Yuhan Zhu
ABSTRACT
Under such severe circumstances, accurately predicting the development trend of the epidemic is of great significance for subsequent intervention and control. This paper proposes an improved SEIRS dynamic model based on the infectious disease prediction model (SEIR model), which can accurately predict the development trend of the new coronavirus pneumonia. First, the Python simulation technology combined with the SEIRS model was used to predict the spread of Wuhan in the 40 days since the outbreak, and compared with the real data in Wuhan. After fully verifying the correctness and applicability of the model, the model was applied to Shanghai. Next, use Python simulation technology to predict the spread and end time of the epidemic in Shanghai, and set different control intensities by changing the parameter , and analyze the impact of different control start times and different control intensities on the new crown pneumonia epidemic. Finally, the experimental results are analyzed to propose corresponding epidemic prevention and control measures, and the model in this paper is extended to a wider range of application scenarios.
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