A comparative analysis of dengue, chikungunya, and Zika manifestations in a pediatric cohort over 18 years
Bustos Carrillo, F. A.; Ojeda, S.; Sanchez, N.; Plazaola, M.; Collado, D.; Miranda, T.; Saborio, S.; Lopez Mercado, B.; Carey Monterrey, J.; Arguello, S.; Campredon, L.; Chu, Z.; Carlson, C. J.; Gordon, A.; Balmaseda, A.; Kuan, G.; Harris, E.
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BackgroundDengue, chikungunya, and Zika are diseases of major human concern. Differential diagnosis is complicated in children and adolescents by their overlapping clinical features (signs, symptoms, and complete blood count results). Few studies have directly compared the three diseases. We aimed to identify distinguishing pediatric characteristics of each disease. MethodsData were derived from laboratory-confirmed cases (symptomatic infections) aged 2-<18 years enrolled in a longitudinal cohort study in Managua, Nicaragua, and attending a primary health care center from January 19, 2006, through December 31, 2023. We collected clinical records and laboratory results across the first 10 days of illness. Data were analyzed with generalized additive models, day-and-disease-specific prevalence estimates, and machine learning models. FindingsWe characterized 1,405 dengue, 517 chikungunya, and 522 Zika pediatric cases. We included 1,165 (47{middle dot}7%) males and 1,279 (52{middle dot}3%) females, with a median age of 10{middle dot}0 (IQR 7{middle dot}0-12{middle dot}7) years. The prevalence of many clinical features exhibited by dengue, chikungunya, and Zika cases differed substantially overall, by age, and by day of illness. Dengue cases were differentiated most by abdominal pain (Prevalence difference (PD) 19{middle dot}1%, 95% confidence interval (CI): 15{middle dot}7%, 22{middle dot}9%), leukopenia (PD 41{middle dot}1%, 95% CI: 36{middle dot}2%, 45{middle dot}6%), nausea (PD 15{middle dot}5%, 95% CI: 12{middle dot}2%, 19{middle dot}2%), vomiting (PD 21{middle dot}9%, 95% CI: 17{middle dot}9%, 26{middle dot}1%), and basophilia (PD 42{middle dot}3%, 95% CI: 37{middle dot}4%, 47{middle dot}0%); chikungunya cases were differentiated most by arthralgia (PD 60{middle dot}5%, 95% CI: 56{middle dot}3%, 64{middle dot}2%) and the absence of leukopenia (PD -32{middle dot}0%, 95% CI: -36{middle dot}7%, -27{middle dot}1%) and papular rash (PD -14{middle dot}9%, 95% CI: -17{middle dot}2%, -12{middle dot}7%); and Zika cases were differentiated most by rash (PD 31{middle dot}8%, 95% CI: 27{middle dot}0%, 36{middle dot}2%) and the lack of fever (PD -37{middle dot}3%, 95% CI: -41{middle dot}7%, -33{middle dot}0%) and lymphocytopenia (PD -41{middle dot}9%, 95% CI: -46{middle dot}6%, -37{middle dot}1%). Dengue and chikungunya cases exhibited similar temperature dynamics during acute illness, and their temperatures were higher than Zika cases. Sixty-two laboratory-confirmed afebrile dengue cases, which would not be captured by any widely used international case definition, presented very similarly to afebrile Zika cases, though some exhibited warning signs of disease severity. The presence of arthralgia, the presence of basophilia, and the absence of fever were the most important model-based distinguishing predictors of chikungunya, dengue, and Zika, respectively. InterpretationsThese findings substantially update our understanding of dengue, chikungunya, and Zika in children while identifying various clinical features that could improve differential diagnoses. The occurrence of afebrile dengue warrants reconsideration of current guidance. FundingUS National Institutes of Health R01AI099631, P01AI106695, U01AI153416, U19AI118610. Research in contextO_ST_ABSEvidence before this studyC_ST_ABSDengue, chikungunya, and Zika co-occur in tropical and subtropical settings and cause fever, rash, and other clinical features. We reviewed international case definitions for the three diseases; the Pan American Health Organizations (PAHO) 2022 report on their differential diagnosis; and the 80 studies underlying PAHOs recommendations. On March 15, 2025, we queried PubMed without restrictions for "pediatric cohort" AND "dengue" AND "chikungunya" AND "Zika," revealing that no other pediatric cohort study simultaneously reported clinical differences between the three diseases. The literature suggests that the broad and overlapping clinical features of the three diseases hamper differential diagnosis, particularly for mild forms of the diseases during acute illness, absent definitive laboratory testing. Most studies on the diseases clinical manifestations are in adults, and these studies constitute the main evidence base for existing case definitions. Disease presentation is more non-specific in children and adolescents than in adults, further impeding differential diagnoses in pediatric populations. Current guidelines suggest that the presence of thrombocytopenia, progressive increases in hematocrit, and leukopenia tend to distinguish dengue from chikungunya and Zika; that arthralgia is more common in chikungunya; and that pruritis is more common in Zika. All dengue case definitions in widespread use require that patients exhibit fever. Added value of this studyThis study follows a cohort of Nicaraguan children through multiple dengue epidemics, two large chikungunya epidemics, and one explosive Zika epidemic. Synthesizing 18 years worth of primary care medical records, we find clinically meaningful differences in the prevalence of many clinical features, including by day of illness and across age. In addition to verifying the clinical features PAHO identified as key distinguishing features, we also identified others, including papular rash, nausea, hemorrhagic manifestations, abdominal pain, and basophilia, that could aid differential diagnoses. As the PAHO report is based on a multitude of studies with varied age ranges, health care accessibility, overall research quality, and patient populations, this study is a complementary and important counterpart that draws from a single, well-characterized source population. Further, we identified 62 laboratory-confirmed cases of afebrile dengue (7{middle dot}1% of all dengue cases since we started testing any suspected case exhibiting afebrile rash). The disease manifestations of afebrile dengue cases were generally clinically indistinguishable from afebrile Zika, although several displayed warning signs of severity. Machine learning models best distinguished chikungunya from dengue and Zika based on clinical features. Our dengue model performed well, especially in classifying febrile dengue cases. However, our Zika model struggled to properly distinguish afebrile dengue cases from afebrile Zika cases, likely due to their very similar and minimal disease presentation. Implications of all the available evidenceWe identify meaningful differences in the pediatric presentation and laboratory markers of dengue, chikungunya, and Zika cases that can be leveraged to improve diagnoses in the absence of laboratory testing. The distinguishing characteristics we identify could be used by future studies to build, optimize, and validate clinical prediction models. Afebrile dengue should be studied more and incorporated into future guidance, as not accounting for its existence can impede surveillance, laboratory testing strategies, clinical management, and research efforts.
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