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

Introduction to Epidemiology01:26

Introduction to Epidemiology

883
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,...
883
Causality in Epidemiology01:21

Causality in Epidemiology

606
Causality or causation is a fundamental concept in epidemiology, vital for understanding the relationships between various factors and health outcomes. Despite its importance, there's no single, universally accepted definition of causality within the discipline. Drawing from a systematic review, causality in epidemiology encompasses several definitions, including production, necessary and sufficient, sufficient-component, counterfactual, and probabilistic models. Each has its strengths and...
606
Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

166
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:
166
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

464
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
464
Study Designs in Epidemiology01:20

Study Designs in Epidemiology

333
Epidemiological study designs are fundamental tools for investigating the distribution, determinants, and control of health conditions in populations. They help researchers understand the relationships between exposures and outcomes, and they broadly fall into two categories: "observational" and "experimental" studies.
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and...
333
Bias in Epidemiological Studies01:29

Bias in Epidemiological Studies

484
Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:  
484

You might also read

Related Articles

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

Sort by
Same authorSame journal

The complexities of comprehensive exams in epidemiology.

American journal of epidemiology·2026
Same author

Paralysis in public health: evidence as an alibi? - Authors' reply.

The Lancet. Public health·2026
Same author

Quantitative bias analysis for time to event data needs good validation data.

American journal of epidemiology·2026
Same author

Combined Oral Contraceptives and Stroke Risk in Individuals With Migraine With Aura.

Obstetrics and gynecology·2026
Same author

Hepatitis B and C Prevention, Screening and Diagnostic Services at HIV Treatment Sites: International epidemiology Databases to Evaluate AIDS.

Journal of acquired immune deficiency syndromes (1999)·2026
Same author

One- and Two-Year Outcomes of Switching to a Dolutegravir-Based ART Regimen: An Observational Emulation of Sequential Target Trials.

Open forum infectious diseases·2026

Related Experiment Video

Updated: Aug 14, 2025

High-throughput Detection of Respiratory Pathogens in Animal Specimens by Nanoscale PCR
11:00

High-throughput Detection of Respiratory Pathogens in Animal Specimens by Nanoscale PCR

Published on: November 28, 2016

12.0K

Toward Open and Reproducible Epidemiology.

Maya B Mathur, Matthew P Fox

    American Journal of Epidemiology
    |January 10, 2023
    PubMed
    Summary

    Open science practices, including data and code sharing, are increasingly adopted in social sciences to boost reproducibility. Their slower adoption in epidemiology highlights a need to foster these beneficial methods for enhanced research integrity.

    Area of Science:

    • Epidemiology
    • Social Sciences
    • Open Science

    Background:

    • Experimental social sciences have increasingly adopted open science practices since the 2010s.
    • Practices include sharing deidentified data, analytical code, and preregistering study protocols.
    • Evidence suggests these methods improve reproducibility and reduce selective reporting.

    Purpose of the Study:

    • To examine the slower adoption of open science practices in academic epidemiology compared to social sciences.
    • To highlight the importance of open science for ensuring the integrity and analytical reproducibility of complex epidemiologic studies.
    • To discuss how researchers can foster a culture of open science in epidemiology.

    Main Methods:

    • Review of open science adoption trends in social sciences and epidemiology.
    Keywords:
    meta-sciencepublication biasreplicationrobustness

    More Related Videos

    Reproducible dsRNA Microinjection and Oviposition Bioassay in Mosquitoes and House Flies
    08:41

    Reproducible dsRNA Microinjection and Oviposition Bioassay in Mosquitoes and House Flies

    Published on: November 8, 2018

    8.9K
    Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
    08:03

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

    Published on: December 7, 2021

    2.3K

    Related Experiment Videos

    Last Updated: Aug 14, 2025

    High-throughput Detection of Respiratory Pathogens in Animal Specimens by Nanoscale PCR
    11:00

    High-throughput Detection of Respiratory Pathogens in Animal Specimens by Nanoscale PCR

    Published on: November 28, 2016

    12.0K
    Reproducible dsRNA Microinjection and Oviposition Bioassay in Mosquitoes and House Flies
    08:41

    Reproducible dsRNA Microinjection and Oviposition Bioassay in Mosquitoes and House Flies

    Published on: November 8, 2018

    8.9K
    Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations
    08:03

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

    Published on: December 7, 2021

    2.3K
  • Discussion of characteristics of epidemiologic studies that impact open science implementation.
  • Consideration of strategies for promoting open science in epidemiology.

    • Main Results:

    • Open science adoption is slower in epidemiology than in social sciences.
    • Epidemiologic studies' complexity and late conception pose challenges to open science.
    • Open science offers benefits like clarified reasoning and organized workflows.

    Conclusions:

    • Fostering open science in epidemiology is crucial for research integrity and reproducibility.
    • Both established and early-career epidemiologists can promote open science through practice, mentorship, and editorial roles.
    • Wider adoption of open science practices can enhance the reliability and transparency of epidemiologic research.