论文标题
基于医学观察的2019-NCOV流行病的发展趋势的简单预测模型
A Simple Prediction Model for the Development Trend of 2019-nCov Epidemics Based on Medical Observations
论文作者
论文摘要
为了预测2019年冠状病毒（2019-NCOV）的发展趋势，我们建立了一个预测模型，以预测除河北省以外的中国诊断病例的数量。从1月25日至2020年1月29日，我们优化了6种预测模型，其中5个基于医学观察的数量，以预测确认诊断的高峰时间将在1月29日上午29年至2月2日至2月2日早上24:00之前出现。然后，我们跟踪了1月29日至1月31日的24点到1月31日的24点，发现数据的预测值与实际值的偏差很小，并且实际值始终保留在综合预测模型6所预测的范围内。因此，我们将披露此发现并将继续跟踪该模式是否可以维持该模式是否可以维持更长的时间。我们认为，医学观察案例数的变化可能有助于提前判断流行病的趋势。
In order to predict the development trend of the 2019 coronavirus (2019-nCov), we established an prediction model to predict the number of diagnoses case in China except Hubei Province. From January 25 to January 29, 2020, we optimized 6 prediction models, 5 of them based on the number of medical observations to predicts the peak time of confirmed diagnosis will appear on the period of morning of January 29 from 24:00 to February 2 before 5 o'clock 24:00. Then we tracked the data from 24 o'clock on January 29 to 24 o'clock on January 31, and found that the predicted value of the data on the 3rd has a small deviation from the actual value, and the actual value has always remained within the range predicted by the comprehensive prediction model 6. Therefore we discloses this finding and will continue to track whether this pattern can be maintained for longer. We believe that the changes medical observation case number may help to judge the trend of the epidemic situation in advance.
