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Peer-reviewedCC BY-NC-ND 4.0Epidemiology and Infection

Pandemic preparedness: Potential of routine general practice data for infectious disease early signal detection

  • Jessica M. Aguilar Diaz1
  • Cornelia H. M. van Jaarsveld1
  • Aloïs Kessener1
  • Annemarie Uijen1
  • Federica Giardina2
  • Tim C. Olde Hartman1
  • Stijn F. H. Raven1,3
  • Aura Timen1
  1. 1Department of Primary and Community Care, Radboud University Medical Center, Nijmegen, The Netherlands
  2. 2IQ Health Science Department, Radboud University Medical Center, Nijmegen, The Netherlands
  3. 3Department of Infectious Disease Control, Public Health Service region Utrecht, Zeist, The Netherlands
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Abstract

In this proof-of-concept study, we explored the potential of structured general practice data for early signal detection, to enhance pandemic preparedness. We used electronic health record data from the Family Medicine Network (FaMe-Net) in the Netherlands between 2014 and 2024. Descriptive evaluation with surveillance attributes was performed, and the Farrington flexible method was used to construct an alert threshold for respiratory, gastroenteritis, rash, infectious conjunctivitis, and fever syndromes. Alert signals were generated, indicating when the observed weekly count exceeded the threshold. This data registry performed adequately for most surveillance attributes. We analysed 634708 diagnostic codes and 9 infectious disease syndromes in the data registry. In 154 weeks, the number of alert signals ranged from 3 to 20. We found similarities and variations in the number of alert signals between infectious syndrome definitions within the different data types. Structured general practice data showed potential for surveillance and early signal detection of infectious diseases because it performed well on most surveillance attributes and weekly counts of infectious disease syndromes led to the generation of alert signals. Further validation of these alert signals is needed, to underpin their early warning potential for timely public health action.

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Cite

BibTeXRIS
BibTeX
@article{diaz2026pandemic,
  title = {{Pandemic preparedness: Potential of routine general practice data for infectious disease early signal detection}},
  author = {Jessica M. Aguilar Diaz and Cornelia H. M. van Jaarsveld and Aloïs Kessener and Annemarie Uijen and Federica Giardina and Tim C. Olde Hartman and Stijn F. H. Raven and Aura Timen},
  journal = {Epidemiology and Infection},
  year = {2026},
  month = jun,
  doi = {10.1017/s0950268826101800},
  url = {https://doi.org/10.1017/s0950268826101800},
  note = {CC BY-NC-ND 4.0},
}
RIS
TY  - JOUR
TI  - Pandemic preparedness: Potential of routine general practice data for infectious disease early signal detection
AU  - Jessica M. Aguilar Diaz
AU  - Cornelia H. M. van Jaarsveld
AU  - Aloïs Kessener
AU  - Annemarie Uijen
AU  - Federica Giardina
AU  - Tim C. Olde Hartman
AU  - Stijn F. H. Raven
AU  - Aura Timen
PY  - 2026
DA  - 2026/06/29
JO  - Epidemiology and Infection
DO  - 10.1017/s0950268826101800
UR  - https://doi.org/10.1017/s0950268826101800
AB  - In this proof-of-concept study, we explored the potential of structured general practice data for early signal detection, to enhance pandemic preparedness. We used electronic health record data from the Family Medicine Network (FaMe-Net) in the Netherlands between 2014 and 2024. Descriptive evaluation with surveillance attributes was performed, and the Farrington flexible method was used to construct an alert threshold for respiratory, gastroenteritis, rash, infectious conjunctivitis, and fever syndromes. Alert signals were generated, indicating when the observed weekly count exceeded the threshold. This data registry performed adequately for most surveillance attributes. We analysed 634708 diagnostic codes and 9 infectious disease syndromes in the data registry. In 154 weeks, the number of alert signals ranged from 3 to 20. We found similarities and variations in the number of alert signals between infectious syndrome definitions within the different data types. Structured general practice data showed potential for surveillance and early signal detection of infectious diseases because it performed well on most surveillance attributes and weekly counts of infectious disease syndromes led to the generation of alert signals. Further validation of these alert signals is needed, to underpin their early warning potential for timely public health action.
SN  - 0950-2688
SN  - 1469-4409
ER  -