The Zika Virus Individual Participant Data Consortium: a global initiative to estimate the effects of exposure to Zika virus during pregnancy on adverse fetal, infant, and child health outcomes

Zika Virus Individual Participant

Research output: Contribution to journalA1: Web of Science-article

Abstract

This commentary describes the creation of the Zika Virus Individual Participant Data Consortium, a global collaboration to address outstanding questions in Zika virus (ZIKV) epidemiology through conducting an individual participant data meta-analysis (IPD-MA). The aims of the IPD-MA are to (1) estimate the absolute and relative risks of miscarriage, fetal loss, and short- and long-term sequelae of fetal exposure; (2) identify and quantify the relative importance of different sources of heterogeneity (e.g., immune profiles, concurrent flavivirus infection) for the risk of adverse fetal, infant, and child outcomes among infants exposed to ZIKV in utero; and (3) develop and validate a prognostic model for the early identification of high-risk pregnancies and inform communication between health care providers and their patients and public health interventions (e.g., vector control strategies, antenatal care, and family planning programs). By leveraging data from a diversity of populations across the world, the IPD-MA will provide a more precise estimate of the risk of adverse ZIKV-related outcomes within clinically relevant subgroups and a quantitative assessment of the generalizability of these estimates across populations and settings. The ZIKV IPD Consortium effort is indicative of the growing recognition that data sharing is a central component of global health security and outbreak response.

Original languageEnglish
Article number152
JournalTropical Medicine and Infectious Disease
Volume5
Issue number4
Number of pages7
ISSN2414-6366
DOIs
Publication statusPublished - 2020

Keywords

  • Zika virus
  • individual participant data meta-analysis
  • data sharing
  • emerging pathogen
  • prognostic model
  • prediction model
  • congenital Zika syndrome
  • microcephaly

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