Selected article for: "death curve and epidemiological model"
Author: Spencer Woody; Mauricio Garcia Tec; Maytal Dahan; Kelly Gaither; Spencer Fox; Lauren Ancel Meyers; James G Scott
Title: Projections for first-wave COVID-19 deaths across the US using social-distancing measures derived from mobile phones
  • Document date: 2020_4_22
    • ID: 87lxnslh_8
    Snippet: Similarity 1: a statistical curve-fitting approach. Ours is not an epidemiological model, in the sense that we do not try to model disease transmission, nor do we use or attempt to estimate underlying epidemiological parameters like the basic reproductive rate or attack rate. Rather, our model is purely statistical: we are fitting a curve and a probabilistic error model to observed death rates in a state, and we are extrapolating from that curve......
    Document: Similarity 1: a statistical curve-fitting approach. Ours is not an epidemiological model, in the sense that we do not try to model disease transmission, nor do we use or attempt to estimate underlying epidemiological parameters like the basic reproductive rate or attack rate. Rather, our model is purely statistical: we are fitting a curve and a probabilistic error model to observed death rates in a state, and we are extrapolating from that curve. The advantage of this approach is that it does not require estimates of critical epidemiological parameters, some of which remain elusive. The disadvantage is that it cannot project longer-term epidemiological dynamics beyond the initial wave of mitigated transmission. For this reason, we do not use the model to make projections beyond a moderate (2-3 week) horizon.

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