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Related Concept Videos

Principles of Disease Surveillance01:26

Principles of Disease Surveillance

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Disease surveillance is the systematic collection, analysis, and interpretation of health data essential to the planning, implementation, and evaluation of public health practice. This process integrates data dissemination to entities responsible for preventing and controlling disease, injury, and disability. Surveillance systems provide crucial information for action, helping public health authorities make informed decisions to manage and prevent outbreaks, ensure public safety, optimize...
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Sensitivity, Specificity, and Predicted Value01:13

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In healthcare diagnostics, laboratory tests play a crucial role in identifying and diagnosing a wide range of medical conditions. However, interpreting test results is not always straightforward. An abnormal test result does not always confirm the presence of a disease, just as a normal result does not guarantee its absence. To assess the reliability of these diagnostic tools, healthcare practitioners rely on two key statistical indicators: sensitivity and specificity.
Sensitivity is the...
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Whose Line Is it Anyway? Defining Seropositivity Cutoffs for Infectious Disease Surveillance.

Michael T White1, Gaëlle Baudemont1, Françoise Donnadieu1

  • 1Infectious Disease Epidemiology and Analytics G5 Unit, Department of Global Health, Institut Pasteur, Université Paris-Cité, INSERM U1347, Paris, France.

The Journal of Infectious Diseases
|October 18, 2025
PubMed
Summary

Determining sero-positivity cut-offs is crucial for infectious disease surveillance. A new framework guides the selection of appropriate methods for antibody data interpretation, improving reliability across diverse settings.

Keywords:
cutoffinfectious diseasesserologyseroprevalencesurveillancethreshold

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Area of Science:

  • Immunology
  • Epidemiology
  • Biostatistics

Background:

  • Serological assays are vital for tracking infectious diseases by measuring antibody responses.
  • Establishing accurate sero-positivity cut-offs is a significant methodological hurdle.

Purpose of the Study:

  • To present a framework for selecting sero-positivity cut-offs based on assay characteristics, sample availability, and intended use.
  • To provide guidance on choosing appropriate methods for antibody data interpretation in serological surveys.

Main Methods:

  • Evaluated four methods: Receiver Operating Characteristic (ROC) curves, Negative Sample Distribution, Positive Sample Distribution, and Mixture Models.
  • Detailed assumptions, advantages, and limitations of each method.
  • Applied the framework to simulated data and multiplex serological survey data for neglected tropical diseases.

Main Results:

  • Demonstrated that a single approach is insufficient for all pathogens or populations.
  • Highlighted confounding factors such as cross-reactive antibodies, population-specific IgG levels, and assay characteristics.
  • Illustrated framework application using simulated and real-world serological data.

Conclusions:

  • Advocated for context-dependent, evidence-based selection of cut-off methodologies using confirmed samples.
  • Emphasized the need for robust frameworks for interpreting antibody data from multiplex serological platforms.
  • Proposed a pragmatic framework to enhance the reliability and comparability of sero-epidemiological insights.