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_91
Snippet: predicted that the date when the number of patients in the hospital N t reaches its peak is Feb 11th, which is consistent with the real world situation. Later, the forecasting results fluctuated but were overall stable and close to the true observation. Meanwhile, we predict that the first zero point Z 1 will arrive between the end of Feb and the beginning of March. And the second zero point Z 2 will arrive at mid-March to mid-April. We also chec.....
Document: predicted that the date when the number of patients in the hospital N t reaches its peak is Feb 11th, which is consistent with the real world situation. Later, the forecasting results fluctuated but were overall stable and close to the true observation. Meanwhile, we predict that the first zero point Z 1 will arrive between the end of Feb and the beginning of March. And the second zero point Z 2 will arrive at mid-March to mid-April. We also checked the robustness of our model under different time windows and found that the selection of the time window has little effect on the prediction of turning points. As a prediction model for the task of early warning of a new epidemic, our prediction model is proved to be quite efficient.
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