A structured course of disease dataset with contact tracing information in Taiwan for COVID-19 modelling

研究成果: Article同行評審

摘要

The COVID-19 pandemic has flooded open databases with population-level data. However, individual-level structured data, such as the course of disease and contact tracing information, is almost non-existent in open databases. Publish a structured and cleaned COVID-19 dataset with the course of disease and contact tracing information for easy benchmarking of COVID-19 models. We gathered data from Taiwanese open databases and daily news reports. The outcome is a structured quantitative dataset encompassing the course of the disease of Taiwanese individuals, alongside their contact tracing information. Our dataset comprises 579 confirmed cases covering the period from January 21, to November 9, 2020, when the original SARS-CoV-2 virus was most prevalent in Taiwan. The data include features such as travel history, age, gender, symptoms, contact types between cases, date of symptoms onset, confirmed, critically ill, recovered, and dead. We also include the daily summary data at population-level from January 21, 2020, to May 23, 2022. Our data can help enhance epidemiological modelling.

原文English
文章編號821
期刊Scientific Data
11
發行號1
DOIs
出版狀態Published - 2024 12月

All Science Journal Classification (ASJC) codes

  • 統計與概率
  • 資訊系統
  • 教育
  • 電腦科學應用
  • 統計、概率和不確定性
  • 圖書館與資訊科學

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