Risk map of the novel coronavirus (2019-nCoV) in China: proportionate control is needed
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Abstract
Background
China is running a national level antivirus campaign against the novel coronavirus (2019-nCoV). Strict control measures are being enforced in either the populated areas and remote regions. While the virus is closed to be under control, tremendous economic loss has been caused.
Methods and findings
We assessed the pandemic risk of 2019-nCoV for all cities/regions in China using the random forest algorithm, taking into account the effect of five factors: the accumulative and increased numbers of confirmed cases, total population, population density, and GDP. We defined four levels of the risk, corresponding to the four response levels to public health emergencies in China. The classification system has good consistency among cities in China, as the error rate of the confusion matrix is 1.58%.
Conclusions
The pandemic risk of 2019-nCoV is dramatically different among the 442 cities/regions. We recommend to adopt proportionate control policy according to the risk level to reduce unnecessary economic loss.
Article activity feed
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SciScore for 10.1101/2020.02.16.20023838: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank…
SciScore for 10.1101/2020.02.16.20023838: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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