Modeling COVID-19 Incidence by the Renewal Equation after Removal of Administrative Bias and Noise

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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Detail(s)

Original languageEnglish
Article number540
Journal / PublicationBiology
Volume11
Issue number4
Online published31 Mar 2022
Publication statusPublished - Apr 2022
Externally publishedYes

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Abstract

The sanitary crisis of the past two years has focused the public’s attention on quantitative indicators of the spread of the COVID-19 pandemic. The daily reproduction number Rt, defined by the average number of new infections caused by a single infected individual at time t, is one of the best metrics for estimating the epidemic trend. In this paper, we provide a complete observation model for sampled epidemiological incidence signals obtained through periodic administrative measurements. The model is governed by the classic renewal equation using an empirical reproduction kernel, and subject to two perturbations: a time-varying gain with a weekly period and a white observation noise. We estimate this noise model and its parameters by extending a variational inversion of the model recovering its main driving variable Rt . Using Rt, a restored incidence curve, corrected of the weekly and festive day bias, can be deduced through the renewal equation. We verify experimentally on many countries that, once the weekly and festive days bias have been corrected, the difference between the incidence curve and its expected value is well approximated by an exponential distributed white noise multiplied by a power of the magnitude of the restored incidence curve. © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

Research Area(s)

  • administrative noise, COVID-19, exponential distribution, incidence curve, pandemic, renewal equation, reproduction kernel, time dependent reproduction number, variational inversion method

Citation Format(s)

Modeling COVID-19 Incidence by the Renewal Equation after Removal of Administrative Bias and Noise. / Alvarez, Luis; Morel, Jean-David; Morel, Jean-Michel.
In: Biology, Vol. 11, No. 4, 540, 04.2022.

Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

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