covidjson.org

What It Is

CovidJSON is a GeoJSON-based data model for virus infection data, designed to exchange infection test results, contact-tracing events, and regional infection statistics. It is explicitly based on concepts from OGC/ISO Observations & Measurements (ISO 19156) and follows the O&M GeoJSON encoding approach. The text indicates that it was initially designed for SARS-CoV-2 testing, but it may also be applicable to testing data for other infectious diseases.

Core Capabilities

Functionally, CovidJSON covers two major use cases. The first is individual-level data, including test events, sampling, healthcare facilities, subjects, and contact events. The second is regional statistics, including new infection counts for a given area and daily time series. The model is highly detailed, with fields such as testing method, LOINC/SNOMED identifiers, sampling time, subject residence, contact distance, contact duration, and more. It also accounts for privacy protection: if a contact location is not recorded, a Polygon with empty coordinates can be used to represent null geometry.

Standards, Integration, and Documentation

Its main value lies in standards compatibility. GeoJSON makes it easy to integrate with GIS, map visualization, and spatial analysis tools, while references to OGC O&M, ISO 19156, GeoJSON RFC 7946, LOINC, SNOMED, GeoNames, and others improve interoperability across organizations. The documentation is reasonably strong at the field-description level, providing complete JSON examples and explanations of properties for different feature types. However, the main text does not mention an SDK, validator, formal API certification, version management, license, or production deployment guidance. As a result, engineering teams would still need to implement parsing, validation, and data governance themselves.

Pricing and Open Source

The collected text does not provide a pricing model, nor does it clarify whether the project is open source or closed source. It appears more like a public data specification than a commercial developer tool or SaaS platform. There are also no specific self-hosting instructions. Since it is a data model, organizations can implement it in their own databases, APIs, or GIS pipelines, but that would be a self-built implementation based on the specification.

Pros, Cons, and Who It’s For

Its strengths are clear semantics, a high level of standardization, suitability for geospatial data exchange, and coverage of individual testing, contact tracing, and regional statistics. Its drawbacks are the relatively high learning curve, as users need to understand GeoJSON and O&M, as well as the lack of toolchains, SDKs, licensing details, and service support information. It is suitable for public health agencies, GIS teams, epidemic data engineers, and developers who need to design infection data exchange formats.

Access in China

The text does not provide information about access, payment, or local services in mainland China, so its availability status can only be considered unknown. For domestic projects, teams could consider internalizing the GeoJSON/OGC approach into a local data specification, or using FHIR, OGC API Features, or self-built GIS services as alternative implementations.