Constructing a global human epidemic database using open-source digital biosurveillance
We developed a dataset consisting of outbreak data collected from official, open-source surveillance reports representing more than 170 pathogens, 237 countries and territories, and more than 3300 events that occurred primarily between 1963 and 2023. Here we present and analyze a subset of these data, comprising a dataset of human epidemic events with onset between 2015 and 2020. Structuring of epidemiological data in the dataset follows a specific methodology to ensure consistency across all events. This methodology has been designed to produce the most reliable spatiotemporal view of an outbreak as possible. To ensure data are true-to-source, the structured data undergoes multiple rounds of both manual and automated review and validation. The extensive and standardized nature of the dataset makes it well-suited for both descriptive epidemiology and exploring outbreak dynamics and disease emergence.
Authors
- Rinette Badker (ORCID: https://orcid.org/0000-0003-4391-9685)
- Ben Oppenheim (ORCID: https://orcid.org/0000-0003-1487-3534)
- Benjamin Ash
- Chris Pardee
- Nita Madhav (ORCID: https://orcid.org/0000-0001-8077-330X)
- Nicole Stephenson
- Patrick D. Savage
- Naama Kipperman
Institutions
- Ginkgo Bioworks, Inc. (United States) (US)
Publication Details
- Journal
- Scientific Data
- Published
- 2025-02-26
- DOI
- https://doi.org/10.1038/s41597-025-04663-z
- Primary Topic
- Zoonotic diseases and public health
- Type
- article
- Field-Weighted Citation Impact
- 0.00