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_9
Snippet: Similarity 2: time-evolving Gaussian curves. The family of curves we use for expected deaths over time is identical to that of the IHME model. Specifically, we assume that expected daily death rates can be locally approximated by a three-parameter curve that is proportional to a Gaussian kernel. This approximation is local in the sense that the curve's three parameters are allowed to evolve in time as a function of state-level covariates. Just as.....
Document: Similarity 2: time-evolving Gaussian curves. The family of curves we use for expected deaths over time is identical to that of the IHME model. Specifically, we assume that expected daily death rates can be locally approximated by a three-parameter curve that is proportional to a Gaussian kernel. This approximation is local in the sense that the curve's three parameters are allowed to evolve in time as a function of state-level covariates. Just as in the IHME model, this results in fitted death-rate curves that, when plotted over time, can differ substantially from the shape of a single Gaussian. While epidemic curves do not resemble Gaussian curves, time-evolving Gaussian curves do provide a good fit to observed COVID-19 state-level death rates.
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