the effect of mobility restriction measures on the infection incidence in countries that are in some way similar to Uruguay: they have between one and twelve million inhabitants, a reasonable testing effort and they had the epidemic under control at some point. For these countries, we study mobility indexes provided by Google, an index on governmental measures compiled by the University of Oxford, and the daily new cases per 100,000 inhabitants. First, we observed that the mobility reported by Google is directly related to government measures: the higher the level of restrictive measures, the lower the mobility index. Then, we analyze the influence of mobility reduction on the growth/decrease speed of the 7-day average of new cases per 100,000 inhabitants (P7) and show that high levels of mobility reduction lead to a decrease in the index. Finally, we related the required duration of mobility restrictions with the P7 maximum and also point out the risk of lifting the measures too early.