Abstract
BackgroundLow 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.ObjectiveWe 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.MethodsThe 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.ResultsAs 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.ConclusionsBig 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.
Highlights
MethodsTaiwan has been acclaimed for a relatively low number of coronavirus disease (COVID-19) confirmed cases and case-fatality rates by its timely and fast response to the COVID-19 pandemic [1]
Taiwan activated the Central Epidemic Command Center (CECC) for the COVID-19 outbreak after the first case was confirmed on January 21, 2020, in Taiwan, and this center responsible for executing control policies including border control, surveillance, quarantine, and resource allocation to prevent the spread of COVID-19 in communities [2]
The conventional epidemiological contact tracing, which relies on personal interviews is labor-intensive and time-consuming, may not be feasible when dealing with a pandemic with rapid propagation such as COVID-19
Summary
MethodsTaiwan has been acclaimed for a relatively low number of coronavirus disease (COVID-19) confirmed cases and case-fatality rates by its timely and fast response to the COVID-19 pandemic [1]. Other contributory factors that are effective and efficient to contain transmission are quarantine, isolation, and surveillance of disease progression of COVID-19 after contact tracing. To achieve these two aims, a systematic and efficient big data method, using digital technology, sensor data, and claimed health insurance data, may strengthen the conventional contact tracing and disease surveillance and inform the following control measures or mitigation plan. The scientific society in Taiwan called for an innovative and integrated approach by making use of current digital technologies and big data on sensor and claimed health insurance to reach the aim of precision prevention for outbreak and surveillance of disease outcome among these contacts. 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
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
