Clinical Symptoms of Dengue Infection among Patients from a Non-Endemic Area and Potential for a Predictive Model: A Multiple Logistic Regression Analysis and Decision Tree.

Under-recognition of dengue infection may lead to increased morbidity and mortality, whereas early detection is shown to help improve patient outcomes. Recent incidence and outbreak reports of dengue virus in the United States and other temperate regions where dengue was not typically seen have raised concerns regarding appropriate diagnosis and management by healthcare providers unfamiliar with the disease. This study aimed to describe self-reported clinical symptoms of dengue fever in a non-endemic cohort and to establish a clinically useful predictive algorithm based on presenting features that can assist in the early evaluation of potential dengue infection.