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. 2019 Feb 8;363(6427):607-610.
doi: 10.1126/science.aav6618.

Impact of preexisting dengue immunity on Zika virus emergence in a dengue endemic region

Isabel Rodriguez-Barraquer  1 , Federico Costa  2   3   4 , Eduardo J M Nascimento  5 , Nivison Nery Júnior  2   3 , Priscila M S Castanha  6   7 , Gielson Almeida Sacramento  3 , Jaqueline Cruz  3 , Mayara Carvalho  3 , Daiana De Olivera  3 , José E Hagan  3   4 , Haritha Adhikarla  4 , Elsio A Wunder Jr  3   4 , Danilo F Coêlho  6   8 , Sasha R Azar  9 , Shannan L Rossi  10 , Nikos Vasilakis  11 , Scott C Weaver  10 , Guilherme S Ribeiro  2   3   12 , Angel Balmaseda  13   14 , Eva Harris  15 , Maurício L Nogueira  16 , Mitermayer G Reis  3   4   12 , Ernesto T A Marques  5   6   17 , Derek A T Cummings  18   19 , Albert I Ko  20   4
Affiliations

Impact of preexisting dengue immunity on Zika virus emergence in a dengue endemic region

Isabel Rodriguez-Barraquer et al. Science. .

Abstract

The clinical outcomes associated with Zika virus (ZIKV) in the Americas have been well documented, but other aspects of the pandemic, such as attack rates and risk factors, are poorly understood. We prospectively followed a cohort of 1453 urban residents in Salvador, Brazil, and, using an assay that measured immunoglobulin G3 (IgG3) responses against ZIKV NS1 antigen, we estimated that 73% of individuals were infected during the 2015 outbreak. Attack rates were spatially heterogeneous, varying by a factor of 3 within a community spanning 0.17 square kilometers. Preexisting high antibody titers to dengue virus were associated with reduced risk of ZIKV infection and symptoms. The landscape of ZIKV immunity that now exists may affect the risk for future transmission.

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Figures

Fig. 1.
Fig. 1.
Location of the study. A. Location of the city of Salvador in the state of Bahía and Brazil. B. Location of households enrolled at the Pau de Lima community study site in Salvador. C. Spatial heterogeneity in the proportion of the samples that were found to be ZIKV IgG3 positive (indicated by colors) in October 2015.. The smoothed surface was generated using a generalized additive model (GAM) that included latitude, longitude and altitude as predictors.
Fig. 2.
Fig. 2.
Results of serological testing conducted prior to and after the ZIKV outbreak among Pau da Lima cohort participants (A). Each dot shows the result of an individual participant sample using our ZIKV IgG3 assay (see supplementary material). ZIKV PRNT was performed on a random subset of samples collected in March 2015 (orange) and October 2015 (green) (B). Dashed line indicates the cutoff established, using the PRNT results as the gold-standard, to achieve a sensitivity of 85% and a specificity of 97% (C).
Fig. 3.
Fig. 3.
Age-stratified seropositivity to ZIKV (A) and DENV (B) measured in October 2015 (post Zika outbreak) and March 2015 (pre-Zika outbreak) respectively. Red line (A) shows the mean seropositivity in this population. Blue line (B) shows the fit of the best model estimating the historical DENV force of infection in this population (see supplementary methods).
Fig. 4
Fig. 4
Results of generalized additive models looking at two metrics of ZIKV infection as a function of age and prior DENV exposure (DENV NS1 IgG titer and DENV NS1 IgG3 OD value measured in March 2015). A. Proportion ZIKV positive in October 2015 according to our ZIKV IgG3 assay and B. Ratio of IgG3 levels in October 2015 vs. March 2015.
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