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

153
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:
153
Gene Flow02:39

Gene Flow

35.3K
Gene flow is the transfer of genes among populations, resulting from either the dispersal of gametes or from the migration of individuals.
35.3K
Threats to Biodiversity01:50

Threats to Biodiversity

22.4K
There have been five major extinction events throughout geological history, resulting in the elimination of biodiversity, followed by a rebound of species that adapted to the new conditions. In the current geological epoch, the Holocene, there is a sixth extinction event in progress. This mass extinction has been attributed to human activities and is thus provisionally called the Anthropocene. In 2019 the human population reached 7.7 billion people and is projected to comprise 10 billion by...
22.4K
Prevalence and Incidence01:08

Prevalence and Incidence

634
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...
634
Causality in Epidemiology01:21

Causality in Epidemiology

486
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...
486
Infection01:20

Infection

8.2K
When a pathogen enters the body and reproduces, it can cause an infection, damage body cells, and cause illness symptoms that eventually lead to disease. Therefore, its prevention requires breaking the chain of infection.
The chain begins with pathogens: bacteria, viruses, fungi, prions, or parasites such as protozoa helminths. These can be present on the skin as transient or resident flora, or they can be acquired from the environment. Identifying and treating the type of infection and...
8.2K

You might also read

Related Articles

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

Sort by
Same author

A global database of West Nile virus host prevalence and competence.

Scientific data·2026
Same author

The structure of pairwise competition drives sudden regime shifts in a microbe-plasmid model.

Journal of the Royal Society, Interface·2026
Same author

Evidence of kinship, overwintering, and Wolbachia presence in Aedes albopictus in urban areas and points of entry in the Netherlands.

Parasites & vectors·2026
Same author

Hydrological dynamics of a Mediterranean water drain network: Implications for Aedes albopictus surveillance and population growth control.

Journal of environmental management·2026
Same author

[COVID-19: spatio-temporal study in the large urban area of Madrid during five epidemic periods].

Gaceta sanitaria·2026
Same author

Invasion dynamics of the disease vector Aedes japonicus in Spain.

Scientific reports·2026
Same journal

Turbulent flow in a vortex separator with a directed pipe inlet.

Scientific reports·2026
Same journal

Systematic characteristic evaluation of clay-based cementitious material derived from calcium carbide residue and waste tile powder.

Scientific reports·2026
Same journal

Retraction Note: Improvement of a rapid diagnostic application of monoclonal antibodies against avian influenza H7 subtype virus using Europium nanoparticles.

Scientific reports·2026
Same journal

Applying large language models to spam detection in the Kazakh low-resource language setting.

Scientific reports·2026
Same journal

An open-source 3D printing system enabling in-situ freeze-thaw processing of hydrogels.

Scientific reports·2026
Same journal

An enhanced EfficientNet framework for automated waste classification using cosine annealing and label smoothing.

Scientific reports·2026
See all related articles

Related Experiment Video

Updated: Jul 23, 2025

Trajectory Data Analyses for Pedestrian Space-time Activity Study
16:14

Trajectory Data Analyses for Pedestrian Space-time Activity Study

Published on: February 25, 2013

13.6K

Epidemic thresholds and human mobility.

Marta Pardo-Araujo1, David García-García2,3, David Alonso1

  • 1Centre d'Estudis Avançats de Blanes (CEAB-CSIC), Blanes, Spain.

Scientific Reports
|July 14, 2023
PubMed
Summary
This summary is machine-generated.

This study introduces a flexible modeling framework to understand how human mobility and disease transmission impact early epidemic growth. The findings are crucial for improving outbreak preparedness and disease control strategies.

More Related Videos

Remote Laboratory Management: Respiratory Virus Diagnostics
14:56

Remote Laboratory Management: Respiratory Virus Diagnostics

Published on: April 6, 2019

33.2K
Monitoring Spatial Segregation in Surface Colonizing Microbial Populations
07:40

Monitoring Spatial Segregation in Surface Colonizing Microbial Populations

Published on: October 29, 2016

11.1K

Related Experiment Videos

Last Updated: Jul 23, 2025

Trajectory Data Analyses for Pedestrian Space-time Activity Study
16:14

Trajectory Data Analyses for Pedestrian Space-time Activity Study

Published on: February 25, 2013

13.6K
Remote Laboratory Management: Respiratory Virus Diagnostics
14:56

Remote Laboratory Management: Respiratory Virus Diagnostics

Published on: April 6, 2019

33.2K
Monitoring Spatial Segregation in Surface Colonizing Microbial Populations
07:40

Monitoring Spatial Segregation in Surface Colonizing Microbial Populations

Published on: October 29, 2016

11.1K

Area of Science:

  • Epidemiology
  • Mathematical Biology
  • Network Science

Background:

  • Understanding disease epidemics requires analyzing human behavior and infectious disease dynamics.
  • Human mobility patterns significantly influence the spread and growth of infectious diseases.

Purpose of the Study:

  • To propose a flexible modeling framework for assessing the impact of human mobility and disease transmission on early epidemic growth.
  • To provide insights applicable to outbreak preparedness and disease control.

Main Methods:

  • Utilized random matrix theory to calculate an epidemic threshold, analogous to the basic reproduction number.
  • Developed a SIR metapopulation model incorporating systematic and random human mobility patterns.
  • Analyzed the influence of transmission rates, mobility modes (commuting, migration), and network connectivity.

Main Results:

  • The epidemic threshold is determined by variations in disease transmission rates, mobility modes, and connectivity strengths.
  • The model can predict whether a disease is likely to establish in a population.
  • The framework elucidates the local incidence distribution based on mobility and transmission parameters.

Conclusions:

  • Human mobility and disease transmission are key drivers of early epidemic growth.
  • The proposed modeling framework offers valuable tools for outbreak preparedness.
  • Disease establishment and local incidence are predictable outcomes influenced by mobility and transmission dynamics.