Maintenance Notice

Due to necessary scheduled maintenance, the JMIR Publications website will be unavailable from Wednesday, July 01, 2020 at 8:00 PM to 10:00 PM EST. We apologize in advance for any inconvenience this may cause you.

Who will be affected?

Accepted for/Published in: JMIR Public Health and Surveillance

Date Submitted: Mar 28, 2020
Date Accepted: Jun 29, 2020
Date Submitted to PubMed: Jun 29, 2020

The final, peer-reviewed published version of this preprint can be found here:

Using Open-Source Intelligence to Detect Early Signals of COVID-19 in China: Descriptive Study

Kpozehouen EB, Chen X, Zhu M, Macintyre CR

Using Open-Source Intelligence to Detect Early Signals of COVID-19 in China: Descriptive Study

JMIR Public Health Surveill 2020;6(3):e18939

DOI: 10.2196/18939

PMID: 32598290

PMCID: 7505682

Using open-source intelligence to detect early signals of COVID-19 in China, Descriptive study

  • Elizabeth Benedict Kpozehouen; 
  • Xin Chen; 
  • Mengyao Zhu; 
  • C Raina Macintyre

ABSTRACT

Background:

COVID-19 in China was first reported to the World Health Organization on December 31st 2019. The first cases were officially identified around December 8th 2019. The origin of COVID-19 is not confirmed, but half the early cases were linked to a seafood market in Wuhan. The first two documented cases did not attend the seafood market. News reports, social media and informal sources may contain information about outbreaks prior to formal notification.

Objective:

To identify early signals of pneumonia and/or severe acute respiratory illness (SARI) in China, prior to official recognition of the outbreak, using open source data.

Methods:

In order to capture early reports we searched an open source epidemic observatory, Epiwatch from 1st November 2019 in China, for severe acute respiratory illness (SARI) or pneumonia related illnesses. Google and Chinese search engine Baidu were used.

Results:

There was an increase in reports following the official notification of COVID 19 to WHO on December 31 2019, and a retracted report on December 26th 2019. A report of severe pneumonia was identified on November 22 2019 in Xiangyang, of a patient with severe pneumonia flown by helicopter to a Wuhan hospital.

Conclusions:

The lack of reports of a SARI outbreaks prior to December 31st, with a retracted report on December 26th suggests media censorship, given formal reports that cases began on December 8th. However, the findings also support relatively recent origin of COVID-19 in November 2019. The case reported on November 22nd was transferred to Wuhan approximately 1 incubation period before the first reported cases on December 8th, and should be further investigated, as only half of the early cases had exposure to the seafood market. It has since been reported that another case of COVID 19 has been retrospectively identified in Hubei on November 17th, confirming that the infection was present prior to December.


 Citation

Please cite as:

Kpozehouen EB, Chen X, Zhu M, Macintyre CR

Using Open-Source Intelligence to Detect Early Signals of COVID-19 in China: Descriptive Study

JMIR Public Health Surveill 2020;6(3):e18939

DOI: 10.2196/18939

PMID: 32598290

PMCID: 7505682

Download PDF


Request queued. Please wait while the file is being generated. It may take some time.

© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.