Selected article for: "contact transmission and infection rate"
Author: Philip J. Turk; Shih-Hsiung Chou; Marc A. Kowalkowski; Pooja P. Palmer; Jennifer S. Priem; Melanie D. Spencer; Yhenneko J. Taylor; Andrew D. McWilliams
Title: Modeling COVID-19 latent prevalence to assess a public health intervention at a state and regional scale
  • Document date: 2020_4_18
    • ID: j5o8it22_15
    Snippet: Given the major public health intervention implemented on March 26, we modify the SIR model for both the CRI and NC to accommodate this (denoted SIR-Int). SIR models with interventions can be simulated using the EpiModel package. We first fit the SIR model as before to the data up until March 26, and extracted the estimates of β and γ. After March 26, we retained the removal rate, but modified the infection rate. First, we set the pre-intervent.....
    Document: Given the major public health intervention implemented on March 26, we modify the SIR model for both the CRI and NC to accommodate this (denoted SIR-Int). SIR models with interventions can be simulated using the EpiModel package. We first fit the SIR model as before to the data up until March 26, and extracted the estimates of β and γ. After March 26, we retained the removal rate, but modified the infection rate. First, we set the pre-intervention probability of transmission equal to 0.015, which is consistent with other viral infectious diseases like SARS and AIDS [27, 28] . We then set the rate of contact so that the probability of transmission multiplied by the rate of contact equaled -. To simulate the observed intervention, using the default RK4 ODE solver, we affected the probability of transmission by iteratively decreasing the hazard ratio of infection given exposure to the intervention (step size of 0.0001) compared to no exposure, until the fitted infection curve yielded a maximum

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