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

Modeling with Differential Equations01:25

Modeling with Differential Equations

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...
Mechanistic Models: Compartment Models in Individual and Population Analysis01:23

Mechanistic Models: Compartment Models in Individual and Population Analysis

Mechanistic models are utilized in individual analysis using single-source data, but imperfections arise due to data collection errors, preventing perfect prediction of observed data. The mathematical equation involves known values (Xi), observed concentrations (Ci), measurement errors (εi), model parameters (ϕj), and the related function (ƒi) for i number of values. Different least-squares metrics quantify differences between predicted and observed values. The ordinary least squares (OLS)...
Population Growth00:57

Population Growth

Population size is dynamic, increasing with birth rates and immigration, and decreasing with death rates and emigration. In ideal conditions with unlimited resources, populations can increase exponentially, which plots as a J-shaped growth rate curve of population size against time. This type of curve is characteristic of newly-introduced invasive species, or populations that have suffered catastrophic declines and are rebounding.
Vector Algebra: Method of Components01:08

Vector Algebra: Method of Components

It is cumbersome to find the magnitudes of vectors using the parallelogram rule or using the graphical method to perform mathematical operations like addition, subtraction, and multiplication. There are two ways to circumvent this algebraic complexity. One way is to draw the vectors to scale, as in navigation, and read approximate vector lengths and angles (directions) from the graphs. The other way is to use the method of components.
In many applications, the magnitudes and directions of...
Buffers: Buffer Capacity01:09

Buffers: Buffer Capacity

Buffer capacity is the quantitative measure of a buffer to resist the change in pH. As shown in the following equation, the buffer capacity, denoted by 'beta', is expressed as the number of moles of acid or base needed to change the pH of a one-liter buffer solution by 1 unit. Here, Ca and Cb indicate the number of moles of acid and base, respectively. Note that dpH represents the change in pH.
In the graph, pH is plotted as a function of the number of moles of base (Cb) added to a weak acid...
Multicompartment Models: Overview01:14

Multicompartment Models: Overview

Multicompartment models are mathematical constructs that depict how drugs are distributed and eliminated within the body. They segment the body into several compartments, symbolizing various physiological or anatomical areas connected through drug transfer processes such as absorption, metabolism, distribution, and elimination.
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...

You might also read

Related Articles

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

Sort by
Same author

Erythrocyte Count, Anemia, and the Human Natural Lifespan Limit: Evidence from the Long Life Family Study.

bioRxiv : the preprint server for biology·2026
Same author

Lower hippocampal volume partly mediates the association between rs6859 in the <i>NECTIN2</i> gene and Alzheimer's disease: new findings from causal mediation analysis of ADNI data.

Frontiers in aging neuroscience·2026
Same author

Traffic-related air pollution significantly aggravates the detrimental effect of infections on the risk of Alzheimer's disease and other dementias, especially in non-carriers of <i>APOE4</i>.

Frontiers in dementia·2026
Same author

Basic Science and Pathogenesis.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2025
Same author

Developing Topics.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2025
Same author

Developing Topics.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2025

Related Experiment Video

Updated: May 21, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

An age-structured extension to the vectorial capacity model.

Vasiliy N Novoseltsev1, Anatoli I Michalski, Janna A Novoseltseva

  • 1Institute of Control Sciences, Moscow, Russia.

Plos One
|June 23, 2012
PubMed
Summary

New models incorporating age-dependent vector mortality offer a more accurate understanding of disease transmission. This research refines vectorial capacity and basic reproductive number (R(0)) calculations, crucial for effective vector-borne disease prevention strategies.

More Related Videos

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
09:01

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

Published on: May 7, 2014

Vector Competence Analyses on Aedes aegypti Mosquitoes using Zika Virus
10:35

Vector Competence Analyses on Aedes aegypti Mosquitoes using Zika Virus

Published on: May 31, 2020

Related Experiment Videos

Last Updated: May 21, 2026

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness
03:14

Augmenting Large Language Models via Vector Embeddings to Improve Domain-Specific Responsiveness

Published on: December 6, 2024

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance
09:01

A Method for Investigating Age-related Differences in the Functional Connectivity of Cognitive Control Networks Associated with Dimensional Change Card Sort Performance

Published on: May 7, 2014

Vector Competence Analyses on Aedes aegypti Mosquitoes using Zika Virus
10:35

Vector Competence Analyses on Aedes aegypti Mosquitoes using Zika Virus

Published on: May 31, 2020

Area of Science:

  • Epidemiology
  • Mathematical Biology
  • Vector Ecology

Background:

  • Vectorial capacity and basic reproductive number (R(0)) are key metrics for vector-borne disease transmission.
  • Traditional models often assume age-independent vector mortality, a simplification challenged by emerging evidence.
  • Age-dependent mortality in insect vectors significantly impacts disease dynamics and prevention.

Purpose of the Study:

  • To develop new equations for vectorial capacity and R(0) that account for age-dependent vector mortality.
  • To explore the behavior of these models under various mortality patterns.
  • To provide a quantitative framework for comparing disease prevention strategies.

Main Methods:

  • Survival analysis was used to derive new equations for vectorial capacity and R(0).
  • The study explored model behavior across different age-dependent and age-independent mortality patterns.
  • A framework was developed for an age-structured extension of the vectorial capacity paradigm.

Main Results:

  • New equations for vectorial capacity and R(0) are valid for any vector mortality pattern.
  • The framework allows for a refined understanding of pathogen transmission dynamics.
  • Quantitative insights are provided on the impact of vector longevity reduction versus other prevention strategies.

Conclusions:

  • Accounting for age-dependent mortality is critical when vector densities are low, influencing R(0) above or below 1.
  • Complex interactions between birth and death rates in age-structured populations necessitate these models.
  • Data scarcity on field vector mortality patterns remains a limiting factor for model evaluation.