Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Apr 22, 2020
Date Accepted: Apr 30, 2020
Date Submitted to PubMed: Apr 30, 2020
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Containing COVID-19 among 627,386 Persons Contacting with Diamond Princess Cruise Ship Passengers Disembarked in Taiwan: Big Data Analytics
ABSTRACT
Background:
Low infection and case-fatality rate has been so far observed in Taiwan. One of major success is attributed to making a better use of big data analytics in efficient contacting tracing and management and surveillance of those who required quarantine and isolation.
Objective:
We present here a unique application with big data analytics to Taiwanese people who contacted with more than 3,000 passengers disembarked at Keelung dock, Taiwan for one-day tour on Jan. 31, 2020, five days before the outbreak of COVID-19 on the Diamond Princess cruise ship on Feb. 5 2020 after an index case identified on Jan. 20th.
Methods:
The smart contact tracing based mobile sensor data cross-validated by other big sensor surveillance data was used to identify 627,386 potential contact persons with the mobile geopositioning method and rapid analysis. Information on self-monitoring and self-quarantine was provided via short message service (SMS) message and SARS-CoV-2 test were offered for symptomatic contacts. National Health Insurance claimed big data were linked to follow up the outcome related to COVID-19 among those who were hospitalized due to pneumonia and advised to screen for SARS-CoV-2.
Results:
As of Feb. 29, total 67 contacts who were had been tested by RT-PCR were all negative and no confirmed COVID-19 cases were found. Less respiratory syndrome cases and pneumonia also found after the follow-up of the contact population compared with the general population until Mar. 10.
Conclusions:
Big data analytics with smart contact tracing, automated alert message for self-restriction, and the follow-up of the outcome related to COVID-19 using health insurance data could curtail the resources required for conventional epidemiological contact tracing.
Citation
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