Dynamic variations in and prediction of COVID-19 with omicron in the four first-tier cities of mainland China, Hong Kong, and Singapore.
Dynamic variations in and prediction of COVID-19 with omicron in the four first-tier cities of mainland China, Hong Kong, and Singapore.
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DOI：
10.3389/fpubh.2023.1228564
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发表时间：
2023
影响因子：
5.2
通讯作者：
Zhang, Hua
中科院分区：
文献类型：
--
作者：
Ni, Xiaohua;Sun, Bo;Hu, Zengyun;Cui, Qianqian;Zhang, Zhuo;Zhang, Hua
2019年末开始的新冠肺炎大流行，导致社会经济毁灭性崩溃，全球1000多万人死亡。最近的一项研究表明，新冠肺炎病例的模式将类似于一波小浪潮，而不是季节性激增。总的来说，新冠肺炎对城市的影响比对农村的影响更严重，特别是在人口密度较高的城市。本研究讨论了新冠肺炎传播的背景情况，包括人口数量和人口密度。此外，本文还应用了一种广泛使用的时间序列自回归滑动平均模型(ARIMA)来模拟和预测这六个城市“新冠肺炎”的变化。我们综合分析了内地中国(北京：北京、上海：上海、广州：广州和深圳：深圳)、香港(香港)、中国和新加坡(SG)四个一线城市2020年至2022年新冠肺炎的动态变化。主要结果表明，这六个城市具有各自的时间特征，这是由不同的防治措施决定的。内地中国的四个一线城市(即北京、上海、广州、深圳)，由于相同的“动态新冠肺炎”战略和严格的非药物干预(NPIs)，一波类似的变异。香港和新加坡有多个主要由输入案例引起的波动。ARIMA模型能够对6个城市的新冠肺炎疫情趋势进行准确的预测，为传染病疫情的短期变化预测提供了一种有用的方法，准确的预测对实施合理的防控措施具有重要价值。我们的主要结论表明，针对新冠肺炎大流行，防控措施应该动态调整，有机结合。进一步验证了数学模型的正确性，为疾病控制提供了重要的科学依据。
The COVID-19 pandemic, which began in late 2019, has resulted in the devastating collapse of the social economy and more than 10 million deaths worldwide. A recent study suggests that the pattern of COVID-19 cases will resemble a mini-wave rather than a seasonal surge. In general, COVID-19 has more severe impacts on cities than on rural areas, especially in cities with high population density. In this study, the background situation of COVID-19 transmission is discussed, including the population number and population density. Moreover, a widely used time series autoregressive integrated moving average (ARIMA) model is applied to simulate and forecast the COVID-19 variations in the six cities. We comprehensively analyze the dynamic variations in COVID-19 in the four first-tier cities of mainland China (BJ: Beijing, SH: Shanghai, GZ: Guangzhou and SZ: Shenzhen), Hong Kong (HK), China and Singapore (SG) from 2020 to 2022. The major results show that the six cities have their own temporal characteristics, which are determined by the different control and prevention measures. The four first-tier cities of mainland China (i.e., BJ, SH, GZ, and SZ) have similar variations with one wave because of their identical “Dynamic COVID-19 Zero” strategy and strict Non-Pharmaceutical Interventions (NPIs). HK and SG have multiple waves primarily caused by the input cases. The ARIMA model has the ability to provide an accurate forecast of the COVID-19 pandemic trend for the six cities, which could provide a useful approach for predicting the short-term variations in infectious diseases.Accurate forecasting has significant value for implementing reasonable control and prevention measures. Our main conclusions show that control and prevention measures should be dynamically adjusted and organically integrated for the COVID-19 pandemic. Moreover, the mathematical models are proven again to provide an important scientific basis for disease control.
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影响因子：
3.7
作者：
通讯作者：
--
DOI：
10.1016/s0140-6736(22)01190-4
发表时间：
2022-07-23
期刊：
Lancet (London, England)
影响因子：
--
作者：
通讯作者：
--
影响因子：
--
作者：
Jacoby, Keya B.;Hall-Clifford, Rachel;Whitney, Cynthia G.;Collins, Matthew H.
通讯作者：
Collins, Matthew H.
DOI：
10.1126/science.aaa4339
发表时间：
2015-03-13
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Heesterbeek H;Anderson RM;Andreasen V;Bansal S;De Angelis D;Dye C;Eames KT;Edmunds WJ;Frost SD;Funk S;Hollingsworth TD;House T;Isham V;Klepac P;Lessler J;Lloyd-Smith JO;Metcalf CJ;Mollison D;Pellis L;Pulliam JR;Roberts MG;Viboud C;Isaac Newton Institute IDD Collaboration
通讯作者：
Isaac Newton Institute IDD Collaboration
影响因子：
168.9
作者：
Chan, Jasper Fuk-Woo;Yuan, Shuofeng;Yuen, Kwok-Yung
通讯作者：
Yuen, Kwok-Yung