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

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...
Pharmacovigilance01:19

Pharmacovigilance

Post-marketing surveillance is a critical component of pharmaceutical regulation, often uncovering unanticipated adverse drug reactions (ADRs) once a drug is widely used over an extended period.
This process, termed pharmacovigilance, aims to detect, evaluate, and minimize harmful effects related to medication use. The data collection for pharmacovigilance depends on spontaneous reporting systems, where healthcare professionals or patients voluntarily report suspected ADRs.
In some cases, there...
Investigation of Disease Outbreaks01:23

Investigation of Disease Outbreaks

Multistate foodborne outbreaks pose significant public health risks and require meticulous investigation to identify sources and implement control measures. The Centers for Disease Control and Prevention (CDC) utilizes a dynamic seven-step process for these investigations, integrating data from laboratories, interviews, and environmental assessments to protect public health.Outbreak Detection: The detection of multistate outbreaks typically begins with PulseNet, the CDC's national laboratory...
Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
Prevalence and Incidence01:08

Prevalence and Incidence

In statistical epidemiology and health sciences, two essential metrics—prevalence and incidence—are fundamental for understanding disease dynamics within a population. These measures enable public health officials, epidemiologists, and researchers to assess the burden of diseases, allocate resources effectively, and design impactful public health policies and interventions.
Prevalence indicates the proportion of individuals in a population who have a specific disease or health condition at a...
Infectious Diseases and Their Occurrence01:28

Infectious Diseases and Their Occurrence

Infectious diseases appear in populations through various transmission patterns, influenced by pathogen characteristics, population immunity, environmental conditions, and social behavior. Understanding these patterns is essential for effective public health surveillance and intervention. These categories—sporadic, outbreak, epidemic, pandemic, and endemic—help frame the nature and scope of disease events.Sporadic diseases occur irregularly and infrequently, without a predictable temporal or...

You might also read

Related Articles

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

Sort by
Same author

Activation of the endocytosis pathway stratifies subtypes and therapeutic sensitivity in colorectal cancer.

Research square·2026
Same author

Published Salmonella risk assessment model contains major errors and inconsistencies - ERRATUM.

Epidemiology and infection·2026
Same author

Dosimetry Results from the Phase 1b/3 ACTION-1 Trial of [<sup>225</sup>Ac]Ac-DOTATATE (RYZ101) in Patients with Somatostatin Receptor-Expressing, Well-Differentiated GEP-NETs.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine·2026
Same author

Published <i>Salmonella</i> risk assessment model contains major errors and inconsistencies.

Epidemiology and infection·2026
Same author

ASO Visual Abstract: Practice Patterns of Graduates from a Surgical Oncology Fellowship Program.

Annals of surgical oncology·2026
Same author

Practice Patterns of Graduates from a Surgical Oncology Fellowship Program.

Annals of surgical oncology·2026

Related Experiment Videos

Analyzing BSE surveillance in low prevalence countries.

Mark Powell1, Aaron Scott, Eric Ebel

  • 1Office of Risk Assessment and Cost Benefit Analysis, U.S. Department of Agriculture, 1400 Independence Avenue SW, Washington, DC 20250, USA. mpowell@uce.usda.gov

Preventive Veterinary Medicine
|November 6, 2007
PubMed
Summary

Stratified analysis of bovine spongiform encephalopathy (BSE) surveillance data can reveal exposure differences. However, low prevalence populations may lack statistical power for cohort distinction, and over-stratification can increase risk estimate uncertainty.

Related Experiment Videos

Area of Science:

  • Veterinary epidemiology
  • Disease surveillance

Background:

  • Bovine spongiform encephalopathy (BSE) prevalence can vary within populations.
  • Stratified analysis of surveillance data is a potential tool for identifying exposure differences.
  • Effective disease prevention and control rely on accurate risk assessment.

Purpose of the Study:

  • To evaluate the utility of stratified analysis for BSE surveillance data.
  • To assess the impact of low prevalence on statistical power for cohort analysis.
  • To examine the effect of over-stratification on BSE risk estimates.

Main Methods:

  • Analysis of simulated BSE surveillance data across various population structures.
  • Power calculations for detecting prevalence differences between cohorts.
  • Sensitivity analysis of risk estimates under different stratification scenarios.

Main Results:

  • Stratified analysis can identify significant BSE exposure variations among cohorts.
  • In low prevalence settings, surveillance may lack the statistical power to differentiate cohorts effectively.
  • Over-stratification can lead to inflated uncertainty and potentially misleading risk estimates.

Conclusions:

  • Stratified analysis is valuable for understanding BSE epidemiology when prevalence varies.
  • Careful consideration of statistical power is crucial in low prevalence populations.
  • Minimizing over-stratification is essential for reliable BSE risk assessment and control strategies.