Chikungunya in a co-circulation setting: diagnostic discrepancies and clinical variation between RT-PCR-positive cases and notified data in Foz do Iguaçu, Brazil.

Chikungunya virus infection remains a diagnostic challenge in regions with co-circulation of dengue, where overlapping clinical manifestations frequently lead to misclassification. This study compared the clinical and epidemiological profiles of chikungunya cases confirmed by molecular diagnosis (RT-PCR) with cases notified to the Brazilian National Notifiable Diseases Information System (SINAN) during the 2023 epidemic in Foz do Iguaçu, southern Brazil, aiming to identify diagnostic discrepancies, symptom patterns, and potential selection biases. A retrospective analytical study was conducted using two datasets: 201 RT-PCR confirmed cases obtained from medical records and 1,964 suspected cases reported to SINAN. Descriptive analyses, bivariate tests, hierarchical cluster analysis, and multiple correspondence analysis were performed. Among RT-PCR confirmed cases, the initial clinical diagnostic error rate was 58.7%. Arthralgia was the primary predictor of a correct clinical diagnosis (OR=3.08) and was more prevalent among RT-PCR confirmed cases than among laboratory-confirmed cases reported to SINAN. In contrast, arthritis and retro-orbital pain were more frequent among cases confirmed by clinical-epidemiological criteria in SINAN than among RT-PCR confirmed cases. Symptom clustering revealed distinct clinical profiles, with an articular pattern accounting for the highest proportion of RT-PCR-positive cases. Hospitalization rates varied by confirmation criteria, suggesting a selection bias toward laboratory testing. These findings demonstrated discrepancies between molecularly confirmed cases and routine surveillance data, as well as a high rate of initial clinical misdiagnosis. The results highlight the need to refine clinical-epidemiological criteria, prioritize arthralgia as a key diagnostic symptom, and account for chikungunya's clinical heterogeneity to improve diagnosis and epidemiological surveillance.