Author: Yi Li; Xianhong Yin; Meng Liang; Xiaoyu Liu; Meng Hao; Yi Wang
Title: A Note on COVID-19 Diagnosis Number Prediction Model in China Document date: 2020_2_23
ID: goqgv2cc_4
Snippet: Considering the limited number of data points and the complexity of the real situation, a simple but robust model is expected to work better than sophisticated epidemiology models. In this paper, we propose a robust model for next day diagnosis number predict. This model had excellent performance on prediction of infected patients in past few days. The prediction is expected to provide practical significance on social and economic application. & .....
Document: Considering the limited number of data points and the complexity of the real situation, a simple but robust model is expected to work better than sophisticated epidemiology models. In this paper, we propose a robust model for next day diagnosis number predict. This model had excellent performance on prediction of infected patients in past few days. The prediction is expected to provide practical significance on social and economic application. & # and its median aggregates were calculated (Fig.1) . It was observed that & # manifests a random fluctuation around a constant center. It is reasonable to assume that is a constant. The estimation of currently (Feb 10) is 0.904. A future diagnosis number formula is obtained based on this estimation:
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