Predicting the cumulative number of cases for the COVID-19 epidemic in China from early data

Predicting the cumulative number of cases for the COVID-19 epidemic in China from early data

We model the COVID-19 coronavirus epidemic in China. We use early reported case data to predict the cumulative number of reported cases to a final size. The key features of our model are the timing of implementation of major public policies restricting social movement, the identification and isolati...

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Bibliographic Details
Main Authors: Zhihua Liu, Pierre Magal, usmane Seydi, Glenn Webb
Format: Article
Language:English
Published: AIMS Press 2020-04-01
Series:Mathematical Biosciences and Engineering
Subjects:
corona virus
reported and unreported cases
isolation
quarantine
public closings
epidemic mathematical model
Online Access:https://www.aimspress.com/article/doi/10.3934/mbe.2020172?viewType=HTML
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spelling doaj-cd05351718ee4aab9a3c875358d4ad382021-07-23T06:30:41ZengAIMS PressMathematical Biosciences and Engineering1551-00182020-04-011743040305110.3934/mbe.2020172Predicting the cumulative number of cases for the COVID-19 epidemic in China from early dataZhihua Liu0Pierre Magal1usmane Seydi 2Glenn Webb31. School of Mathematical Sciences, Beijing Normal University. Beijing 100875, China2. Université de Bordeaux, IMB, UMR 5251, F-33400 Talence, France 3. CNRS, IMB, UMR 5251, F-33400 Talence, France4. Département Tronc Commun, École Polytechnique de Thiès, Sénégal5. Mathematics Department, Vanderbilt University, Nashville, TN, USAWe model the COVID-19 coronavirus epidemic in China. We use early reported case data to predict the cumulative number of reported cases to a final size. The key features of our model are the timing of implementation of major public policies restricting social movement, the identification and isolation of unreported cases, and the impact of asymptomatic infectious cases.https://www.aimspress.com/article/doi/10.3934/mbe.2020172?viewType=HTMLcorona virusreported and unreported casesisolationquarantinepublic closingsepidemic mathematical model
collection DOAJ
language English
format Article
sources DOAJ
author Zhihua Liu
Pierre Magal
usmane Seydi
Glenn Webb
spellingShingle Zhihua Liu
Pierre Magal
usmane Seydi
Glenn Webb
Predicting the cumulative number of cases for the COVID-19 epidemic in China from early data
Mathematical Biosciences and Engineering
corona virus
reported and unreported cases
isolation
quarantine
public closings
epidemic mathematical model
author_facet Zhihua Liu
Pierre Magal
usmane Seydi
Glenn Webb
author_sort Zhihua Liu
title Predicting the cumulative number of cases for the COVID-19 epidemic in China from early data
title_short Predicting the cumulative number of cases for the COVID-19 epidemic in China from early data
title_full Predicting the cumulative number of cases for the COVID-19 epidemic in China from early data
title_fullStr Predicting the cumulative number of cases for the COVID-19 epidemic in China from early data
title_full_unstemmed Predicting the cumulative number of cases for the COVID-19 epidemic in China from early data
title_sort predicting the cumulative number of cases for the covid-19 epidemic in china from early data
publisher AIMS Press
series Mathematical Biosciences and Engineering
issn 1551-0018
publishDate 2020-04-01
description We model the COVID-19 coronavirus epidemic in China. We use early reported case data to predict the cumulative number of reported cases to a final size. The key features of our model are the timing of implementation of major public policies restricting social movement, the identification and isolation of unreported cases, and the impact of asymptomatic infectious cases.
topic corona virus
reported and unreported cases
isolation
quarantine
public closings
epidemic mathematical model
url https://www.aimspress.com/article/doi/10.3934/mbe.2020172?viewType=HTML
work_keys_str_mv AT zhihualiu predictingthecumulativenumberofcasesforthecovid19epidemicinchinafromearlydata
AT pierremagal predictingthecumulativenumberofcasesforthecovid19epidemicinchinafromearlydata
AT usmaneseydi predictingthecumulativenumberofcasesforthecovid19epidemicinchinafromearlydata
AT glennwebb predictingthecumulativenumberofcasesforthecovid19epidemicinchinafromearlydata
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