Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Distributions to Estimate Population Parameter

Distributions to Estimate Population Parameter

The accurate values of population parameters such as population proportion, population mean, and population standard deviation (or variance) are usually unknown. These are fixed values that can only be estimated from the data collected from the samples. The estimates of each of these parameters are sample proportion, the sample mean, and sample standard deviation (or variance). To obtain the values of these sample statistics, data are required that have particular distribution and central...

Introduction to Epidemiology

Introduction to Epidemiology

Epidemiology, known as the cornerstone of public health, involves studying the distribution and determinants of health-related events in defined populations and applying these insights to control health issues. This is essential for understanding how diseases spread, identifying populations at greater risk, and implementing measures to control or prevent outbreaks. Epidemiology addresses not only infectious diseases but also non-communicable conditions like cancer and cardiovascular disease,...

Sampling Plans

Sampling Plans

Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...

Confidence Intervals

Confidence Intervals

An unbiased point estimate is often insufficient to predict a population estimate, such as population mean or population proportion. In this scenario, a confidence interval is used. A confidence interval is an estimate similar to a sample proportion. However, unlike the point estimate which is a single value, the confidence interval contains a range of values. These values have lower and upper limits, known as confidence limits, and can be designated as L1 and L2, respectively.
A confidence...

Analysis of Population Pharmacokinetic Data

Analysis of Population Pharmacokinetic Data

Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...

Contaminants and Errors

Contaminants and Errors

Effective sample preparation is crucial for accurate and reliable laboratory analysis. During this process, two significant sources of error can arise: concentration bias from improper sample splitting and contamination caused by methods used to reduce particle size, such as grinding or homogenization. Identifying and minimizing these potential errors is crucial to ensuring the validity of the analysis.
Another key consideration is determining the appropriate number of samples required to...

You might also read

Related Articles

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

Sort by

Same author

Assessment of Mammalian Scavenger and Wild White-Tailed Deer Activity at White-Tailed Deer Farms.

Viruses·2025

Same author

Design and methodology for monitoring the occurrence of foodborne pathogens in meat and poultry in United States: Case study of Campylobacter on chicken.

International journal of food microbiology·2025

Same author

Differences in Salmonella Serotypes in Broiler Chickens Within and Between Slaughter Establishments in the United States.

Journal of food protection·2025

Same author

Use of biosecurity practices to prevent chronic wasting disease in Minnesota cervid herds.

Preventive veterinary medicine·2024

Same author

One Health as a Core Component of Veterinary Medicine: Defining Day-1 Public Health Competencies for the Veterinary Workforce.

Journal of veterinary medical education·2024

Same author

Oral Administration of a Novel, Synthetic Ketogenic Compound Elevates Blood β-Hydroxybutyrate Levels in Mice in Both Fasted and Fed Conditions.

Nutrients·2024

Search research articles

Related Experiment Video

Updated: Jun 25, 2026

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

Population inferences from targeted sampling with uncertain epidemiologic information.

Michael S Williams¹, Eric D Ebel, Scott J Wells

¹Risk Assessment and Residue Division, Office of Public Health Science, Food Safety Inspection Service-USDA, 2150 Centre Avenue, Building D, Fort Collins, CO 80526, USA. mike.williams@fsis.usda.gov

Preventive Veterinary Medicine

|February 10, 2009

Summary

Targeted sampling in animal epidemiology can improve disease detection and prevalence estimation. This study presents new methods to account for uncertainty in disease epidemiology, enhancing the reliability of targeted sampling approaches.

More Related Videos

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

Comparative Lesions Analysis Through a Targeted Sequencing Approach

Comparative Lesions Analysis Through a Targeted Sequencing Approach

Published on: November 5, 2019

Related Experiment Videos

Last Updated: Jun 25, 2026

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index

Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index

Published on: January 8, 2020

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

Comparative Lesions Analysis Through a Targeted Sequencing Approach

Comparative Lesions Analysis Through a Targeted Sequencing Approach

Published on: November 5, 2019

Area of Science:

Veterinary epidemiology
Biostatistics
Disease surveillance

Background:

Targeted sampling is a common data collection method in animal health studies.
It involves selecting samples from subpopulations with a higher probability of disease.
Accurate inferences from targeted samples depend on disease epidemiology, which is often uncertain.

Purpose of the Study:

To develop statistical estimators for disease detection and prevalence estimation using targeted sampling.
To modify these estimators to address uncertainty in disease epidemiological parameters.
To evaluate the impact of epidemiological uncertainty on targeted sampling results.

Main Methods:

Description of novel estimators for targeted sampling in disease surveillance.
Development of modified estimators incorporating uncertainty in epidemiological parameters.
Simulation study to assess the performance of the proposed estimators.

Main Results:

The study provides modified estimators for disease detection and prevalence under targeted sampling.
These estimators effectively account for uncertainty in disease epidemiology.
Simulation results demonstrate the influence of parameter uncertainty on estimation accuracy.

Conclusions:

The proposed estimators enhance the reliability of targeted sampling in animal epidemiology.
Accounting for epidemiological uncertainty is crucial for accurate disease detection and prevalence estimation.
This work offers improved tools for disease surveillance using targeted sampling strategies.