Selected article for: "China epidemic and data point"

Author: Huiwen Wang; Yanwen Zhang; Shan Lu; Shanshan Wang
Title: Tracking and forecasting milepost moments of the epidemic in the early-outbreak: framework and applications to the COVID-19
  • Document date: 2020_3_24
  • ID: fyh8gjjl_79
    Snippet: second turning point that observed in reality. Since then, we have continuously tracked the rolling predictions, which have not yet changed much. points obtained with t 0 varying from Jan 29th to Feb 29th, 2020 and m = 5, respectively. Specifically, for the predicted first zero point Z 1 in Figure 3 (b), we divide the prediction results from these days into 5 intervals, which can be seen that the prediction results of the first zero point Z 1 are.....
    Document: second turning point that observed in reality. Since then, we have continuously tracked the rolling predictions, which have not yet changed much. points obtained with t 0 varying from Jan 29th to Feb 29th, 2020 and m = 5, respectively. Specifically, for the predicted first zero point Z 1 in Figure 3 (b), we divide the prediction results from these days into 5 intervals, which can be seen that the prediction results of the first zero point Z 1 are mainly concentrated on Mar 1st to 5th, which is consistent with the actual result. There is also a "pessimistic" prediction as a result of the sudden fluctuation of data on Feb 3rd, which predicted that the first zero point would arrive on Mar 17th. For the predicted second zero point Z 2 in Figure 3 (c), it can be seen that the second zero point will be reached from mid-March to mid-April. However, there is a prediction result that Z 2 will appear on May 11th, which is far away from other results. The reason for this uncommon result is that the starting point of this forecast is Jan 29th, when the epidemic situation in mainland China beyond Hubei was still in the outbreak period with E t still rising, I t very small, so the prediction result about the finish of the epidemic may not be accurate.

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