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.

Vaccine is supposed to be the most effective means to prevent COVID-19 as it may not only save lives but also reduce productivity loss due to resuming pre-pandemic activities. Providing the results of economic evaluation for mass vaccination is paramount important for all stakeholders worldwide. We developed a Markov decision tree for the economic evaluation of mass vaccination against COVID-19. The effectiveness of reducing outcomes after the administration of three COVID-19 vaccines (BNT162b2 (Pfizer-BioNTech), mRNA-1273 (Moderna), and AZD1222 (Oxford-AstraZeneca)) were modelled with empirical parameters obtained from literatures. The direct cost of vaccine and COVID-19 related medical cost, the indirect cost of productivity loss due to vaccine jabs and hospitalization, and the productivity loss were accumulated given different vaccination scenarios. We reported the incremental cost-utility ratio and benefit/cost (B/C) ratio of three vaccines compared to no vaccination with a probabilistic approach. Moderna and Pfizer vaccines won the greatest effectiveness among the three vaccines under consideration. After taking both direct and indirect costs into account, all of the three vaccines dominated no vaccination strategy. The results of B/C ratio show that one dollar invested in vaccine would have USD $13, USD $23, and USD $28 in return for Moderna, Pfizer, and AstraZeneca, respectively when health and education loss are considered. The corresponding figures taking value of the statistical life into account were USD $176, USD $300, and USD $443. Mass vaccination against COVID-19 with three current available vaccines is cost-saving for gaining more lives and less cost incurred.

It is known that the risk of stroke in patients with traumatic brain injury might be increased. However, the relationship between mild traumatic brain injury and ischemic stroke has never been established. We conducted a study of patients in Taiwan with mild traumatic brain injury to evaluate if they had a higher risk of stroke compared with the general population. We utilized a sampled National Health Insurance claims database containing one million beneficiaries. We followed all adult beneficiaries older than 18 years from January 1, 2007 to December 31, 2010 to determine if they were diagnosed with ischemic stroke. We further identified patients with mild traumatic brain injury and compared their risk of ischemic stroke with the general population. We identified 24,905 patients with mild traumatic brain injury and 719,811 patients without mild traumatic brain injury. After controlling for age, gender, urbanization level, socioeconomic status, diabetes, hypertension, coronary artery disease, hyperlipidemia, history of alcohol intoxication, malignancies, heart failure, atrial fibrillation, smoking, obesity, epilepsy, peripheral artery disease and Charlson Comorbidity Index score, the adjusted hazard ratio for ischemic stroke was 1.46 (95% confidence interval, 1.33—1.62). Mild traumatic brain injury is an independent significant risk factor for ischemic stroke.

Household transmission is responsible for the subsequent outbreak of community-acquired COVID-19. The aim of this study was to elucidate the household transmission mode and to further estimate effective and basic reproductive number with and without non-pharmaceutical interventions (NPIs). A total of 26 households with 39 family contacts between January, 2020 and February, 2021 in Taiwan were enrolled for analysis. The Becker’s chain binomial model was used to analyze the probabilities of being infected and escaped from SARS-COV-2 before and after January 1st, 2021, which were further converted to estimating basic reproductive numbers in the absence of NPIs. The likelihood of leading to the subsequent community-acquired outbreak given NPIs was further assessed. The secondary attack rate was 46.2%. Given the saturated Greenwood mode selected as the best fitted model, the probability of infected and escaped from COVID-19 within household was estimated as 44.4% (95% CI: 5.0%-53.7%) and 55.7% (95% CI: 46.3%-65.0%), respectively. In the second period of early 2021, the infected probability was increased to 58.3% (95% CI: 12.7%-90.0%)) and the escape probability was lowered to 41.7% (95% CI: 0.0%-86.9%)). The corresponding basic reproductive numbers (R0) increased from 4.29 in the first period to 6.73 in the second period without NPIs. However, none of subsequent community-acquired outbreak was noted in Taiwan given very effective NPIs in both periods. The proposed method and results are useful for designing household-specific containment measures and NPIs to stamp out a large-scale community-acquired outbreak as demonstrated in Taiwan.

Conflicting results have been obtained by studies attempting to assess the risks of ischemic stroke in patients with burn injury, while the long-term risk of stroke in survivors of burn injury remains unexplored. We evaluated whether the risk of ischemic stroke in patients hospitalized with burn injury in Taiwan is higher when compared to the general population. The data from one million National Health Insurance (NHI) adult beneficiaries were evaluated from January 1, 2005 until December 31, 2012 to identify those who developed ischemic stroke. Each identified patient with burn injury was matched with one hundred unexposed patients based on a high-dimensional propensity score. Cox regression models were applied to compare the risks of the development of ischemic stroke in the matched cohorts. A total of 743,237 patients were enrolled. After matching, 1,763 burn injury patients and 176,300 unexposed patients were selected and compared. The adjusted hazard ratio of ischemic stroke was significantly increased in burn injury patients (1.84; 95 % CI, 1.43–2.36). A subgroup analysis based on patients who survived longer than 12 months in the matched cohort also revealed higher hazard ratio in the burn injury patients (1.54; 95 % CI, 1.11–2.13). The risk of ischemic stroke is significantly higher in patients hospitalized with burn injury than in the general population, and these risks may extend longer than expected.

A “Public Health Emergency of International Concern (PHEIC)” monkeypox outbreak was declared by the World Health Organization on 23 June 2022. More than 16,000 monkeypox cases were reported in more than 75 countries across six regions as of July 25. The Bayesian SIR (Susceptible–Infected–Recovered) model with the directed acyclic graphic method was used to estimate the basic/effective reproductive number (R₀/R_e) and to assess the epidemic spread of monkeypox across the globe. The maximum estimated R₀/R_e was 1.16 (1.15–1.17), 1.20 (1.20–1.20), 1.34 (1.34–1.35), 1.33 (1.33–1.33) and 2.52 (2.41–2.66) in the United States, Spain, Brazil, the United Kingdom and the Democratic Republic of the Congo, respectively. The values of R₀/R_e were below 1 after August 2022. The estimated infectious time before isolation ranged from 2.05 to 2.74 days. The PHEIC of the global spreading of human monkeypox has been contained so as to avoid a pandemic in the light of the reasoning-based epidemic model assessment.