EpiJSON: A unified data-format for epidemiology.
Epidemiology relies on data but the divergent ways data are recorded and transferred, both within and between outbreaks, and the expanding range of data-types are creating an increasingly complex problem for the discipline. There is a need for a consistent, interpretable and precise way to transfer data while maintaining its fidelity. We introduce 'EpiJSON', a new, flexible, and standards-compliant format for the interchange of epidemiological data using JavaScript Object Notation. This format is designed to enable the widest range of epidemiological data to be unambiguously held and transferred between people, software and institutions. In this paper, we provide a full description of the format and a discussion of the design decisions made. We introduce a schema enabling automatic checks of the validity of data stored as EpiJSON, which can serve as a basis for the development of additional tools. In addition, we also present the R package 'repijson' which provides conversion tools between this format, line-list data and pre-existing analysis tools. An example is given to illustrate how EpiJSON can be used to store line list data. EpiJSON, designed around modern standards for interchange of information on the internet, is simple to implement, read and check. As such, it provides an ideal new standard for epidemiological, and other, data transfer to the fast-growing open-source platform for the analysis of disease outbreaks.
Emergency Response Department Science and Technology, Public Health England, Porton Down, Salisbury, United Kingdom. Electronic address: Thomas.Finnie@phe.gov.uk.
Thomas J R
TJ
Finnie
Consultancy, Norwich, United Kingdom. Electronic address: http://andysouth.co.uk.
Andy
A
South
MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.
Ana
A
Bento
MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.
Ellie
E
Sherrard-Smith
MRC Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, United Kingdom.
Thibaut
T
Jombart
D066264:Datasets as Topic; D004196:Disease Outbreaks / Q000517:prevention & control*; D004812:Epidemiologic Methods; D006801:Humans; D012984:Software
Communications standards; Databases; Epidemics; Outbreaks; Software