Zika Image Data Sharing Platform
OVERVIEW: The Nuffield Department of Women's & Reproductive Health leads a multi-disciplinary team of clinician scientists, epidemiologists, geneticists, engineers, computational biologists and radiologists from Brazil, the USA and UK. The aim of this consortium is to offer a secure, online information platform for images of fetal/newborn heads as a global data-sharing resource to help accelerate research into the effects of Zika virus (ZIKV) infection on fetal/newborn development.
We wish to collect a large number of ZIKV-related images from ongoing research projects, in particular:
2D and 3D ultrasound images of fetal brains
2D and 3D photos and MRI/CT scans of newborn and infant heads
Images of brain autopsy slides
2D photos of parents (where possible) for comparison with their children
HOW TO GET INVOLVED
Please read our Data Contribution Agreement and complete the form below.
Please note that fields marked with a red star are mandatory.
Please note it is also important to assemble the relevant, anonymised, clinical and laboratory records from mothers and infants. Therefore, we have built an online clinical database linked to the digital platform using clinical research forms (CRFs) developed jointly with ISARIC (International Severe Acute Respiratory and Emerging Infection Consortium) and PREPARE (Platform foR European Preparedness Against (Re-)emerging Epidemics). Read more.
If you have collected any of the images listed above, please would you consider sharing them and the associated clinical data with the platform. If your clinical data have been collected using other CRFs, we will only ask you for a minimal dataset.
Ethics: We have approval from the University of Oxford’s Research Ethics Committee (OxTREC) to store and analyse ZIKV-related images and clinical/laboratory records. However, before we can accept any data, contributors are required to have local ethics approval to share these data with the platform. You/your institution will continue to own your data even if copies are submitted to the platform, and the collaboration will not affect your right to publish your data independently.
Publication policy: We aim to be very inclusive in this project. Therefore, any data submitted that contribute to a publication using the pooled dataset will be acknowledged with co-authorship in accordance with the guidelines of the International Committee of Medical Journal Editors Read more
We are committed to protecting the privacy and security of your personal information. This notice describes how we collect and use your personal data submitted to us online, by email or on paper, in accordance with the General Data Protection Regulation (GDPR) and associated data protection legislation. Read more