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Healthcare-resource-adjusted vulnerabilities towards the 2019-nCoV epidemic across China

Hanchu Zhou, Jiannan Yang, Kaicheng Tang, View ORCID ProfileQingpeng Zhang, Zhidong Cao, Dirk Pfeiffer, Daniel Dajun Zeng
doi: https://doi.org/10.1101/2020.02.11.20022111
Hanchu Zhou
1School of Data Science, City University of Hong Kong, Hong Kong, China
2School of Traffic and Transportation, Central South University, Changsha, China
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Jiannan Yang
1School of Data Science, City University of Hong Kong, Hong Kong, China
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Kaicheng Tang
1School of Data Science, City University of Hong Kong, Hong Kong, China
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Qingpeng Zhang
1School of Data Science, City University of Hong Kong, Hong Kong, China
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  • ORCID record for Qingpeng Zhang
  • For correspondence: qingpeng.zhang{at}cityu.edu.hk dajun.zeng{at}ia.ac.cn
Zhidong Cao
3The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China
4School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
5Shenzhen Artificial Intelligence and Data Science Institute (Longhua), Shenzhen, China
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Dirk Pfeiffer
6Department of Infectious Diseases and Public Health, City University of Hong Kong, Hong Kong, China
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Daniel Dajun Zeng
3The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China
4School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing, China
5Shenzhen Artificial Intelligence and Data Science Institute (Longhua), Shenzhen, China
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  • For correspondence: qingpeng.zhang{at}cityu.edu.hk dajun.zeng{at}ia.ac.cn
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Abstract

We integrate the human movement and healthcare resource data to identify cities with high vulnerability towards the 2019-nCoV epidemic with respect to available health resources. The results inform public health responses in multiple ways.

Competing Interest Statement

The authors have declared no competing interest.

Funding Statement

This work was supported in part by grants from the Ministry of Science and Technology (2016QY02D0305), National Natural Science Foundation of China (71621002, and 71972164), and Chinese Academy of Sciences (ZDRW-XH-2017-3).

Author Declarations

All relevant ethical guidelines have been followed; any necessary IRB and/or ethics committee approvals have been obtained and details of the IRB/oversight body are included in the manuscript.

Yes

All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.

Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

Yes

I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.

Yes

Data Availability

All data are available online (as indicated by the links in the manuscript).

Copyright 
The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted February 12, 2020.
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Healthcare-resource-adjusted vulnerabilities towards the 2019-nCoV epidemic across China
Hanchu Zhou, Jiannan Yang, Kaicheng Tang, Qingpeng Zhang, Zhidong Cao, Dirk Pfeiffer, Daniel Dajun Zeng
medRxiv 2020.02.11.20022111; doi: https://doi.org/10.1101/2020.02.11.20022111
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Healthcare-resource-adjusted vulnerabilities towards the 2019-nCoV epidemic across China
Hanchu Zhou, Jiannan Yang, Kaicheng Tang, Qingpeng Zhang, Zhidong Cao, Dirk Pfeiffer, Daniel Dajun Zeng
medRxiv 2020.02.11.20022111; doi: https://doi.org/10.1101/2020.02.11.20022111

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