Constructing a global human epidemic database using open-source digital biosurveillance

利用开源数字生物监测构建全球人类流行病数据库

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Abstract

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.

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