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Assessing effects of reopening policies on COVID-19 pandemic in Texas with a data-driven transmission model

infectious disease Modelling 2021年第1期6卷 461-473页

作者： Duo Yu Gen Zhu Xueying Wang Chenguang Zhang Babak Soltanalizadeh Xia Wang Sanyi Tang Hulin Wu Department of Biostatistics and Data Science The University of Texas Health Science Center at HoustonHoustonUSA School of Mathematics and Information Science Shaanxi Normal UniversityXi’anPR China

While the Coronavirus disease 2019(COVID-19)pandemic continues to threaten public health and safety,every state has strategically reopened the business in the United *** is urgent to evaluate the effect of reopening policies on the COVID-19 pandemic to help with the decision-making on the control measures and medical resource *** this study,a novel SEIR model was developed to evaluate the effect of reopening policies based on the real-world reported COVID-19 data in *** earlier reported data before the reopening were used to develop the SEIR model;data after the reopening were used for *** simulation results show that if continuing the“stay-at-home order”without reopening the business,the COVID-19 pandemic could end in December 2020 in *** the other hand,the pandemic could be controlled similarly as the case of noreopening only if the contact rate was low and additional high magnitude of control measures could be *** the control measures are only slightly enhanced after reopening,it could flatten the curve of the COVID-19 epidemic with reduced numbers of infections and deaths,but it might make the epidemic last *** on the reported data up to July 2020 in Texas,the real-world epidemic pattern is between the cases of the low and high magnitude of control measures with a medium risk of contact rate after *** this case,the pandemic might last until summer 2021 to February 2022 with a total of 4-10 million infected cases and 20,080e58,604 deaths.

关键词： COVID-19 pandemic SEIR model Texas state Reopening business infectious disease transmission

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