Given the recent outbreak of Sars-CoV-2, several countries started to seek different strategies to control contamination and minimize fatalities, which are usually the primary objectives for all strategies. Secondary objectives are related to economic factors, therefore ensuring that society would be able is to keep its essential activities and avoid supply disruptions. This paper presents an application of anonymized mobile phone users' location data to estimate population flow amongst cities with an origin-destination matrix. The work includes a clustering analysis of cities, which may enable policymakers (and epidemiologists) to develop public policies giving the appropriate consideration for each set of cities within a Province or State. Risk measures are included to analyze the severity of the spread among the clusters, which can be ranked. Then, intelligence can be obtained from the analysis, and some clusters could be isolated to avoid contagion while keeping their economic activities. Therefore, this analysis is reproducible for other states of Brazil and other countries and can be adapted for districts within a city, especially considering the possibility of a second wave COVID-19 pandemic.

鉴于最近爆发的 Sars-CoV-2，一些国家开始寻求不同的策略来控制污染并最大限度地减少死亡人数，这通常是所有策略的主要目标。次要目标与经济因素有关，因此确保社会能够保持其基本活动并避免供应中断。本文提出了一种应用匿名移动电话用户位置数据来估计具有出发地-目的地矩阵的城市之间的人口流动的方法。这项工作包括对城市的聚类分析，这可以使政策制定者（和流行病学家）在制定公共政策时适当考虑省或州内的每组城市。其中包括风险度量，用于分析集群之间传播的严重程度，并可以对其进行排名。然后，可以从分析中获得情报，并可以隔离一些集群以避免传染，同时保留其经济活动。因此，该分析对于巴西其他州和其他国家是可重复的，并且可以适用于城市内的地区，特别是考虑到第二波 COVID-19 大流行的可能性。