Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Assessing surveillance using sensitivity, specificity and timeliness.

Ken P Kleinman1, Allyson M Abrams

  • 1Department of Ambulatory Care and Prevention, Harvard Medical School and Harvard Pilgrim Health Care, 133 Brookline Avenue, Boston, MA 02215, USA. ken.kleinman@gmail.com

Statistical Methods in Medical Research
|November 9, 2006
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Cohort Profile Update: Project Viva Offspring.

International journal of epidemiology·2024
Same author

Temporal trends of concentrations of per- and polyfluoroalkyl substances among adults with overweight and obesity in the United States: Results from the Diabetes Prevention Program and NHANES.

Environment international·2021
Same author

Type I error control for cluster randomized trials under varying small sample structures.

BMC medical research methodology·2021
Same author

Per- and polyfluoroalkyl substances and calcifications of the coronary and aortic arteries in adults with prediabetes: Results from the diabetes prevention program outcomes study.

Environment international·2021
Same author

Using a Microsimulation of Energy Balance to Explore the Influence of Prenatal Sugar-Sweetened Beverage Intake on Child BMI.

Obesity (Silver Spring, Md.)·2021
Same author

Per- and polyfluoroalkyl substances and kidney function: Follow-up results from the Diabetes Prevention Program trial.

Environment international·2021
Same journal

Asymptotic online FWER control for dependent test statistics.

Statistical methods in medical research·2026
Same journal

Regression analysis of misclassified current status data with potentially unknown test accuracy.

Statistical methods in medical research·2026
Same journal

Bayesian multivariate linear mixed-effects models with varied association structures.

Statistical methods in medical research·2026
Same journal

Inference about the ratio of age-standardized rates between two overlapping populations.

Statistical methods in medical research·2026
Same journal

A robust neural network with random effects for subject-specific prediction of clustered count data.

Statistical methods in medical research·2026
Same journal

A comparison of methods for designing hybrid type 2 cluster-randomized trials with continuous effectiveness and implementation endpoints.

Statistical methods in medical research·2026
See all related articles

This study introduces new metrics to evaluate disease surveillance methods, generalizing receiver operating characteristic (ROC) curves to include detection time. These methods improve the analysis of spatial and temporal disease data for outbreak detection.

Area of Science:

  • Epidemiology
  • Biostatistics
  • Public Health Surveillance

Background:

  • Traditional disease monitoring often relies on unidimensional data streams over time.
  • Emerging data streams incorporate spatial and temporal elements, necessitating advanced surveillance methods.
  • Existing analytical methods for spatial surveillance data may be suboptimal.

Purpose of the Study:

  • To introduce and discuss novel evaluation metrics for statistical disease surveillance methods.
  • To compare the performance of surveillance methods, particularly those incorporating spatial and temporal data.
  • To generalize receiver operating characteristic (ROC) curves to include timeliness in disease outbreak detection.

Main Methods:

  • Generalization of receiver operating characteristic (ROC) curves to incorporate detection time alongside sensitivity and specificity.

Related Experiment Videos

  • Development of three-dimensional generalizations, termed timeliness-ROC surfaces.
  • Application and demonstration of these metrics using artificial examples and simulation contexts for disease outbreak surveillance.

    • Main Results:

    • The proposed metrics provide a framework for comparing surveillance methods that utilize both spatial and temporal data.
    • Timeliness-ROC surfaces offer a more comprehensive evaluation than traditional ROC curves by including detection speed.
    • Demonstrated differences in metric performance across various surveillance scenarios.

    Conclusions:

    • The introduced evaluation metrics enhance the assessment of disease surveillance systems, especially for detecting sudden outbreaks.
    • Incorporating timeliness into performance metrics is crucial for effective spatial-temporal disease surveillance.
    • The choice of surveillance method and its evaluation metric should consider the specific context and data characteristics.