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PLoS One ; 14(12): e0225840, 2019.
Article in English | MEDLINE | ID: mdl-31805101

ABSTRACT

BACKGROUND: Dengue fever is endemic in tropical and subtropical areas, especially Southeast Asia. International air travel facilitates the spread of dengue across and within borders. To date, no predictive factors have been established for assessing risk of dengue among febrile travelers. METHODS: Since 2006, Taiwan has operated a program of infrared thermometer-based non-contact active surveillance at Taoyuan International Airport (TPE). All inbound passengers from dengue-endemic countries who are febrile (tympanic temperature ≥38°C) undergo routine laboratory testing for dengue. We analyzed clinical and epidemiological characteristics of all tested passengers entering Taiwan via TPE in 2011 to identify the predictive factors of dengue infection. RESULTS: In 2011, of the 3,719 febrile passengers from dengue-endemic countries, 74 (2.0%) had laboratory-confirmed dengue infection. Multivariable logistic regression analysis revealed that those who were aged ≥60 years (adjusted odds ratio [aOR], 8.7; 95% confidence interval [CI], 2.6-29.6) and had self-reported fever (aOR, 2.5; 95% CI, 1.5-4.1), skin rashes (aOR, 11.0; 95% CI, 3.4-35.1), or a tympanic temperature ≥39°C (aOR, 2.9; 95% CI, 1.7-4.9) were significantly more likely to have dengue (all p values < 0.05). Compared with travelers who stayed in dengue-endemic countries for ≤7 days, those who traveled 8-14, 15-21, 22-28, and ≥29 days were also more likely to be infected (aORs of 10.2, 14.9, 39.0 and 12.0, respectively). CONCLUSION: These clinical and epidemiological features can facilitate timely recognition and diagnosis of imported dengue in febrile inbound passengers and therefore help prevent domestic transmission of dengue virus.


Subject(s)
Airports , Dengue/epidemiology , Infrared Rays , Internationality , Population Surveillance , Thermometers , Travel , Adolescent , Adult , Child , Child, Preschool , Female , Humans , Infant , Infant, Newborn , Male , Middle Aged , Multivariate Analysis , Young Adult
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