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Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) entered Brazil before travel restrictions and border closures were imposed. This study reports the characteristics of suspected and confirmed coronavirus disease 2019 (COVID-19) cases among symptomatic international travelers in Brazil and their contacts. Methods: The REDCap platform developed by the Brazilian Ministry of Health was analyzed to identify and investigate suspected cases of COVID-19 recorded during the period January 1 to March 20, 2020. The impact of Brazil's targeted approach to suspected cases from specific countries on epidemiological surveillance efforts during the early stages of the COVID-19 pandemic were analyzed. Results: Based on molecular RT-PCR tests, there were 217 (4.2%) confirmed, 1030 (20.1%) unconfirmed, 722 (14.1%) suspected, and 3157 (61.6%) non-investigated cases among travelers returning from countries included on the alert list for surveillance, as defined by the Ministry of Health. Among the 3372 travelers who went to countries not included on the alert list, there were 66 (2.0%) confirmed, 845 (25.3%) unconfirmed, 521 (15.6%) suspected, and 1914 (57.2%) non-investigated cases. A comparison of the characteristics of confirmed cases returning from alert and non-alert countries did not reveal a statistically significant difference in symptoms. Almost half of the hospitalized travelers with known travel dates and hospitalization status (53.6%) were inbound from countries not included on the alert list, and RT-PCR tests were reported for only 30.5%. Conclusions: Policies adopted at entry points to contain the introduction of SARS-CoV-2 in Brazil were not ideal. An analysis of the early response shows that surveillance of travelers, including testing strategies, data standards, and reporting systems, was insufficient.
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BACKGROUND: In 2011, the Centers for Disease Control and Prevention and the New Jersey Department of Health used the New Jersey Behavioral Risk Factor Survey (NJBRFS), a state component of the national Behavioral Risk Factor Surveillance System (BRFSS) to pilot a travel health module designed to collect population-based data on New Jersey residents travelling internationally. Our objective was to use this population-based travel health information to serve as a baseline to evaluate trends in US international travellers. METHODS: A representative sample of New Jersey residents was identified through a random-digit-dialing method and administered the travel health module, which asked five questions: travel outside of USA during the previous year; destination; purpose; if a healthcare provider was visited before travel and any travel-related illness. Additional health variables from the larger NJBRFS were considered and included in bivariate analyses and multiple logistic regression; weights were assigned to variables to account for survey design complexity. RESULTS: Of 4029 participants, 841 (21%) travelled internationally. Top destinations included Mexico (10%), Canada (9%), Dominican Republic (6%), Bahamas (5%) and Italy (5%). Variables positively associated with travel included foreign birth, ≥$75 000 annual household income, college education and no children living in the household. One hundred fifty (18%) of 821 travellers with known destinations went to high-risk countries; 40% were visiting friends and relatives and only 30% sought pre-travel healthcare. Forty-eight (6%) of 837 responding travellers reported travel-related illness; 44% visited high-risk countries. CONCLUSIONS: Approximately one in five NJBRFS respondents travelled internationally during the previous year, a sizeable proportion to high-risk destinations. Few reported becoming ill as a result of travel but almost one-half of those ill had travelled to high-risk destinations. Population-based surveillance data on travellers can help document trends in destinations, traveller type and disease prevalence and evaluate the effectiveness of disease prevention programmmes.