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Primary exposure to Zika virus is linked with increased risk of symptomatic dengue virus infection with serotypes 2, 3, and 4, but not 1.

José Victor ZambranaChloe M HasundRosemary A AogoSandra BosSonia ArguelloKarla GonzalezDamaris ColladoTatiana MirandaGuillermina KuanAubree GordonAngel BalmasedaLeah C KatzelnickEva Harris
Published in: Science translational medicine (2024)
Infection with any of the four dengue virus serotypes (DENV1-4) can protect against or enhance subsequent dengue depending on preexisting antibodies and infecting serotype. Additionally, primary infection with the related flavivirus Zika virus (ZIKV) is associated with increased risk of DENV2 disease. Here, we measured how prior DENV and ZIKV immunity influenced risk of disease caused by DENV1-4 in a pediatric Nicaraguan cohort. Of 3412 participants in 2022, 10.6% experienced dengue cases caused by DENV1 ( n = 139), DENV4 ( n = 133), DENV3 ( n = 54), DENV2 ( n = 9), or an undetermined serotype ( n = 39). Longitudinal clinical and serological data were used to define infection histories, and generalized linear and additive models adjusted for age, sex, time since last infection, and year, and repeat measurements were used to predict disease risk. Compared with flavivirus-naïve participants, primary ZIKV infection was associated with increased risk of disease caused by DENV4 (relative risk = 2.62, 95% confidence interval: 1.48 to 4.63) and DENV3 (2.90, 1.34 to 6.27), but not DENV1 infection. Primary DENV infection or DENV followed by ZIKV infection was also associated with increased risk of DENV4 disease. We reanalyzed 19 years of cohort data and demonstrated that prior flavivirus immunity and antibody titer had distinct associations with disease risk depending on incoming serotype. We thus find that prior ZIKV infection, like prior DENV infection, is associated with increased risk of disease with certain DENV serotypes. Cross-reactivity among flaviviruses should be considered when assessing vaccine safety and efficacy.
Keyphrases
  • dengue virus
  • zika virus
  • aedes aegypti
  • young adults
  • deep learning
  • electronic health record
  • big data
  • data analysis
  • neural network
  • disease virus