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Containing COVID-19 Among 627,386 Persons in Contact With the Diamond Princess Cruise Ship Passengers Who Disembarked in Taiwan: Big Data Analytics
BACKGROUND: Low infection and case-fatality rates have been thus far observed in Taiwan. One of the reasons for this major success is better use of big data analytics in efficient contact tracing and management and surveillance of those who require quarantine and isolation. OBJECTIVE: We present her...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
JMIR Publications
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7202311/ https://www.ncbi.nlm.nih.gov/pubmed/32353827 http://dx.doi.org/10.2196/19540 |
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author | Chen, Chi-Mai Jyan, Hong-Wei Chien, Shih-Chieh Jen, Hsiao-Hsuan Hsu, Chen-Yang Lee, Po-Chang Lee, Chun-Fu Yang, Yi-Ting Chen, Meng-Yu Chen, Li-Sheng Chen, Hsiu-Hsi Chan, Chang-Chuan |
author_facet | Chen, Chi-Mai Jyan, Hong-Wei Chien, Shih-Chieh Jen, Hsiao-Hsuan Hsu, Chen-Yang Lee, Po-Chang Lee, Chun-Fu Yang, Yi-Ting Chen, Meng-Yu Chen, Li-Sheng Chen, Hsiu-Hsi Chan, Chang-Chuan |
author_sort | Chen, Chi-Mai |
collection | PubMed |
description | BACKGROUND: Low infection and case-fatality rates have been thus far observed in Taiwan. One of the reasons for this major success is better use of big data analytics in efficient contact tracing and management and surveillance of those who require quarantine and isolation. OBJECTIVE: We present here a unique application of big data analytics among Taiwanese people who had contact with more than 3000 passengers that disembarked at Keelung harbor in Taiwan for a 1-day tour on January 31, 2020, 5 days before the outbreak of coronavirus disease (COVID-19) on the Diamond Princess cruise ship on February 5, 2020, after an index case was identified on January 20, 2020. METHODS: The smart contact tracing–based mobile sensor data, cross-validated by other big sensor surveillance data, were analyzed by the mobile geopositioning method and rapid analysis to identify 627,386 potential contact-persons. Information on self-monitoring and self-quarantine was provided via SMS, and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) tests were offered for symptomatic contacts. National Health Insurance claims big data were linked, to follow-up on the outcome related to COVID-19 among those who were hospitalized due to pneumonia and advised to undergo screening for SARS-CoV-2. RESULTS: As of February 29, a total of 67 contacts who were tested by reverse transcription–polymerase chain reaction were all negative and no confirmed COVID-19 cases were found. Less cases of respiratory syndrome and pneumonia were found after the follow-up of the contact population compared with the general population until March 10, 2020. CONCLUSIONS: Big data analytics with smart contact tracing, automated alert messaging for self-restriction, and follow-up of the outcome related to COVID-19 using health insurance data could curtail the resources required for conventional epidemiological contact tracing. |
format | Online Article Text |
id | pubmed-7202311 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | JMIR Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-72023112020-05-08 Containing COVID-19 Among 627,386 Persons in Contact With the Diamond Princess Cruise Ship Passengers Who Disembarked in Taiwan: Big Data Analytics Chen, Chi-Mai Jyan, Hong-Wei Chien, Shih-Chieh Jen, Hsiao-Hsuan Hsu, Chen-Yang Lee, Po-Chang Lee, Chun-Fu Yang, Yi-Ting Chen, Meng-Yu Chen, Li-Sheng Chen, Hsiu-Hsi Chan, Chang-Chuan J Med Internet Res Original Paper BACKGROUND: Low infection and case-fatality rates have been thus far observed in Taiwan. One of the reasons for this major success is better use of big data analytics in efficient contact tracing and management and surveillance of those who require quarantine and isolation. OBJECTIVE: We present here a unique application of big data analytics among Taiwanese people who had contact with more than 3000 passengers that disembarked at Keelung harbor in Taiwan for a 1-day tour on January 31, 2020, 5 days before the outbreak of coronavirus disease (COVID-19) on the Diamond Princess cruise ship on February 5, 2020, after an index case was identified on January 20, 2020. METHODS: The smart contact tracing–based mobile sensor data, cross-validated by other big sensor surveillance data, were analyzed by the mobile geopositioning method and rapid analysis to identify 627,386 potential contact-persons. Information on self-monitoring and self-quarantine was provided via SMS, and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) tests were offered for symptomatic contacts. National Health Insurance claims big data were linked, to follow-up on the outcome related to COVID-19 among those who were hospitalized due to pneumonia and advised to undergo screening for SARS-CoV-2. RESULTS: As of February 29, a total of 67 contacts who were tested by reverse transcription–polymerase chain reaction were all negative and no confirmed COVID-19 cases were found. Less cases of respiratory syndrome and pneumonia were found after the follow-up of the contact population compared with the general population until March 10, 2020. CONCLUSIONS: Big data analytics with smart contact tracing, automated alert messaging for self-restriction, and follow-up of the outcome related to COVID-19 using health insurance data could curtail the resources required for conventional epidemiological contact tracing. JMIR Publications 2020-05-05 /pmc/articles/PMC7202311/ /pubmed/32353827 http://dx.doi.org/10.2196/19540 Text en ©Chi-Mai Chen, Hong-Wei Jyan, Shih-Chieh Chien, Hsiao-Hsuan Jen, Chen-Yang Hsu, Po-Chang Lee, Chun-Fu Lee, Yi-Ting Yang, Meng-Yu Chen, Li-Sheng Chen, Hsiu-Hsi Chen, Chang-Chuan Chan. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 05.05.2020. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included. |
spellingShingle | Original Paper Chen, Chi-Mai Jyan, Hong-Wei Chien, Shih-Chieh Jen, Hsiao-Hsuan Hsu, Chen-Yang Lee, Po-Chang Lee, Chun-Fu Yang, Yi-Ting Chen, Meng-Yu Chen, Li-Sheng Chen, Hsiu-Hsi Chan, Chang-Chuan Containing COVID-19 Among 627,386 Persons in Contact With the Diamond Princess Cruise Ship Passengers Who Disembarked in Taiwan: Big Data Analytics |
title | Containing COVID-19 Among 627,386 Persons in Contact With the Diamond Princess Cruise Ship Passengers Who Disembarked in Taiwan: Big Data Analytics |
title_full | Containing COVID-19 Among 627,386 Persons in Contact With the Diamond Princess Cruise Ship Passengers Who Disembarked in Taiwan: Big Data Analytics |
title_fullStr | Containing COVID-19 Among 627,386 Persons in Contact With the Diamond Princess Cruise Ship Passengers Who Disembarked in Taiwan: Big Data Analytics |
title_full_unstemmed | Containing COVID-19 Among 627,386 Persons in Contact With the Diamond Princess Cruise Ship Passengers Who Disembarked in Taiwan: Big Data Analytics |
title_short | Containing COVID-19 Among 627,386 Persons in Contact With the Diamond Princess Cruise Ship Passengers Who Disembarked in Taiwan: Big Data Analytics |
title_sort | containing covid-19 among 627,386 persons in contact with the diamond princess cruise ship passengers who disembarked in taiwan: big data analytics |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7202311/ https://www.ncbi.nlm.nih.gov/pubmed/32353827 http://dx.doi.org/10.2196/19540 |
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