Rapid surveillance of COVID-19 in the United States using a prospective space-time scan statistic: Detecting and evaluating emerging clusters
Rapid surveillance of COVID-19 in the United States using a prospective space-time scan statistic: Detecting and evaluating emerging clusters
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DOI：
10.1016/j.apgeog.2020.102202
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发表时间：
2020-05-01
影响因子：
4.9
通讯作者：
Delmelle, E. M.
中科院分区：
文献类型：
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作者：
Desjardins, M. R.;Hohl, A.;Delmelle, E. M.
2019冠状病毒病（COVID-19）于2019年12月在中国武汉首次发现，由严重急性呼吸道综合征冠状病毒2（SARS-CoV-2）引起。COVID-19是一种流行病，估计死亡率为1%至5%;根据各种来源，估计R-0为2. 2至6. 7。截至2020年3月28日，全球共有超过649，000例确诊病例和30，249例死亡病例。在美国，有超过115，500例病例和1891例死亡，这一数字可能会迅速增加。随着疫情的持续发展，检测COVID-19的聚集性至关重要，以更好地分配资源并改善决策。利用约翰霍普金斯大学提供的县级每日病例数据，我们使用SaTScan进行了前瞻性时空分析。我们检测到2020年1月22日至3月9日和2020年1月22日至3月27日期间美国县级COVID-19的统计学显著时空集群。时空前瞻性扫描统计检测到在我们的研究期结束时存在的“活跃”和新出现的集群-值得注意的是，在添加更新的病例数据时，又检测到18个集群。这些及时的结果可以告知公共卫生官员和决策者在哪里改善资源分配，检测地点，以及在哪里实施更严格的禁令和旅行禁令。随着更多的数据变得可用，统计数据可以被更新，以支持及时监测COVID-19，如这里所示。我们的研究是第一个利用时空统计来监测美国COVID-19的地理研究。
Coronavirus disease 2019 (COVID-19) was first identified in Wuhan, China in December 2019, and is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). COVID-19 is a pandemic with an estimated death rate between 1% and 5%; and an estimated R-0 between 2.2 and 6.7 according to various sources. As of March 28th, 2020, there were over 649,000 confirmed cases and 30,249 total deaths, globally. In the United States, there were over 115,500 cases and 1891 deaths and this number is likely to increase rapidly. It is critical to detect clusters of COVID-19 to better allocate resources and improve decision-making as the outbreaks continue to grow. Using daily case data at the county level provided by Johns Hopkins University, we conducted a prospective spatial-temporal analysis with SaTScan. We detect statistically significant space-time clusters of COVID-19 at the county level in the U.S. between January 22nd-March 9th, 2020, and January 22nd-March 27th, 2020. The space-time prospective scan statistic detected "active" and emerging clusters that are present at the end of our study periods - notably, 18 more clusters were detected when adding the updated case data. These timely results can inform public health officials and decision makers about where to improve the allocation of resources, testing sites; also, where to implement stricter quarantines and travel bans. As more data becomes available, the statistic can be rerun to support timely surveillance of COVID-19, demonstrated here. Our research is the first geographic study that utilizes space-time statistics to monitor COVID-19 in the U.S.