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Individual-based COVID-19 Modeling, Parameter Estimation, And Variance Metric Analysis

Posted on:2021-11-15Degree:MasterType:Thesis
Country:ChinaCandidate:C XuFull Text:PDF
GTID:2510306494992839Subject:Computer technology
Abstract/Summary:PDF Full Text Request
Since the outbreak of COVID-19 in China until the end of November 2020,more than 80,000 cases have been confirmed and more than 4,000 deaths have been reported.With the improvement of the epidemic prevention situation,the current domestic epidemic prevention and control task has become to prevent imported cases and the rebound of sporadic domestic cases.Therefore,how to prevent and control the local transmission of COVID-19 is an urgent problem to be solved for the occurrence of sporadic cases under normal conditions.Based on the analysis of the transmission characteristics of COVID-19 epidemic,this paper adopted the method of mathematical modeling to explore the effectiveness of epidemic prevention and control measures under normal conditions.In this study,the social contact network was used to simulate the interconnection between people to construct an individual-based model,which more truly reflected the evolution process of the local transmission of COVID-19 infectious diseases.At the same time,we have considered important infectious disease prevention and control measures,such as tracing and isolating close contacts and restricting social contact between people.We have proposed three levels of response measures to gradually strengthen the control.Approximate Bayesian Computation(ABC)is an effective method to estimate the above model parameters.The key step is to calculate the difference between the simulated data and the observed data.We analyzed and evaluated the effects of applying various difference measures to the ABC method,and used the improved ABC method for parameter estimation of the model.The simulation of the transmission of COVID-19 epidemic on the contact network with the intervention of the proposed control measures was realized by computer programming,and the state changes of each individual at different moments were recorded.Based on the simulation results,we concluded that the isolation of infected cases and close contacts alone cannot control the local transmission of COVID-19,and there is still a risk of a second outbreak.Two-layer close contact tracing and quarantine measures can significantly reduce the outbreak size.To effectively eliminate daily new infections in a short period of time,contact between individuals must be reduced.This study is helpful to provide suggestions for the prevention and control of COVID-19 under normal conditions,and can also provide important theoretical and quantitative basis for targeted measures for the prevention and control of other emergent major infectious diseases.
Keywords/Search Tags:COVID-19, Individual-Based Model, Contact network, Parameter estimation, Discrepancy measure
PDF Full Text Request
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