Next Article in Journal
The Dynamics of Respiratory Microbiota during Mechanical Ventilation in Patients with Pneumonia
Next Article in Special Issue
Backcalculating the Incidence of Infection with COVID-19 on the Diamond Princess
Previous Article in Journal
Physical, Psychological, and Social Factors Associated with Exacerbation-Related Hospitalization in Patients with COPD
Previous Article in Special Issue
Potential Rapid Diagnostics, Vaccine and Therapeutics for 2019 Novel Coronavirus (2019-nCoV): A Systematic Review
Open AccessFeature PaperArticle

Epidemiological Identification of A Novel Pathogen in Real Time: Analysis of the Atypical Pneumonia Outbreak in Wuhan, China, 2019–2020

1
Graduate School of Medicine, Hokkaido University, Kita 15 Jo Nishi 7 Chome, Kita-ku, Sapporo-shi, Hokkaido 060-8638, Japan
2
Mathematical Institute, University of Oxford, Andrew Wiles Building, Radcliffe Observatory Quarter, Woodstock Road, Oxford OX2 6GG, UK
3
Christ Church, University of Oxford, St Aldates, Oxford OX1 1DP, UK
4
CREST, Japan Science and Technology Agency, Honcho 4-1-8, Kawaguchi, Saitama 332-0012, Japan
*
Author to whom correspondence should be addressed.
These authors equally contributed to this work.
J. Clin. Med. 2020, 9(3), 637; https://doi.org/10.3390/jcm9030637
Received: 8 February 2020 / Revised: 20 February 2020 / Accepted: 24 February 2020 / Published: 27 February 2020
Virological tests have now shown conclusively that a novel coronavirus is causing the 2019–2020 atypical pneumonia outbreak in Wuhan, China. We demonstrate that non-virological descriptive characteristics could have determined that the outbreak is caused by a novel pathogen in advance of virological testing. Characteristics of the ongoing outbreak were collected in real time from two medical social media sites. These were compared against characteristics of eleven pathogens that have previously caused cases of atypical pneumonia. The probability that the current outbreak is due to “Disease X” (i.e., previously unknown etiology) as opposed to one of the known pathogens was inferred, and this estimate was updated as the outbreak continued. The probability (expressed as a percentage) that Disease X is driving the outbreak was assessed as over 29% on 31 December 2019, one week before virus identification. After some specific pathogens were ruled out by laboratory tests on 5 January 2020, the inferred probability of Disease X was over 49%. We showed quantitatively that the emerging outbreak of atypical pneumonia cases is consistent with causation by a novel pathogen. The proposed approach, which uses only routinely observed non-virological data, can aid ongoing risk assessments in advance of virological test results becoming available. View Full-Text
Keywords: epidemic; causation; Bayes’ theorem; diagnosis; prediction; statistical model epidemic; causation; Bayes’ theorem; diagnosis; prediction; statistical model
Show Figures

Figure 1

MDPI and ACS Style

Jung, S.-M.; Kinoshita, R.; Thompson, R.N.; Linton, N.M.; Yang, Y.; Akhmetzhanov, A.R.; Nishiura, H. Epidemiological Identification of A Novel Pathogen in Real Time: Analysis of the Atypical Pneumonia Outbreak in Wuhan, China, 2019–2020. J. Clin. Med. 2020, 9, 637.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop