Abstract

After the COVID-19 epidemic leveled off in China, many provinces have started to resume schooling. Long-term contact between students and teachers in such a closed environment in schooling can increase the possibility of the outbreak. Although the school closure can effectively alleviate the epidemic, large-scale students’ isolation not only causes social panic but also brings huge social and economic burden, so before the emergence of school epidemics, one should select and adopt more scientific prevention and control measures. In this study, according to the virus excretion of COVID-19 patients in the disease period, the infectious capacity of patients is redefined. After introducing it into the traditional suspected-exposed-infected-removed (SEIR) model, a continuous infection model that is more consistent with the actual transmission of COVID-19 patients is proposed. Secondly, the effective distance between students is calculated through real contact data. Based on the analysis of the effective distance, three types of isolation area prevention and control measures are proposed and compared with the recently proposed digital contact tracking prevention and control measures. Simulating the spread of COVID-19 in schools through real student contact data and continuous infection models, in order to compare the preventions and control effects of various prevention and control measures in the school epidemic situation, and evaluating the social influence of measures by accumulating the number of quarantines when prevention and control measures are adopted, we find that the COVID-19 can lead the cases to happen on a larger scale in the continuous infection model than in the traditional SEIR model, and the prevention and control measures verified in the continuous infection model are more convincing. Using digital contact tracking prevention and control measures in schools can achieve similar results to those in closed schools with the smallest number of quarantines. The research in this paper can help schools choose appropriate prevention and control measures, and the proposed continuous infection model can help researchers more accurately simulate the spread of COVID-19.

Highlights

  • Simulating the spread of COVID-19 in schools through real student contact data and continuous infection models, in order to compare the preventions and control effects of various prevention and control measures in the school epidemic situation, and evaluating the social influence of measures by accumulating the number of quarantines when prevention and control measures are adopted, we find that the COVID-19 can lead the cases to happen on a larger scale in the continuous infection model than in the traditional SEIR model, and the prevention and control measures verified in the continuous infection model are more convincing

  • 首先, 根据患者在患病期间病毒排出情况, 定 义患者在不同时间上的传染能力, 将其引入到传 统 SEIR 模型后提出连续感染模型

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Summary

Introduction

新型冠状病毒肺炎早期时空传播特征分析 Analysis on early spatiotemporal transmission characteristics of COVID-19 物理学报. 新型冠状病毒肺炎疫情确诊病例的统计分析及自回归建模 Statistical analysis and autoregressive modeling of confirmed coronavirus disease 2019 epidemic cases 物理学报. 新型冠状病毒肺炎的流行病学参数与模型 Epidemiological parameters and models of coronavirus disease 2019 物理学报. 评估新型冠状病毒地区防控效果的一种近似方法 Approximate method to evaluate the regional control efficacy of COVID-19 物理学报. 结果发 现, 相比于传统 SEIR 模型, 新冠肺炎在连续感染模型中会造成更大的病例规模, 在连续感染模型中验证的防 控措施更具有说服力. 虽然很多 研究通过传统易感-潜伏-传染-恢复 (SEIR) 模型并 考虑潜伏期传染性去仿真新冠肺炎的传播 [3], 但是 这些经典传染病数学模型与现实中病毒的传播依 旧存在很明显的差别.

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