Selected article for: "daily incidence and herd immunity"

Author: Roach, Jared C
Title: Empirical Model of Spring 2020 Decrease in Daily Confirmed COVID-19 Cases in King County, Washington
  • Cord-id: oql50xub
  • Document date: 2020_5_18
  • ID: oql50xub
    Snippet: Projections of the near future of daily case incidence of COVID-19 are valuable for informing public policy. Near-future estimates are also useful for outbreaks of other diseases. Short-term predictions are unlikely to be affected by changes in herd immunity. In the absence of major net changes in factors that affect reproduction number (R), the two-parameter exponential model should be a standard model - indeed, it has been standard for epidemiological analysis of pandemics for a century but in
    Document: Projections of the near future of daily case incidence of COVID-19 are valuable for informing public policy. Near-future estimates are also useful for outbreaks of other diseases. Short-term predictions are unlikely to be affected by changes in herd immunity. In the absence of major net changes in factors that affect reproduction number (R), the two-parameter exponential model should be a standard model - indeed, it has been standard for epidemiological analysis of pandemics for a century but in recent decades has lost popularity to more complex compartmental models. Exponential model should be routinely included in reports describing epidemiological models as a reference, or null hypothesis. Exponential models should be fitted separately for each epidemiologically distinct jurisdiction. They should also be fitted separately to time intervals that differ by any major changes in factors that affect R. Using an exponential model, incidence-count half-life is a better statistic than R. Here an example of the exponential model is applied to King County, Washington during Spring 2020. The parameters and predictions of this model have remained stable for at least 45 days and the accuracy of model predictions has outperformed models with more parameters.

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