中国中部地区SARS-CoV-2传播监测指标研究卡塔尔世界杯8强波胆分析纵向趋势分析%A Post,Lori Ann %A Benishay,Elana T %A Moss,Charles B %A Murphy,Robert Leo %A Achenbach,Chad J %A Ison,Michael G %A Resnick,Danielle %A Singh,Lauren Nadya %A White,Janine %A Chaudhury,Azraa S %A botor,Michael J %A Welch,Sarah B %A oehke,James Francis %+ Buehler卫生政策和经济中心，西北大学范伯格医学院，芝加哥，伊利诺伊州，60611，美国，1209807107，lori.post@northwestern.edu %K SARS-CoV-2监测%K第二波%K波2 %K全球COVID-19监测%K中亚公共卫生监测%K中亚COVID-19 %K中亚监测指标%K动态面板数据%K广义时刻法%K中亚计量经济学%K中亚SARS-CoV-2 %K中亚COVID-19监测系统%K中亚COVID-19传播速度%K中亚COVID-19传播加速%K COVID-19传播COVID-19传播时滞%K COVID-19 7天滞后%K SARS-CoV-2 %K Arellano-Bond估计量;广义矩方法% K GMM % K亚美尼亚% K阿塞拜疆% K塞浦路斯% K法罗群岛% K格鲁吉亚% K直布罗陀% K哈萨克斯坦% K科索沃% K吉尔吉斯斯坦% K马其顿% K俄罗斯% K塔吉克斯坦土耳其% K土库曼斯坦% K乌兹别克斯坦% K COVID-19 % K监视% K纵向% K趋势% K趋势分析% K监控% K公共卫生% K传染病% K传输% K风险% K管理% K政策预防% D % K原始论文7 3.2.2021 % 9 2021% % J J互联网Res % G英语% X背景:引发全球COVID-19大流行的SARS-CoV-2病毒对中亚造成严重影响;2020年春季，该地区报告了大量病例和死亡病例。第二波COVID-19大流行目前正在突破中亚边界。公共卫生监测是必要的，以便为政策提供信息和指导领导人;然而，现有的监测解释了过去的传播，同时模糊了大流行的变化、感染率的上升以及COVID-19传播的持续存在。 Objective: The goal of this study is to provide enhanced surveillance metrics for SARS-CoV-2 transmission that account for weekly shifts in the pandemic, including speed, acceleration, jerk, and persistence, to better understand the risk of explosive growth in each country and which countries are managing the pandemic successfully. Methods: Using a longitudinal trend analysis study design, we extracted 60 days of COVID-19–related data from public health registries. We used an empirical difference equation to measure the daily number of cases in the Central Asia region as a function of the prior number of cases, level of testing, and weekly shift variables based on a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R. Results: COVID-19 transmission rates were tracked for the weeks of September 30 to October 6 and October 7-13, 2020, in Central Asia. The region averaged 11,730 new cases per day for the first week and 14,514 for the second week. Infection rates increased across the region from 4.74 per 100,000 persons to 5.66. Russia and Turkey had the highest 7-day moving averages in the region, with 9836 and 1469, respectively, for the week of October 6 and 12,501 and 1603, respectively, for the week of October 13. Russia has the fourth highest speed in the region and continues to have positive acceleration, driving the negative trend for the entire region as the largest country by population. Armenia is experiencing explosive growth of COVID-19; its infection rate of 13.73 for the week of October 6 quickly jumped to 25.19, the highest in the region, the following week. The region overall is experiencing increases in its 7-day moving average of new cases, infection, rate, and speed, with continued positive acceleration and no sign of a reversal in sight. Conclusions: The rapidly evolving COVID-19 pandemic requires novel dynamic surveillance metrics in addition to static metrics to effectively analyze the pandemic trajectory and control spread. Policy makers need to know the magnitude of transmission rates, how quickly they are accelerating, and how previous cases are impacting current caseload due to a lag effect. These metrics applied to Central Asia suggest that the region is trending negatively, primarily due to minimal restrictions in Russia. %M 33475513 %R 10.2196/25799 %U //www.mybigtv.com/2021/2/e25799 %U https://doi.org/10.2196/25799 %U http://www.ncbi.nlm.nih.gov/pubmed/33475513