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_9
Snippet: is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.04.14.20063420 doi: medRxiv preprint S is the number of individuals that are susceptible to infection in the population, I is the number of individuals that are infected, and R is the number of individuals that are removed from the population via recovery and subsequent immunity or death from infection. This mutually exclusive and exhaustive.....
Document: is the (which was not peer-reviewed) The copyright holder for this preprint . https://doi.org/10.1101/2020.04.14.20063420 doi: medRxiv preprint S is the number of individuals that are susceptible to infection in the population, I is the number of individuals that are infected, and R is the number of individuals that are removed from the population via recovery and subsequent immunity or death from infection. This mutually exclusive and exhaustive partition is such that S + I + R = N, where N is the closed population size. We further assume all uninfected individuals are susceptible to infection. The transition flow is described by the arrows in the figure labeled with two rates. The parameter β is the infection rate and can be further decomposed as the product of the probability of transmission per contact and the rate of contact per person per unit time. γ is the removal rate.
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