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

Parametric Survival Analysis: Weibull and Exponential Methods01:14

Parametric Survival Analysis: Weibull and Exponential Methods

694
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...
694
Causality in Epidemiology01:21

Causality in Epidemiology

1.1K
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...
1.1K
Nonlinear Pharmacokinetics: Michaelis-Menten Equation01:18

Nonlinear Pharmacokinetics: Michaelis-Menten Equation

569
The Michaelis–Menten equation is a fundamental model for describing capacity-limited kinetics in drug metabolism. It offers insights into the rate of decline of plasma drug concentration Cp over time, with Vmax and KM as pivotal parameters.
Vmax represents the maximum achievable process rate, while KM, known as the Michaelis constant, signifies the drug concentration at which the process rate reaches half its maximum. This relationship between Vmax, KM, and Cp gives rise to three distinct...
569
Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models00:57

Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models

168
Physiological pharmacokinetic models, often called flow-limited or perfusion models, typically assume a swift drug distribution between tissue and venous blood, creating a rapid drug equilibrium. This premise is based on the idea that drug diffusion is extremely fast, and the cell membrane presents no barrier to drug permeation. In this scenario, where no drug binding occurs, the drug concentration in the tissue equals that of the venous blood leaving the tissue. This greatly simplifies the...
168
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

599
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:
599
Compartment Models: Single-Compartment Model01:14

Compartment Models: Single-Compartment Model

2.6K
The single-compartment model serves as a simplified representation of the human body. This model assumes that the body functions as a single, well-mixed open compartment. When a drug is administered intravenously, it enters the body and quickly distributes uniformly. The drug then undergoes biotransformation and elimination, ultimately leaving the body. The volume of this compartment is referred to as the apparent volume of distribution into which the drug can uniformly distribute. In this...
2.6K

You might also read

Related Articles

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

Sort by
Same author

[Reliability and validity of impairment measure for parental food allergy-associated anxiety and coping tool in China].

Zhonghua yu fang yi xue za zhi [Chinese journal of preventive medicine]·2026
Same author

Observation of the Singly Cabibbo Suppressed Decay D^{0}→b_{1}(1235)^{-}e^{+}ν_{e} and Evidence for D^{+}→b_{1}(1235)^{0}e^{+}ν_{e}.

Physical review letters·2026
Same author

Rock art from at least 67,800 years ago in Sulawesi.

Nature·2026
Same author

Observation of a mixed close-packed structure in superionic water.

Nature communications·2025
Same author

Unraveling the Structure of Λ Hyperons with Polarized ΛΛ[over ¯] Pairs.

Physical review letters·2025
Same author

Precision CP Symmetry Test and Polarization Analysis in Σ^{+} Decays.

Physical review letters·2025
Same journal

Studying Synchronization of Neural Oscillators through NMDA-AMPA Receptor interactions.

Chaos, solitons, and fractals·2026
Same journal

Prediction of excitable wave dynamics using machine learning.

Chaos, solitons, and fractals·2025
Same journal

A network-based model to assess vaccination strategies for the COVID-19 pandemic by using Bayesian optimization.

Chaos, solitons, and fractals·2025
Same journal

COVID-19 dynamics and immune response: Linking within-host and between-host dynamics.

Chaos, solitons, and fractals·2024
Same journal

Ion gradient-driven bifurcations of a multi-scale neuronal model.

Chaos, solitons, and fractals·2023
Same journal

Growth Feedback Confers Cooperativity in Resource-Competing Synthetic Gene Circuits.

Chaos, solitons, and fractals·2023
See all related articles

Related Experiment Video

Updated: Oct 10, 2025

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

10.8K

Gompertz model in COVID-19 spreading simulation.

E Pelinovsky1,2, M Kokoulina3, A Epifanova3

  • 1National Research University - Higher School of Economics, Myasnitskaya st., 20, Moscow 101000, Russian Federation.

Chaos, Solitons, and Fractals
|December 13, 2021
PubMed
Summary
This summary is machine-generated.

The Gompertz model accurately describes COVID-19 growth dynamics. This study found the Gompertz model superior to the Verhulst model for predicting pandemic spread across 23 countries.

Keywords:
COVID-19Gompertz modelLogistic equationMathematical modeling

More Related Videos

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

20.0K
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

2.7K

Related Experiment Videos

Last Updated: Oct 10, 2025

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
10:46

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

Published on: December 9, 2015

10.8K
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

20.0K
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

2.7K

Area of Science:

  • Epidemiology
  • Mathematical Modeling

Background:

  • The COVID-19 pandemic presented unprecedented challenges in understanding disease transmission dynamics.
  • Accurate modeling is crucial for predicting epidemic trajectories and informing public health interventions.

Purpose of the Study:

  • To apply the Gompertz model to analyze COVID-19 case growth during the pandemic's first wave.
  • To compare the predictive accuracy of the Gompertz model against the logistic (Verhulst) model.

Main Methods:

  • Utilized official World Health Organization data for 23 countries.
  • Employed regression analysis to determine Gompertz model parameters.
  • Performed comparative analysis between Gompertz and Verhulst models.

Main Results:

  • The Gompertz model effectively characterized COVID-19 case growth dynamics.
  • The Gompertz model demonstrated higher predictive accuracy compared to the Verhulst model.
  • Analysis covered diverse geographical regions including Australia, USA, China, and Brazil.

Conclusions:

  • The Gompertz model offers a more accurate approach for modeling COVID-19 spread.
  • Findings support the utility of the Gompertz model in epidemiological forecasting.
  • This study provides valuable insights for pandemic preparedness and response strategies.