Griette, Quentin, Liu, Zhihua, Magal, Pierre and Thompson, Robin N. (2021) Real-time prediction of the end of an epidemic wave : COVID-19 in China as a case-study. In: Kumar Murty, V. and Wu, Jianhong, (eds.) Mathematics of Public Health: Proceedings of the Seminar on the Mathematical Modelling of COVID-19. Fields Institute Communications, 85 . Switzerland: Springer, Cham, pp. 173-195. ISBN 9783030850524

Preview

PDF WRAP-real-time-prediction-end-epidemic-wave-COVID-19-China-case-study-Thompson-2021.pdf - Accepted Version - Requires a PDF viewer. Download (1124Kb) | Preview

Request Changes to record.

Abstract

Forecasting when an epidemic wave is likely to end is an important component of disease management, allowing deployment of limited control resources to be planned efficiently. Here, we report an analysis that we conducted in real-time during the first COVID-19 epidemic wave in mainland China. We developed a mathematical model to construct bounds on the end date of the first epidemic wave there, assuming that strong quarantine and testing measures remained in place until the epidemic wave was confirmed over. We used reported data on case numbers in China from January 20 to April 9, 2020. We first developed an analytic approach, obtaining a formula describing the probability distribution of the epidemic wave end date using a combination of deterministic modelling and the theory of continuous-time Markov processes. Then, we ran simulations of an individual-based model to demonstrate that our analytic predictions were accurate. We found that the predicted end date of the first epidemic wave in China depended on the proportion of infected individuals that are symptomatic and appear in case notification data, as opposed to remaining asymptomatic throughout their courses of infection. We therefore provide an easy-to-use approach for predicting the ends of epidemic waves, as well as a clear demonstration that predicted end-of-epidemic times depend on the extent of asymptomatic infection. Our framework can be applied to predict the ends of epidemic waves during future outbreaks of a wide range of pathogens.

Item Type:	Book Item
Subjects:	R Medicine > RA Public aspects of medicine
Divisions:	Faculty of Science, Engineering and Medicine > Science > Mathematics
Library of Congress Subject Headings (LCSH):	COVID-19 (Disease) -- Mathematical models, COVID-19 (Disease) -- China, COVID-19 (Disease) -- Case studies, Epidemics -- Prevention -- Case studies
Series Name:	Fields Institute Communications
Publisher:	Springer, Cham
Place of Publication:	Switzerland
ISBN:	9783030850524
ISSN:	1069-5265
Book Title:	Mathematics of Public Health: Proceedings of the Seminar on the Mathematical Modelling of COVID-19
Editor:	Kumar Murty, V. and Wu, Jianhong
Official Date:	7 September 2021
Dates:	Date Event 7 September 2021 Available 1 September 2021 Accepted
Volume:	85
Page Range:	pp. 173-195
DOI:	10.1007/978-3-030-85053-1_8
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Restricted or Subscription Access
Copyright Holders:	Springer Nature Switzerland AG
Description:	ISSN: 1069-5265
Date of first compliant deposit:	22 March 2022
Date of first compliant Open Access:	22 March 2022
RIOXX Funder/Project Grant:	Project/Grant ID RIOXX Funder Name Funder ID 11871007 [NSFC] National Natural Science Foundation of China http://dx.doi.org/10.13039/501100001809 11811530272 [NSFC] National Natural Science Foundation of China http://dx.doi.org/10.13039/501100001809 11811530272 [CNRS] Centre National de la Recherche Scientifique http://dx.doi.org/10.13039/501100004794 UNSPECIFIED Fundamental Research Funds for the Central Universities http://dx.doi.org/10.13039/501100012226 UNSPECIFIED Agence Nationale de la Recherche in France UNSPECIFIED UNSPECIFIED Christ Church (University of Oxford) UNSPECIFIED

Request changes or add full text files to a record

Repository staff actions (login required)

View Item

Downloads