Your browser doesn't support javascript.
loading
Transmission in Latent Period Causes A Large Number of Infected People in the United States
Qinghe Liu; Junkai Zhu; Zhicheng Liu; Yuhao Zhu; Liuling Zhou; Zefei Gao; Deqiang Li; Yuanbo Tang; Xiang Zhang; Junyan Yang; Qiao Wang.
Afiliação
  • Qinghe Liu; Southeast University
  • Junkai Zhu; Southeast University
  • Zhicheng Liu; Southeast University
  • Yuhao Zhu; Erasmus School of Economics, Erasmus University Rotterdam, Rotterdam, the Netherlands
  • Liuling Zhou; Southeast University
  • Zefei Gao; Southeast University
  • Deqiang Li; Southeast Univesity
  • Yuanbo Tang; Southeast University
  • Xiang Zhang; Southeast University
  • Junyan Yang; Southeast University
  • Qiao Wang; Southeast University
Preprint em Inglês | medRxiv | ID: ppmedrxiv-20094086
ABSTRACT
The cumulative number of confirmed cases in the United States exceeded one million on 29 April 2020, becoming the country of the most serious pandemic in the world. We proposed a model to analyze the real situation and follow-up trend of the epidemic in the US. The proposed model divides the epidemic period into two phases, and includes three different categories of transmitters the latent population, the documented infectious population, and the undocumented infectious population. We use metapopulation network to simulate the spread of the COVID-19 in the US, and apply the Bayesian inference to estimate the key parameters of the model. We also perform component analysis and sensitivity analysis, researching the compositions of the people with COVID-19. The results show that the basic reproduction number in the early period of propagation is 4.06. As of April 13, 2020, only 45% (95% CI 35% - 73%) of symptom onset cases in the United States were documented. The incubation period of COVID-19 is 10.69 days (95% CI 10.02 - 11.74). If the current level of interventions is continued, the cumulative number of confirmed cases is expected to reach more than 1.7 million in July and continue to grow.
Licença
cc_by_nd
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Cohort_studies / Estudo prognóstico Idioma: Inglês Ano de publicação: 2020 Tipo de documento: Preprint
Texto completo: Disponível Coleções: Preprints Base de dados: medRxiv Tipo de estudo: Cohort_studies / Estudo prognóstico Idioma: Inglês Ano de publicação: 2020 Tipo de documento: Preprint
...