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Modeling of the Long-Term Epidemic Dynamics of COVID-19 in the United States.
Huang, Derek; Tao, Huanyu; Wu, Qilong; Huang, Sheng-You; Xiao, Yi.
  • Huang D; Wuhan Britain-China School, No.10 Gutian Rd., Qiaokou District, Wuhan 430022, China.
  • Tao H; Institute of Biophysics, School of Physics, Huazhong University of Science and Technology, Wuhan 430074, China.
  • Wu Q; Institute of Biophysics, School of Physics, Huazhong University of Science and Technology, Wuhan 430074, China.
  • Huang SY; Institute of Biophysics, School of Physics, Huazhong University of Science and Technology, Wuhan 430074, China.
  • Xiao Y; Institute of Biophysics, School of Physics, Huazhong University of Science and Technology, Wuhan 430074, China.
Int J Environ Res Public Health ; 18(14)2021 07 16.
Artículo en Inglés | MEDLINE | ID: covidwho-1314656
ABSTRACT
Coronavirus 2019 (COVID-19) is causing a severe pandemic that has resulted in millions of confirmed cases and deaths around the world. In the absence of effective drugs for treatment, non-pharmaceutical interventions are the most effective approaches to control the disease. Although some countries have the pandemic under control, all countries around the world, including the United States (US), are still in the process of controlling COVID-19, which calls for an effective epidemic model to describe the transmission dynamics of COVID-19. Meeting this need, we have extensively investigated the transmission dynamics of COVID-19 from 22 January 2020 to 14 February 2021 for the 50 states of the United States, which revealed the general principles underlying the spread of the virus in terms of intervention measures and demographic properties. We further proposed a time-dependent epidemic model, named T-SIR, to model the long-term transmission dynamics of COVID-19 in the US. It was shown in this paper that our T-SIR model could effectively model the epidemic dynamics of COVID-19 for all 50 states, which provided insights into the transmission dynamics of COVID-19 in the US. The present study will be valuable to help understand the epidemic dynamics of COVID-19 and thus help governments determine and implement effective intervention measures or vaccine prioritization to control the pandemic.
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Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Estudio observacional Tópicos: Covid persistente / Vacunas Límite: Humanos País/Región como asunto: America del Norte Idioma: Inglés Año: 2021 Tipo del documento: Artículo País de afiliación: Ijerph18147594

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Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Asunto principal: COVID-19 Tipo de estudio: Estudio observacional Tópicos: Covid persistente / Vacunas Límite: Humanos País/Región como asunto: America del Norte Idioma: Inglés Año: 2021 Tipo del documento: Artículo País de afiliación: Ijerph18147594