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Epidemiological Identification of A Novel Pathogen in Real Time : Analysis of the Atypical Pneumonia Outbreak in Wuhan, China, 2019-2020
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| Title: | Epidemiological Identification of A Novel Pathogen in Real Time : Analysis of the Atypical Pneumonia Outbreak in Wuhan, China, 2019-2020 |
| Authors: | Jung, Sung-mok Browse this author | | Kinoshita, Ryo Browse this author | | Thompson, Robin N. Browse this author | | Linton, Natalie M. Browse this author | | Yang, Yichi Browse this author | | Akhmetzhanov, Andrei R. Browse this author | | Nishiura, Hiroshi Browse this author →KAKEN DB |
| Keywords: | epidemic | | causation | | Bayes' theorem | | diagnosis | | prediction | | statistical model |
| Issue Date: | Mar-2020 |
| Publisher: | MDPI |
| Journal Title: | Journal of clinical medicine |
| Volume: | 9 |
| Issue: | 3 |
| Start Page: | 637 |
| Publisher DOI: | 10.3390/jcm9030637 |
| Abstract: | 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. |
| Rights: | http://creativecommons.org/licenses/by/4.0/ |
| Type: | article |
| URI: | http://hdl.handle.net/2115/78421 |
| Appears in Collections: | 医学院・医学研究院 (Graduate School of Medicine / Faculty of Medicine) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
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