ArticleEmerging infectious diseases2026
Using Routine Surveillance Data to Assess Dengue Virus Transmission Risk in Travelers Returning to the United States.
Article in Emerging infectious diseases, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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10 authors.
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Abstract
Dengue virus poses a growing global health threat, yet inconsistent local surveillance limits global risk assessments. We analyzed 10,530 travel-associated dengue cases among US travelers reported to ArboNET during January 2010-April 2024, involving travel to 128 countries. By using negative binomial and Poisson models, we developed country-specific thresholds (75th, 80th, 90th percentiles) to identify elevated travel-associated dengue risk. We applied a >10-case threshold in a 3-month period to improve specificity. The final dual-criteria method accurately identified high-risk periods, including sustained transmission in countries with limited official reporting, such as Cuba in 2022-2023. Threshold comparisons revealed a tradeoff between early detection and overclassification, whereas real-time and retrospective assessments revealed consistent high-risk signals. This traveler-based approach offers a timely, complementary method for travel-associated dengue risk detection, although timeliness might be reduced if reporting delays increase beyond our observations. Our findings support integrating travel surveillance into global dengue monitoring and preparedness efforts.
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