Systematic Framework for Interpreting Laboratory-Confirmed Infectious Disease Surveillance Data: A Pragmatic Scenario-Based Approach
In infectious disease surveillance, laboratory-confirmed case counts and test positivity (proportion of tests positive for the target pathogen) are commonly used to monitor disease activity. However, these test-based data are affected not only by disease incidence but also by testing intensity, often making interpretations difficult. To help address this challenge, we present a generalizable, systematic framework that considers the number of tests performed, number of test-positive counts, and test positivity. With explicit consideration of ascertainment bias, we explain why all 3 indicators should be used to improve data interpretation, situational assessment, and communication.
Authors
- Osamu Takahara
- Katsuhiro Komase (ORCID: https://orcid.org/0000-0002-0470-6073)
- Yuuki Tsuchihashi (ORCID: https://orcid.org/0000-0002-6117-4448)
- Kazuhiko Kanou
- Takeshi Arashiro (ORCID: https://orcid.org/0000-0002-5215-1500)
- Reiko Shimbashi (ORCID: https://orcid.org/0000-0002-3265-7950)
- Ayu Kasamatsu (ORCID: https://orcid.org/0000-0003-1515-6238)
- Hirofumi Kato (ORCID: https://orcid.org/0000-0002-0704-9611)
- Yusuke Kobayashi (ORCID: https://orcid.org/0000-0002-4541-8318)
- Taro Kamigaki (ORCID: https://orcid.org/0000-0002-3612-4270)
- Takuri Takahashi (ORCID: https://orcid.org/0000-0002-2482-7286)
- Tamano Matsui
- Yuzo Arima
- Motoi Suzuki
Institutions
- Public Health Dayton & Montgomery County (US)
Publication Details
- Journal
- Health Security
- Published
- 2026-04-27
- DOI
- https://doi.org/10.1177/23265094261435869
- Primary Topic
- Data-Driven Disease Surveillance
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Ministry of Health, Labour and Welfare