This is an international resource for facilitating the collection of standardised clinical data on patients hospitalised with suspected or confirmed infection with novel coronavirus (COVID-19). The Case Record Form (CRF) has undergone extensive review and validation by international clinical experts. 


About the tools

Aim: The primary aim is to provide tools for standardised data collection to inform local and international public health responses and patient care. 
Rationale: In the past, clinical data on emerging infections has not been collected, standardised, or shared quickly enough to inform the outbreak response and patient care.

Data collection

There are two options for implementing this CRF in your institution: 

1. Centralised eCRF (preferred option): An electronic version of the COVID-19 CRF (eCRF) has been developed in REDCap for your convenience. REDCap is a secure web platform for managing online databases, hosted by the University of Oxford and free to use. You will retain full ownership of and access to your data and it will not be used or shared in any way without your written permission. To gain access to the nCoV eCRF your institution is required to accept the Data Sharing Agreement (DSA) Terms of Data Submission on REDCap. The DSA outlines the measures taken to ensure patient confidentiality, data security, and equitable access to the data for public health purposes. A copy of the DSA is available to download for review in the tools section of this webpage. To obtain access to the centralised eCRF please use the contact below.  

2. Localised Database: If your institution does not wish to enter a DSA, it is possible to set up a localised version of the eCRF in REDCap. For instructions on how to do this please use the contact below. 

Contact: For further information about these resources, please email the ISARIC Global Support Centre

ISARIC is a signatory to the joint statements on data sharing in public health emergencies available here. We stand by the principles of data sharing in public health emergencies, as defined through work led by GloPID-R. We would not expect data sharing to compromise contributors future publications.