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Remote Laboratory Management: Respiratory Virus Diagnostics
Published on: April 6, 2019
Leveraging limited testing data for early detection of emerging infectious disease outbreaks
Alexander John Zapf1, Marc Lipsitch2
1Center for Communicable Disease Dynamics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Ave, Boston, MA 02115, United States.
American Journal of Epidemiology
|August 11, 2026
Summary
Negative test data can provide early warnings for emerging infectious disease outbreaks, even when pathogens mimic common illnesses. This method offers timely detection but requires specific conditions for reliable performance.
Area of Science:
- Epidemiology
- Public Health Surveillance
- Infectious Disease Modeling
Background:
- Early outbreak surveillance is challenged by limited testing, diagnostic delays, and low clinical suspicion for novel pathogens.
- New infectious diseases often present with symptoms similar to existing conditions, potentially creating detectable signals in routine testing data.
- Individuals with novel infections may seek testing for known, similar conditions, leading to negative results for the tested condition.
Purpose of the Study:
- To evaluate the utility of total and negative testing volumes for a clinically similar condition in providing timely outbreak warnings for emerging infectious diseases.
- To assess the performance of outbreak detection using negative test data across various epidemiological and testing parameters.
Main Methods:
- Developed analytic and simulation frameworks utilizing Poisson and negative binomial models.
- Systematically evaluated detection performance by varying baseline test counts, epidemic growth rates, testing fractions among cases, detection threshold stringency, and overdispersion.
Main Results:
- Detection thresholds based on negative test volumes consistently outperformed total test volume thresholds, enabling earlier detection with fewer cumulative cases.
- Reliable detection necessitates high testing fractions among epidemic cases (ideally >30%), low baseline test volumes, and low overdispersion.
- Negative test-based detection achieved earlier detection with approximately one-third fewer cumulative cases compared to total test thresholds, maintaining similar false positive rates.
Conclusions:
- Negative testing data can serve as a valuable, resource-efficient complement to integrated surveillance systems for early detection of emerging infectious disease outbreaks.
- Prioritizing access to disaggregated test result data is crucial for enhancing the effectiveness of this surveillance approach.
- This method is best positioned as a complementary tool rather than a standalone early warning system due to stringent data requirements.
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