利用状态转移矩阵模型，根据中国的经验趋势预测全球主要疫区 COVID-19 的发展情况。
The prediction for development of COVID-19 in global major epidemic areas through empirical trends in China by utilizing state transition matrix model.
机构信息
Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University, School of Medicine, Shanghai, China.
Department of Pharmacy, Huashan Hospital, Fudan University, Shanghai, China.
出版信息
BMC Infect Dis. 2020 Sep 29;20(1):710. doi: 10.1186/s12879-020-05417-5.
BACKGROUND
Since pneumonia caused by coronavirus disease 2019 (COVID-19) broke out in Wuhan, Hubei province, China, tremendous infected cases has risen all over the world attributed to its high transmissibility. We aimed to mathematically forecast the inflection point (IFP) of new cases in South Korea, Italy, and Iran, utilizing the transcendental model from China.
METHODS
Data from reports released by the National Health Commission of the People's Republic of China (Dec 31, 2019 to Mar 5, 2020) and the World Health Organization (Jan 20, 2020 to Mar 5, 2020) were extracted as the training set and the data from Mar 6 to 9 as the validation set. New close contacts, newly confirmed cases, cumulative confirmed cases, non-severe cases, severe cases, critical cases, cured cases, and death were collected and analyzed. We analyzed the data above through the State Transition Matrix model.
RESULTS
The optimistic scenario (non-Hubei model, daily increment rate of - 3.87%), the cautiously optimistic scenario (Hubei model, daily increment rate of - 2.20%), and the relatively pessimistic scenario (adjustment, daily increment rate of - 1.50%) were inferred and modeling from data in China. The IFP of time in South Korea would be Mar 6 to 12, Italy Mar 10 to 24, and Iran Mar 10 to 24. The numbers of cumulative confirmed patients will reach approximately 20 k in South Korea, 209 k in Italy, and 226 k in Iran under fitting scenarios, respectively. However, with the adoption of different diagnosis criteria, the variation of new cases could impose various influences in the predictive model. If that happens, the IFP of increment will be earlier than predicted above.
CONCLUSION
The end of the pandemic is still inapproachable, and the number of confirmed cases is still escalating. With the augment of data, the world epidemic trend could be further predicted, and it is imperative to consummate the assignment of global medical resources to curb the development of COVID-19.
背景
自 2019 年新型冠状病毒肺炎（COVID-19）在湖北省武汉市爆发以来，由于其高传染性，全球感染病例数量急剧上升。我们旨在利用中国的超越模型，对韩国、意大利和伊朗的新发病例拐点（IFP）进行数学预测。
方法
从中国国家卫生健康委员会（2019 年 12 月 31 日至 2020 年 3 月 5 日）和世界卫生组织（2020 年 1 月 20 日至 2020 年 3 月 5 日）发布的报告中提取数据作为训练集，从 2020 年 3 月 6 日至 9 日的数据作为验证集。收集和分析新的密切接触者、新确诊病例、累计确诊病例、非重症病例、重症病例、危重症病例、治愈病例和死亡病例。我们通过状态转移矩阵模型对上述数据进行分析。
结果
从中国的数据推断出乐观情景（非湖北模式，日增长率为-3.87%）、谨慎乐观情景（湖北模式，日增长率为-2.20%）和相对悲观情景（调整，日增长率为-1.50%）。韩国的 IFP 将在 3 月 6 日至 12 日，意大利为 3 月 10 日至 24 日，伊朗为 3 月 10 日至 24 日。在拟合情景下，韩国的累计确诊患者数将分别达到约 20,000 例，意大利为 209,000 例，伊朗为 226,000 例。然而，由于采用了不同的诊断标准，新发病例的变化会对预测模型产生不同的影响。如果发生这种情况，增长的 IFP 将早于上述预测。
结论
大流行仍遥不可及，确诊病例数量仍在上升。随着数据的增加，全球疫情趋势可以进一步预测，完善全球医疗资源的分配以遏制 COVID-19 的发展迫在眉睫。
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