Selected article for: "branching process model and local transmission"

Author: Alex Perkins; Sean M. Cavany; Sean M Moore; Rachel J Oidtman; Anita Lerch; Marya Poterek
Title: Estimating unobserved SARS-CoV-2 infections in the United States
  • Document date: 2020_3_18
  • ID: fb8mca1h_4
    Snippet: To estimate the extent of community transmission of SARS-CoV-2 in the US, we used a stochastic simulation model that combined importation and local transmission processes. We informed model parameters with estimates from other countries, where available (Table 1) , and estimated values of two unknown parameters by fitting the model to data on local reported deaths in the US (18). To model importation, we simulated observed and unobserved imported.....
    Document: To estimate the extent of community transmission of SARS-CoV-2 in the US, we used a stochastic simulation model that combined importation and local transmission processes. We informed model parameters with estimates from other countries, where available (Table 1) , and estimated values of two unknown parameters by fitting the model to data on local reported deaths in the US (18). To model importation, we simulated observed and unobserved imported infections based on the number and timing of imported cases reported in the US (19) and assumptions about the proportion of different infection outcomes (5, 20) . To model local transmission, we used a branching process model informed by estimates of the serial interval and reproduction number of SARS-CoV-2 from Singapore (3). Due to aggressive containment efforts there (12) , we considered our model to be a conservative representation of community transmission in the US. To relate our model's predictions to US data on reported cases and deaths, we also simulated the timing of symptom onset (3), case reporting (18), and death (21) , for simulated infections for which those outcomes occurred.

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