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

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 Assays06:03

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 Sepsis07:42

A Data-Driven Approach to Quantifying Immune States in Sepsis

Published on: February 7, 2025

391

Related Concept Videos

Immune Response Against Viral Pathogens01:29

Immune Response Against Viral Pathogens

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

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

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

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

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