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

Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

1.3K
Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
1.3K
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

819
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:
819
Introduction to Epidemiology01:26

Introduction to Epidemiology

1.5K
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,...
1.5K
Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

425
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:
425
Causality in Epidemiology01:21

Causality in Epidemiology

1.4K
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...
1.4K
Study Designs in Epidemiology01:20

Study Designs in Epidemiology

789
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...
789

You might also read

Related Articles

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

Sort by
Same journal

The GA4GH Task Execution Application Programming Interface: Enabling Easy Multicloud Task Execution.

Computing in science & engineering·2025
Same journal

Comparing the Use of Research Resource Identifiers and Natural Language Processing for Citation of Databases, Software, and Other Digital Artifacts.

Computing in science & engineering·2025
Same journal

FluoRender Script: A Case Study of Lingua Franca in Translational Computer Science.

Computing in science & engineering·2023
Same journal

ANARI: A 3-D Rendering API Standard.

Computing in science & engineering·2022
Same journal

Cloud Computing for COVID-19: Lessons Learned From Massively Parallel Models of Ventilator Splitting.

Computing in science & engineering·2022
Same journal

Supercomputing Pipelines Search for Therapeutics Against COVID-19.

Computing in science & engineering·2022
See all related articles

Related Experiment Video

Updated: Dec 24, 2025

Author Spotlight: Integrating Computational and Experimental Approaches in Precision Oncology
07:03

Author Spotlight: Integrating Computational and Experimental Approaches in Precision Oncology

Published on: December 1, 2023

1.4K

Computational Epidemiology.

Pam Frost Gorder

    Computing in Science & Engineering
    |April 8, 2020
    PubMed
    Summary
    This summary is machine-generated.

    Computational epidemiology uses computing power to predict future disease spread, moving beyond traditional past-focused studies. This approach aims to unravel the complex dynamics of how infectious diseases propagate through populations.

    More Related Videos

    Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis
    07:11

    Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis

    Published on: November 10, 2023

    3.1K
    Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
    06:55

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

    Published on: January 8, 2020

    15.0K

    Related Experiment Videos

    Last Updated: Dec 24, 2025

    Author Spotlight: Integrating Computational and Experimental Approaches in Precision Oncology
    07:03

    Author Spotlight: Integrating Computational and Experimental Approaches in Precision Oncology

    Published on: December 1, 2023

    1.4K
    Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis
    07:11

    Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis

    Published on: November 10, 2023

    3.1K
    Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
    06:55

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

    Published on: January 8, 2020

    15.0K

    Area of Science:

    • Epidemiology
    • Computational Science
    • Public Health

    Background:

    • Traditional epidemiology primarily analyzes historical disease data.
    • Predicting future disease outbreaks remains a significant challenge.
    • Advancements in computing offer new possibilities for epidemiological research.

    Purpose of the Study:

    • To explore the application of computational methods in epidemiology.
    • To enhance the predictive capabilities of disease spread models.
    • To understand the complex dynamics of infectious disease transmission.

    Main Methods:

    • Utilizing advanced computing power and algorithms.
    • Developing computational models for disease transmission.
    • Analyzing large-scale datasets to inform predictions.

    Main Results:

    • Demonstrating the potential of computational approaches to forecast disease spread.
    • Identifying key factors influencing disease propagation through simulations.
    • Providing a framework for proactive public health interventions.

    Conclusions:

    • Computational epidemiology offers a powerful new paradigm for understanding and predicting disease outbreaks.
    • Harnessing computing power is crucial for advancing epidemiological insights.
    • This approach can significantly improve future public health strategies and disease management.