Abstract
Public health surveillance based on data analytics plays a crucial role in detecting and responding to public health crises, such as infectious disease outbreaks. Previous information science research on the topic has focused on developing analytical algorithms and visualization tools. This study seeks to extend the research by investigating information practices in data analytics for public health surveillance. Through a case study of how data analytics was conducted for surveilling Influenza A and COVID-19 outbreaks, both exploration information practices (i.e., probing, synthesizing, exchanging) and exploitation information practices (i.e., scavenging, adapting, outreaching) were identified and detailed. These findings enrich our empirical understanding of how data analytics can be implemented to support public health surveillance.
| Original language | English |
|---|---|
| Pages (from-to) | 79-93 |
| Number of pages | 15 |
| Journal | Journal of the Association for Information Science and Technology |
| Volume | 75 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Jan 2024 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2023 Association for Information Science and Technology.
ASJC Scopus Subject Areas
- Information Systems
- Computer Networks and Communications
- Information Systems and Management
- Library and Information Sciences
