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

Infectious Diseases and Their Occurrence01:28

Infectious Diseases and Their Occurrence

82
Infectious diseases appear in populations through various transmission patterns, influenced by pathogen characteristics, population immunity, environmental conditions, and social behavior. Understanding these patterns is essential for effective public health surveillance and intervention. These categories—sporadic, outbreak, epidemic, pandemic, and endemic—help frame the nature and scope of disease events.Sporadic diseases occur irregularly and infrequently, without a predictable...
82
Models of Health Promotion and Illness Prevention II01:18

Models of Health Promotion and Illness Prevention II

2.1K
The person's health status fluctuates continually, varying from being in good health to becoming ill and returning to being healthy. To understand the concept of illness prevention, there are two models. First, the health-illness continuum model is a graphic representation of an individual's wellness. It states that a person is considered healthy in the absence of physical disease and the presence of good emotional health.
The agent-host-environment model states that disease results...
2.1K
Pharmacodynamic Models: Link Model and Systems Pharmacodynamic Model01:14

Pharmacodynamic Models: Link Model and Systems Pharmacodynamic Model

145
The link model is a fundamental pharmacokinetic-pharmacodynamic (PK–PD) approach to account for delayed drug responses when the observed effect does not immediately correlate with the drug's plasma concentration peak. This delay is mathematically addressed by introducing an effect compartment concentration, Ce, which is kinetically linked to the plasma concentration, Cp, via a first-order rate constant, ke0. The linkage allows for a more accurate prediction of drug effects over time. A...
145
Modeling with Differential Equations01:25

Modeling with Differential Equations

327
Population dynamics can be described mathematically by considering the population size P(t) as a function of time. The rate of change of the population is then represented by the derivative of P(t). A simple assumption is that the rate of growth is proportional to the size of the population itself. This leads to an exponential growth model, where the population increases rapidly without bound. While this is a useful first approximation, it does not reflect realistic long-term...
327
Causality in Epidemiology01:21

Causality in Epidemiology

2.1K
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...
2.1K
Infection01:20

Infection

11.3K
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...
11.3K

You might also read

Related Articles

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

Sort by
Same authorSame journal

A comparison of alternative vaccination strategies for protecting those vulnerable to illness, hospitalization, or death upon infection with SARS-CoV-2.

Journal of theoretical biology·2026
Same author

Modulating the interfacial solvation structure to promote hydroxyl migration for alkaline hydrogen oxidation.

Nature communications·2026
Same author

Microglia-vascular interactions after spinal cord injury: regulatory mechanisms and therapeutic advances.

Frontiers in immunology·2026
Same author

Artificial intelligence in thoracic surgery: a narrative review of clinical advances and applications in 2025.

Journal of thoracic disease·2026
Same author

Association of childhood maltreatment with risk of lung cancer: A mediation analysis from the UK biobank.

Child abuse & neglect·2026
Same author

Integrated bioinformatics and experimental validation identifies CLIC6 as a novel tumor suppressor regulating NF-κB signaling and immune microenvironment in nasopharyngeal carcinoma.

Translational oncology·2026

Related Experiment Video

Updated: Apr 26, 2026

A Mouse Model for the Transition of Streptococcus pneumoniae from Colonizer to Pathogen upon Viral Co-Infection Recapitulates Age-Exacerbated Illness
12:21

A Mouse Model for the Transition of Streptococcus pneumoniae from Colonizer to Pathogen upon Viral Co-Infection Recapitulates Age-Exacerbated Illness

Published on: September 28, 2022

3.9K

Emerging disease dynamics in a model coupling within-host and between-host systems.

Xiuli Cen1, Zhilan Feng2, Yulin Zhao1

  • 1Department of Mathematics, Sun Yat-sen University, Guangzhou, 510275, PR China.

Journal of Theoretical Biology
|August 6, 2014
PubMed
Summary

Coupling epidemiological and immunological models reveals complex disease dynamics. This integrated approach, using Toxoplasma gondii as an example, shows that disease control thresholds can differ significantly from isolated models.

Keywords:
Backward bifurcationBetween-host dynamicsCoupled systemsEnvironmentally driven diseaseWithin-host dynamics

More Related Videos

Author Spotlight: Advanced Enteroid Model for Studying Host-Pathogen Interactions
07:56

Author Spotlight: Advanced Enteroid Model for Studying Host-Pathogen Interactions

Published on: April 5, 2024

2.3K
An Experimental Model to Study Tuberculosis-Malaria Coinfection upon Natural Transmission of Mycobacterium tuberculosis and Plasmodium berghei
09:02

An Experimental Model to Study Tuberculosis-Malaria Coinfection upon Natural Transmission of Mycobacterium tuberculosis and Plasmodium berghei

Published on: February 17, 2014

21.3K

Related Experiment Videos

Last Updated: Apr 26, 2026

A Mouse Model for the Transition of Streptococcus pneumoniae from Colonizer to Pathogen upon Viral Co-Infection Recapitulates Age-Exacerbated Illness
12:21

A Mouse Model for the Transition of Streptococcus pneumoniae from Colonizer to Pathogen upon Viral Co-Infection Recapitulates Age-Exacerbated Illness

Published on: September 28, 2022

3.9K
Author Spotlight: Advanced Enteroid Model for Studying Host-Pathogen Interactions
07:56

Author Spotlight: Advanced Enteroid Model for Studying Host-Pathogen Interactions

Published on: April 5, 2024

2.3K
An Experimental Model to Study Tuberculosis-Malaria Coinfection upon Natural Transmission of Mycobacterium tuberculosis and Plasmodium berghei
09:02

An Experimental Model to Study Tuberculosis-Malaria Coinfection upon Natural Transmission of Mycobacterium tuberculosis and Plasmodium berghei

Published on: February 17, 2014

21.3K

Area of Science:

  • Mathematical Biology
  • Epidemiology
  • Immunology
  • Disease Modeling

Background:

  • Epidemiological and immunological models are typically studied in isolation.
  • Within-host and between-host disease processes are interconnected and occur simultaneously.
  • Coupling these processes may yield novel biological insights and alter disease control thresholds.

Purpose of the Study:

  • To develop and analyze a mathematical model that explicitly couples within-host and between-host dynamics for environmentally driven infectious diseases.
  • To investigate how the integration of these two sub-systems affects disease dynamics and control strategies.
  • To illustrate the implications using the spread and control of toxoplasmosis.

Main Methods:

  • Developed a mathematical model integrating within-host parasite load dynamics with between-host transmission dynamics.
  • Incorporated environmental contamination as a link between host parasite load and transmission.
  • Analyzed the model's dynamics, focusing on equilibria, reproduction numbers, and bifurcations.

Main Results:

  • Isolated within-host and between-host models exhibit standard dynamics (stable infection-free or unique positive equilibrium).
  • The coupled model demonstrates more complex dynamics, including backward bifurcations.
  • Backward bifurcations allow for multiple stable equilibria, even when the basic reproduction number is less than 1, impacting disease persistence.

Conclusions:

  • Explicitly coupling within-host and between-host disease dynamics is crucial for understanding complex epidemiological patterns.
  • Integrated models reveal that disease control thresholds can be substantially different compared to models studied in isolation.
  • The findings highlight the importance of considering host-environment-pathogen interactions for effective disease management, as exemplified by toxoplasmosis.