Global new coronavirus propagation prediction method based on optimized SEIRD model

Abstract

The invention discloses a global new coronavirus propagation prediction method based on an optimized SEIRD model, and relates to the technical field of infectious disease data processing, and the method comprises the steps: A, collecting data, and building an improved SEIRD cabin model on the basis of an epidemiological SEIR model: 1, increasing the index of latent crowd infection rate, subdividing the susceptible population conversion rate in the SEIR model into a latent population infection rate and a definite population infection rate; 2, subdividing the removal rate in the SEIR model intoa death rate and a cure rate; 3, expressing the cure rate and the death rate as a time sequence function of time t; dividing crowds in the bin into five types, namely susceptible people, symptomatic latent infected people, symptomatic infected people, cured people and dead people; B, respectively carrying out parameter estimation and model fitting on the model according to a least square method, estimating an inflection point and an end date of an epidemic situation, and carrying out model inspection by using actual data. The method has the advantages of accurate prediction and good reliability.

Description

technical field [0001] The present invention relates to the technical field of infectious disease data processing, in particular to a method for predicting the spread of a global novel coronavirus based on an optimized SEIRD model. Background technique [0002] Since the World Health Organization declared COVID-19 a global pandemic on March 11, 2020, as of September 10, 2020, the cumulative number of confirmed cases of COVID-19 worldwide has exceeded 27.69 million, and the cumulative number of deaths has exceeded 900,000. What is even more worrying is that although countries have adopted different levels of epidemic prevention measures, the global epidemic situation does not seem to have improved. Due to the complexity of the new coronavirus, especially the characteristics of the long incubation period and the concealment of asymptomatic infection, the epidemic prevention and control Therefore, establishing a reasonable mathematical model, scientifically analyzing the transm...

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Problems solved by technology

[0003] In virus transmission dynamics, complex network transmission models (SI, SIS, SIR, SEIR, etc.) are widely used. At present, a lot of work has been done on the 2019-nCoV epidemic. Some articles use segmented curve fitting, The characteristics of the spread of the epidemic in different periods are summarized. Some articles use the SIS model to study the impact of the initial value on the stable point. Based on the SEIR model, the article estimated the reproduction number of 2019-nCoV according to the development trend before January 25, 2020, and predicted the development of the epidemic. Some articles revised the SEIR model to subdivide the transmission population into susceptible There are 6 types of population, asymptomatic population during the incubation period, and natural immune population. For the first time, the phenomenon of self-healing during the incubation period is considered. Some articles further subdivide the population into 8 categories, and give parameter estimates based on general infectious diseases. The parameters are calculated using EpisIX software. The solution and sensitivity analysis have been carried out. These studies have made important contributions to the modeling analysis of the early stage of the epidemic, but there are still some shortcomings and room for improvement, such as: too many parameters will lead to overfitting, and the system will not remove the crowd. Segmentation leads to too extensive predictions, etc. At the same time, with the deepening of global research on the new coronavirus, the incubation period, especially the asymptomatic incubation period, has been paid more and more attention to the infectious characteristics and hazards, and is considered to be a hidden danger of triggering a new round of outbreaks One, the corresponding mathematical model should also strengthen and further refine the consideration of the latency parameters

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