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A farewell to R : time-series models for tracking and forecasting epidemics

Authors
  • Harvey, Andrew
  • Kattuman, Paul
Type
Published Article
Journal
Journal of The Royal Society Interface
Publisher
The Royal Society
Publication Date
Sep 29, 2021
Volume
18
Issue
182
Identifiers
DOI: 10.1098/rsif.2021.0179
PMID: 34583564
PMCID: PMC8479341
Source
PubMed Central
Keywords
Disciplines
  • Research Articles
License
Unknown

Abstract

The time-dependent reproduction number, R t , is a key metric used by epidemiologists to assess the current state of an outbreak of an infectious disease. This quantity is usually estimated using time-series observations on new infections combined with assumptions about the distribution of the serial interval of transmissions. Bayesian methods are often used with the new cases data smoothed using a simple, but to some extent arbitrary, moving average. This paper describes a new class of time-series models, estimated by classical statistical methods, for tracking and forecasting the growth rate of new cases and deaths. Very few assumptions are needed and those that are made can be tested. Estimates of R t , together with their standard deviations, are obtained as a by-product.

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