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

View ORCID ProfileWai-Kit Ming, Jian Huang, View ORCID ProfileCasper 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
MD, PhD, MPH, MMSc, EMBA
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  • For correspondence: wkming{at}connect.hku.hk
Jian Huang
2MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, St Mary’s Campus, Imperial College London, Norfolk Place, London W2 1PG, UNITED KINGDOM
PhD, MPH
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Casper J. P. Zhang
3School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, CHINA
PhD, MPH
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  • ORCID record for Casper J. P. Zhang
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Abstract

Background 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.

Methods and Findings 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 (ICU), given the scenarios of different diagnosis rates as well as different public health intervention efficacy. Our estimates suggest, assuming 50% diagnosis rate if no public health interventions were implemented, that the actual number of infected cases could be much higher than the reported, with estimated 88,075 cases (as of 31st January, 2020), and projected burdens on isolation wards and ICU would be 34,786 and 9,346 respectively The estimated burdens on healthcare system could be largely reduced if at least 70% efficacy of public health intervention is achieved.

Conclusion The health system burdens arising from the actual number of cases infected by the novel coronavirus appear to be considerable if no effective public health interventions were implemented. This calls for continuation of implemented anti-transmission measures (e.g., closure of schools and facilities, suspension of public transport, lockdown of city) and further effective large-scale interventions spanning all subgroups of populations (e.g., universal facemask wear) aiming at obtaining overall efficacy with at least 70% to ensure the functioning of and to avoid the breakdown of health system.

Footnotes

  • Given that the probability of misdiagnosis is likely to be high in the early stage of the outbreak, we used the reported incidence between 0:00-24:00 on 28th Jan, 2020 (the most updated data when the analysis was performed).

  • Abbreviations

    ICU
    intensive care unit
    NHC
    National Health Commission
  • 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.
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    Posted January 30, 2020.
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    Breaking down of 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
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    Breaking down of 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

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