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

Immune Response Against Viral Pathogens01:29

Immune Response Against Viral Pathogens

1.4K
The immune system's response to viral infections is a complex and coordinated process involving natural killer (NK) cells, T cell-mediated responses, and antibody-mediated responses.
NK Cells
NK cells are a crucial part of our innate immune system, acting as the first line of defense against viral infections. These cells can recognize and kill infected cells without prior exposure to the virus, effectively slowing down the spread of infection. Additionally, NK cells produce proinflammatory...
1.4K
Factors Affecting the Risk of Infection01:26

Factors Affecting the Risk of Infection

13.1K
The hosts' susceptibility to infection depends on several factors. The integrity of the skin and mucous membranes helps protect the body against microbial attacks. When the skin is altered, the chance of infection, limb loss, and even death increases.
The integrity and count of the white blood cells help the body resist pathogens and fight infection. When impaired, it reduces the body's resistance to pathogens. The acidic pH levels of the gastrointestinal, genitourinary tracts, and skin...
13.1K
Assumptions of Survival Analysis01:15

Assumptions of Survival Analysis

280
Survival models analyze the time until one or more events occur, such as death in biological organisms or failure in mechanical systems. These models are widely used across fields like medicine, biology, engineering, and public health to study time-to-event phenomena. To ensure accurate results, survival analysis relies on key assumptions and careful study design.
280
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

755
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:
755
Parametric Survival Analysis: Weibull and Exponential Methods01:14

Parametric Survival Analysis: Weibull and Exponential Methods

861
Parametric survival analysis models survival data by assuming a specific probability distribution for the time until an event occurs. The Weibull and exponential distributions are two of the most commonly used methods in this context, due to their versatility and relatively straightforward application.
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...
861

You might also read

Related Articles

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

Sort by
Same author

Exploring meteorological drivers in the transmission dynamics of viral and bacterial diarrhea: A modeling study in Davao City, Philippines.

Mathematical biosciences·2026
Same author

Linking Infection, Immunity, and Symptoms for Age-Dependent Influenza Severity.

bioRxiv : the preprint server for biology·2026
Same author

Computational framework for streamlining the success of sequential antibiotic therapy.

npj antimicrobials and resistance·2025
Same author

Invariant set theory for predicting potential failure of antibiotic cycling.

Infectious Disease Modelling·2025
Same author

Multi-objective control to schedule therapies for acute viral infections.

Journal of mathematical biology·2025
Same author

Hybrid Neural Differential Equations to Model Unknown Mechanisms and States in Biology.

bioRxiv : the preprint server for biology·2024

Related Experiment Video

Updated: Dec 1, 2025

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

2.9K

Stability analysis in COVID-19 within-host model with immune response.

Alexis Erich S Almocera1, Griselda Quiroz2, Esteban A Hernandez-Vargas3,4

  • 1Division of Physical Sciences and Mathematics, College of Arts and Sciences, University of the Philippines Visayas, Philippines.

Communications in Nonlinear Science & Numerical Simulation
|November 9, 2020
PubMed
Summary

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) may overcome the body's T-cell response, leading to COVID-19 infection. Mathematical modeling reveals viral load dynamics near a critical bifurcation point.

Keywords:
BifurcationCOVID-19Effector T cell responseIn-host modelSARS-CoV-2

More Related Videos

Author Spotlight: Advancing Immune Monitoring in Critical Care Patients Using Whole Blood Assays
06:03

Author Spotlight: Advancing Immune Monitoring in Critical Care Patients Using Whole Blood Assays

Published on: September 20, 2024

1.6K
A Data-Driven Approach to Quantifying Immune States in Sepsis
07:42

A Data-Driven Approach to Quantifying Immune States in Sepsis

Published on: February 7, 2025

391

Related Experiment Videos

Last Updated: Dec 1, 2025

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

2.9K
Author Spotlight: Advancing Immune Monitoring in Critical Care Patients Using Whole Blood Assays
06:03

Author Spotlight: Advancing Immune Monitoring in Critical Care Patients Using Whole Blood Assays

Published on: September 20, 2024

1.6K
A Data-Driven Approach to Quantifying Immune States in Sepsis
07:42

A Data-Driven Approach to Quantifying Immune States in Sepsis

Published on: February 7, 2025

391

Area of Science:

  • Immunology
  • Mathematical Biology
  • Virology

Background:

  • The 2019 coronavirus disease (COVID-19) pandemic is caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2).
  • Understanding the in-host dynamics of SARS-CoV-2 infection is crucial for developing effective treatments.

Purpose of the Study:

  • To investigate the role of effector T-cell response in controlling SARS-CoV-2 replication.
  • To analyze the mathematical model of SARS-CoV-2 infection dynamics.

Main Methods:

  • Development of an in-host mathematical model.
  • Analysis of the stability of equilibrium points, focusing on viral load.
  • Identification of a bifurcation point related to viral replication and T-cell response.

Main Results:

  • The model suggests a unique positive equilibrium point indicating potential viral dominance.
  • The stability analysis highlights a bifurcation point where viral load can be sensitive to parameter changes.
  • This suggests SARS-CoV-2 may replicate rapidly enough to overwhelm the T-cell-mediated immune response.

Conclusions:

  • Mathematical insights into SARS-CoV-2 pathogenesis.
  • The T-cell response plays a critical role in determining infection outcome.
  • Viral replication rate is a key factor in overcoming host immunity.