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Chikungunya, a mosquito-borne viral, acute febrile illness (AFI) is associated with polyarthralgia and polyarthritis. Differentiation from other AFI is difficult due to the non-specific presentation and limited availability of diagnostics. This 3-year study identified independent clinical predictors by day post-illness onset (DPO) at presentation and age-group that distinguish chikungunya cases from two groups: other AFI and dengue. Specimens collected from participants with fever ≤7 days were tested for chikungunya, dengue viruses 1–4, and 20 other pathogens. Of 8,996 participants, 18.2% had chikungunya, and 10.8% had dengue. Chikungunya cases were more likely than other groups to be older, report a chronic condition, and present <3 DPO. Regardless of timing of presentation, significant positive predictors for chikungunya versus other AFI were: joint pain, muscle, bone or back pain, skin rash, and red conjunctiva; with dengue as the comparator, red swollen joints (arthritis), joint pain, skin rash, any bleeding, and irritability were predictors. Chikungunya cases were less likely than AFI and dengue to present with thrombocytopenia, signs of poor circulation, diarrhea, headache, and cough. Among participants presenting <3 DPO, predictors for chikungunya versus other AFI included: joint pain, skin rash, and muscle, bone or back pain, and absence of thrombocytopenia, poor circulation and respiratory or gastrointestinal symptoms; when the comparator was dengue, joint pain and arthritis, and absence of thrombocytopenia, leukopenia, and nausea were early predictors. Among all groups presenting 3–5 DPO, pruritic skin became a predictor for chikungunya, joint, muscle, bone or back pain were no longer predictive, while arthritis became predictive in all age-groups. Absence of thrombocytopenia was a significant predictor regardless of DPO or comparison group. This study identified robust clinical indicators such as joint pain, skin rash and absence of thrombocytopenia that can allow early identification of and accurate differentiation between patients with chikungunya and other common causes of AFI.

Objectives:Hurricane Maria caused catastrophic damage in Puerto Rico, increasing the risk for morbidity and mortality in the post-impact period. We aimed to establish a syndromic surveillance system to describe the number and type of visits at 2 emergency health-care settings in the same hospital system in Ponce, Puerto Rico.Methods:We implemented a hurricane surveillance system by interviewing patients with a short questionnaire about the reason for visit at a hospital emergency department and associated urgent care clinic in the 6 mo after Hurricane Maria. We then evaluated the system by comparing findings with data from the electronic medical record (EMR) system for the same time period.Results:The hurricane surveillance system captured information from 5116 participants across the 2 sites, representing 17% of all visits captured in the EMR for the same period. Most visits were associated with acute illness/symptoms (79%), followed by injury (11%). The hurricane surveillance and EMR data were similar, proportionally, by sex, age, and visit category.Conclusions:The hurricane surveillance system provided timely and representative data about the number and type of visits at 2 sites. This system, or an adapted version using available electronic data, should be considered in future disaster settings.

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