A “Pandemic-Proof” Methodology for Outbreak Detection Adapted From COVID-19’s Impact on Notifications of Infectious Diseases in the Netherlands: Surveillance Study

During the COVID-19 pandemic, notifications of 10 infectious diseases declined significantly. The duration of this decline varied among infections, highlighting the need for pattern-specific adjustments. Our study demonstrates that accounting for the reduced notifications impacts alarm threshold calculations for outbreak detection. We therefore recommend amending the alarm thresholds to account for this impact to ensure reliable outbreak detection, so that communicable disease control professionals can act in a timely and data-driven manner. The next step in the development of the "pandemic-proof" methodology is to determine which correction method is most suitable. Further validation by communicable disease control professionals is essential to assess the applicability of the adjusted alarm thresholds for outbreak detection.

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Publication Details

Journal
JMIR Public Health and Surveillance
Published
2025-07-01
DOI
https://doi.org/10.2196/73953
Primary Topic
Data-Driven Disease Surveillance
Type
article
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article

A “Pandemic-Proof” Methodology for Outbreak Detection Adapted From COVID-19’s Impact on Notifications of Infectious Diseases in the Netherlands: Surveillance Study

Cornelia H.M. van Jaarsveld, Stijn Raven, Babette van Deursen, Wolfer van den Bosch et al.
JMIR Public Health and Surveillance
Data-Driven Disease Surveillance
article

A “Pandemic-Proof” Methodology for Outbreak Detection Adapted From COVID-19’s Impact on Notifications of Infectious Diseases in the Netherlands: Surveillance Study

Cornelia H.M. van Jaarsveld, Stijn Raven, Babette van Deursen, Wolfer van den Bosch, Aura Timen
article en

Abstract

During the COVID-19 pandemic, notifications of 10 infectious diseases declined significantly. The duration of this decline varied among infections, highlighting the need for pattern-specific adjustments. Our study demonstrates that accounting for the reduced notifications impacts alarm threshold calculations for outbreak detection. We therefore recommend amending the alarm thresholds to account for this impact to ensure reliable outbreak detection, so that communicable disease control professionals can act in a timely and data-driven manner. The next step in the development of the "pandemic-proof" methodology is to determine which correction method is most suitable. Further validation by communicable disease control professionals is essential to assess the applicability of the adjusted alarm thresholds for outbreak detection.

JMIR Public Health and SurveillanceVol. 11
Radboud University Nijmegen (NL), Radboud University Medical Center (NL), Public Health Service of Amsterdam (NL)
Good health and well-being
Openalex Percentile: Top 78%
Data-Driven Disease Surveillance
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A “Pandemic-Proof” Methodology for Outbreak Detection Adapted From COVID-19’s Impact on Notifications of Infectious Diseases in the Netherlands: Surveillance Study — Cornelia H.M. van Jaarsveld, Stijn Raven, et al. · JMIR Public Health and Surveillance (2025) | TGRS Research Map | TGRS