Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Breaking down of the healthcare system: Mathematical modelling for controlling the novel coronavirus (2019-nCoV) outbreak in Wuhan, China

View ORCID ProfileWai-Kit Ming, Jian Huang, Casper J. P. Zhang
doi: https://doi.org/10.1101/2020.01.27.922443
Wai-Kit Ming
1Department of Public Health and Preventive Medicine, School of Medicine, Jinan University, Guangzhou, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Wai-Kit Ming
  • For correspondence: wkming@connect.hku.hk
Jian Huang
2Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Casper J. P. Zhang
3School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Preview PDF
Loading

Abstract

A novel coronavirus pneumonia initially identified in Wuhan, China and provisionally named 2019-nCoV has surged in the public. In anticipation of substantial burdens on healthcare system following this human-to-human spread, we aim to scrutinise the currently available information and evaluate the burden of healthcare systems during this outbreak in Wuhan. We applied a modified SIR model to project the actual number of infected cases and the specific burdens on isolation wards and intensive care units, given the scenarios of different diagnosis rates as well as different public health intervention efficacy. Our estimates suggest the actual number of infected cases could be much higher than the reported, with estimated 26,701 cases (as of 28th January 2020) assuming 50% diagnosis rate if no public health interventions were implemented. The estimated burdens on healthcare system could be largely reduced if at least 70% efficacy of public health intervention is achieved.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
Back to top
PreviousNext
Posted January 28, 2020.
Download PDF
Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Breaking down of the healthcare system: Mathematical modelling for controlling the novel coronavirus (2019-nCoV) outbreak in Wuhan, China
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Breaking down of the healthcare system: Mathematical modelling for controlling the novel coronavirus (2019-nCoV) outbreak in Wuhan, China
Wai-Kit Ming, Jian Huang, Casper J. P. Zhang
bioRxiv 2020.01.27.922443; doi: https://doi.org/10.1101/2020.01.27.922443
Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Citation Tools
Breaking down of the healthcare system: Mathematical modelling for controlling the novel coronavirus (2019-nCoV) outbreak in Wuhan, China
Wai-Kit Ming, Jian Huang, Casper J. P. Zhang
bioRxiv 2020.01.27.922443; doi: https://doi.org/10.1101/2020.01.27.922443

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Microbiology
Subject Areas
All Articles
  • Animal Behavior and Cognition (4119)
  • Biochemistry (8828)
  • Bioengineering (6531)
  • Bioinformatics (23484)
  • Biophysics (11804)
  • Cancer Biology (9222)
  • Cell Biology (13336)
  • Clinical Trials (138)
  • Developmental Biology (7442)
  • Ecology (11424)
  • Epidemiology (2066)
  • Evolutionary Biology (15173)
  • Genetics (10452)
  • Genomics (14056)
  • Immunology (9187)
  • Microbiology (22198)
  • Molecular Biology (8823)
  • Neuroscience (47621)
  • Paleontology (351)
  • Pathology (1431)
  • Pharmacology and Toxicology (2493)
  • Physiology (3736)
  • Plant Biology (8090)
  • Scientific Communication and Education (1438)
  • Synthetic Biology (2224)
  • Systems Biology (6042)
  • Zoology (1254)