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 Concept Videos

Principles of Disease Surveillance01:26

Principles of Disease Surveillance

859
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...
859

You might also read

Related Articles

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

Sort by
Same author

Timely Availability and Accessibility of Health Data: Meeting the Challenge of Pan-Canadian Health Charter Principle 6.

Healthcare management forum·2026
Same author

Coconstructing CHAMP, an Artificial Intelligence Chatbot for Pediatric Infectious Symptoms Management: Protocol for a Multiphase Participatory Study.

JMIR research protocols·2026
Same author

Spatial analysis of healthcare services availability and demand for people aged 65 and over in Québec.

Research in health services & regions·2026
Same author

Incidence of and Risk Factors for Lower Extremity Apophysitis in Children and Adolescents.

Sports medicine (Auckland, N.Z.)·2025
Same author

Machine Learning Applications in Population and Public Health: Guidelines for Development, Testing, and Implementation.

JMIR public health and surveillance·2025
Same author

Time-Varying Associations Between Physical Activity and Injury Risk Among Children.

Paediatric and perinatal epidemiology·2025
Same journal

Predicting Tuberculosis Outcomes Using Routine Surveillance Data in Chiang Mai, Thailand: Retrospective Cohort Study.

JMIR public health and surveillance·2026
Same journal

Multimodal Data Approaches for Examining the 2024-2025 Highly Pathogenic Avian Influenza Outbreak in the United States: Descriptive Study.

JMIR public health and surveillance·2026
Same journal

Encouraging Adults at Risk for Type 2 Diabetes to Enroll in Diabetes Prevention Programs Through a Media Campaign in Hawai'i: Cross-Sectional Study.

JMIR public health and surveillance·2026
Same journal

Experts' Opinions on the Sustainable Use of Digital Health Tools for Effective Future Pandemic Preparedness and Response: Questionnaire Study.

JMIR public health and surveillance·2026
Same journal

Retraction: Secular Trends in Gastric and Esophageal Cancer Attributable to Dietary Carcinogens From 1990 to 2019 and Projections Until 2044 in China: Population-Based Study.

JMIR public health and surveillance·2026
Same journal

Legal Infoveillance of Unlicensed Medical Practices in South Korea Through Criminal Court Decisions Using Machine Learning: Retrospective Observational Study.

JMIR public health and surveillance·2026
See all related articles

Related Experiment Video

Updated: May 7, 2026

Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

12.6K

Early Detection Intervals for Evaluating Event-Based Surveillance System: Reference Dataset Development Study.

Yannan Shen1, Philip AbdelMalik2, Russell J Steele3

  • 1Department of Epidemiology, Biostatistics and Occupational Health, School of Population and Global Health, Faculty of Medicine and Health Sciences, McGill University, Suite 1200, 2001 McGill College Avenue, Montreal, QC, H3A 1G1, Canada, 1 514-396-1153.

JMIR Public Health and Surveillance
|May 5, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces early detection intervals for the Omicron variant, revealing disparities in detection times across countries. High-income nations with better sequencing data had longer intervals, while low-income countries experienced shorter ones.

Keywords:
COVID-19SARS-CoV-2data qualitydatasetdetectionevaluationevent-based surveillanceinfectious disease outbreakpublic health surveillancesurveillance

More Related Videos

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

4.5K
A Precise and Autonomous System for the Detection of Insect Emergence Patterns
06:22

A Precise and Autonomous System for the Detection of Insect Emergence Patterns

Published on: January 9, 2019

7.4K

Related Experiment Videos

Last Updated: May 7, 2026

Design and Analysis for Fall Detection System Simplification
08:05

Design and Analysis for Fall Detection System Simplification

Published on: April 6, 2020

12.6K
Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention
06:37

Author Spotlight: Addressing Technical and Subjective Challenges in Measuring Classroom Attention

Published on: December 15, 2023

4.5K
A Precise and Autonomous System for the Detection of Insect Emergence Patterns
06:22

A Precise and Autonomous System for the Detection of Insect Emergence Patterns

Published on: January 9, 2019

7.4K

Area of Science:

  • Epidemiology
  • Public Health Surveillance
  • Genomic Epidemiology

Background:

  • Event-based surveillance (EBS) aids early detection of health threats using diverse data sources.
  • Evaluating EBS systems is challenging due to a lack of reference data on outbreak onsets.

Purpose of the Study:

  • Introduce the concept of an "early detection interval" for infectious diseases.
  • Create a dataset of these intervals for the SARS-CoV-2 Omicron variant across multiple countries.
  • Provide reference data to evaluate the timeliness of EBS systems.

Main Methods:

  • Defined "early detection interval" as time from pathogen introduction to detectability in surveillance data.
  • Determined Omicron introduction dates using phylogenetic studies and genome databases.
  • Estimated interval end dates via Bayesian change point detection on COVID-19 case counts.

Main Results:

  • Dataset includes early detection intervals for Omicron in 117 countries (median length 28 days).
  • High sequencing availability correlated with earlier start dates but prolonged intervals.
  • Low-income countries, underrepresented, showed shorter intervals (median 16 days).

Conclusions:

  • The created dataset facilitates EBS system evaluation and guides public health practice.
  • Highlights significant cross-country disparities in data quality, especially genomic data.
  • Emphasizes the need for enhanced data collection and sharing in low-resource settings.