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

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
Causality in Epidemiology01:21

Causality in Epidemiology

602
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...
602
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

109
Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
109
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

463
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:
463
Principles of Disease Surveillance01:26

Principles of Disease Surveillance

159
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...
159
Analysis of Population Pharmacokinetic Data01:12

Analysis of Population Pharmacokinetic Data

335
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...
335

You might also read

Related Articles

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

Sort by
Same author

Insulation between adjacent TADs is controlled by the width of their boundaries through distinct mechanisms.

Proceedings of the National Academy of Sciences of the United States of America·2025
Same author

Unraveling microglial spatial organization in the developing human brain with DeepCellMap, a deep learning approach coupled with spatial statistics.

Nature communications·2025
Same author

Unveiling the functional connectivity of astrocytic networks with AstroNet, a graph reconstruction algorithm coupled to image processing.

Communications biology·2025
Same author

Voltage mapping in subcellular nanodomains using electro-diffusion modeling.

The Journal of chemical physics·2024
Same author

Chromatin phase separated nanoregions explored by polymer cross-linker models and reconstructed from single particle trajectories.

PLoS computational biology·2024
Same author

Impact of Multiplex PCR in the Therapeutic Management of Severe Bacterial Pneumonia.

Antibiotics (Basel, Switzerland)·2024
Same journal

Analysis of strength degradation of coal and rock masses and stability of mined areas under long term immersion environment.

PloS one·2026
Same journal

Biogenic Silver-Selenium nanocomposite with anticancer activity and potent efficacy against vancomycin-resistant Staphylococcus aureus.

PloS one·2026
Same journal

Preparation and physicochemical characterization of a biodegradable chitosan/carboxymethyl cellulose hydrogel synthesized in NaOH/urea medium.

PloS one·2026
Same journal

Action-guilt, survivor-guilt, and depression in combat-related PTSD.

PloS one·2026
Same journal

Explainable machine learning for predicting activities of daily living at discharge in stroke patients: A retrospective study using SHAP interpretability.

PloS one·2026
Same journal

Deep learning based two-way feature depiction model for brain tumor detection.

PloS one·2026
See all related articles

Related Experiment Video

Updated: Aug 14, 2025

Multi-target Parallel Processing Approach for Gene-to-structure Determination of the Influenza Polymerase PB2 Subunit
22:10

Multi-target Parallel Processing Approach for Gene-to-structure Determination of the Influenza Polymerase PB2 Subunit

Published on: June 28, 2013

13.3K

Data-driven multiscale dynamical framework to control a pandemic evolution with non-pharmaceutical interventions.

Jürgen Reingruber1,2, Andrea Papale1, Stéphane Ruckly3

  • 1Department of Biology, Ecole Normale Superieure, University PSL, CNRS, Paris, France.

Plos One
|January 17, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a computational framework to manage pandemics using non-pharmaceutical interventions (NPIs). It models disease spread and recalibrates parameters with new data, aiding pandemic control strategies.

More Related Videos

Modeling The Lifecycle Of Ebola Virus Under Biosafety Level 2 Conditions With Virus-like Particles Containing Tetracistronic Minigenomes
10:11

Modeling The Lifecycle Of Ebola Virus Under Biosafety Level 2 Conditions With Virus-like Particles Containing Tetracistronic Minigenomes

Published on: September 27, 2014

36.4K
Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.2K

Related Experiment Videos

Last Updated: Aug 14, 2025

Multi-target Parallel Processing Approach for Gene-to-structure Determination of the Influenza Polymerase PB2 Subunit
22:10

Multi-target Parallel Processing Approach for Gene-to-structure Determination of the Influenza Polymerase PB2 Subunit

Published on: June 28, 2013

13.3K
Modeling The Lifecycle Of Ebola Virus Under Biosafety Level 2 Conditions With Virus-like Particles Containing Tetracistronic Minigenomes
10:11

Modeling The Lifecycle Of Ebola Virus Under Biosafety Level 2 Conditions With Virus-like Particles Containing Tetracistronic Minigenomes

Published on: September 27, 2014

36.4K
Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.2K

Area of Science:

  • Epidemiology
  • Computational Biology
  • Public Health

Background:

  • COVID-19 pandemic necessitated social restrictions to prevent healthcare system saturation.
  • Non-pharmaceutical interventions (NPIs) are crucial for pandemic control, especially with data-sharing advancements.
  • Computational models are vital for efficiently managing pandemics in dynamic environments.

Purpose of the Study:

  • To develop a data-driven computational framework for pandemic control using NPIs.
  • To model disease evolution both within and outside hospitals.
  • To enable real-time parameter recalibration with incoming data.

Main Methods:

  • Developed a time-discrete, age-stratified compartmental model with a dual time-scale for infection history.
  • Implemented inference methods and feedback procedures for parameter recalibration.
  • Calibrated the framework using French national hospitalization data and single-hospital clinical data.

Main Results:

  • Inferred changes in social contact matrices based on NPIs using testing and hospitalization data.
  • Estimated hidden pandemic properties like infection rates, hospitalization probability, and infection fatality ratio.
  • Demonstrated the dependence of reproduction numbers and herd immunity on social dynamics.

Conclusions:

  • The developed framework effectively models pandemic evolution and the impact of NPIs.
  • The study highlights the importance of data-driven computational approaches for pandemic management.
  • Findings provide insights into reproduction numbers and herd immunity influenced by societal behavior.