Defining Zika virus infection in pregnant women

Defining cases of Zika virus (ZIKV) infection is a critical challenge for epidemiological research. Due to ZIKV's overlapping clinical features and potential immunologic cross-reactivity with other flaviviruses and the current lack of an optimal ZIKV-specific diagnostic assay, varying approaches for identifying ZIKV infections have been employed to date. This paper presents the laboratory results and diagnostic criteria developed by the Microcephaly Epidemic Research Group for defining cases of maternal ZIKV infection in a cohort of pregnant women with rash (N = 694) recruited during the declining 2015-2017 epidemic in northeast Brazil. For this investigation, we tested maternal sera for ZIKV by quantitative reverse transcription polymerase chain reaction (qRT-PCR), Immunoglobulin (Ig) M and IgG3 enzyme-linked immunosorbent assays (ELISAs), and Plaque Reduction Neutralization Test (PRNT50). Overall, 23.8% of participants tested positive by qRT-PCR during pregnancy (range of detection: 0-72 days after rash onset). However, the inter-assay concordance was lower than expected. Among women with qRT-PCR-confirmed ZIKV and further testing, only 10.1% had positive IgM tests within 90 days of rash, and only 48.5% had ZIKV-specific PRNT50 titers ≥20 within 1 year of rash. Given the complexity of these data, we convened a panel of experts to propose an algorithm for identifying ZIKV infections in pregnancy based on all available lines of evidence. When the diagnostic algorithm was applied to the cohort, 26.9% of participants were classified as having robust evidence of a ZIKV infection during pregnancy, 4.0% as having moderate evidence, 13.3% as having limited evidence of a ZIKV infection but with uncertain timing, and 19.5% as having evidence of an unspecified flavivirus infection before or during pregnancy. Our findings suggest that integrating longitudinal data from nucleic acid and serologic testing may enhance diagnostic sensitivity and underscore the need for an on-going dialogue regarding the optimization of strategies for defining cases of ZIKV in research.