Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Steps in Outbreak Investigation01:18

Steps in Outbreak Investigation

492
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
492
Modeling with Differential Equations01:25

Modeling with Differential Equations

20
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...
20
Causality in Epidemiology01:21

Causality in Epidemiology

1.5K
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...
1.5K
Exponential Equations for Modeling Growth02:33

Exponential Equations for Modeling Growth

225
Exponential models are essential for describing rapid, multiplicative changes in natural systems, such as population growth. When a population doubles at regular intervals, the process can be modeled using a suitable base. For instance, a bacterial culture that doubles every three hours follows the model n(t)=n0⋅2t/3, where n(t) is the population at the time t.A more general model uses the natural base e, especially for continuous growth. This takes the form n(t)=n0⋅ert, where r is...
225
Population Growth00:57

Population Growth

27.8K
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.
27.8K
Hyperbolas01:30

Hyperbolas

399
A hyperbola is a conic section produced when a double-napped cone is intersected by a plane at an angle steeper than the slope of the cone, such that it cuts through both nappes. This intersection yields two separate, mirror-image curves known as branches, which open away from each other along the transverse axis. The nearest points on each branch to the hyperbola’s center are termed vertices, and the distance from the center to a vertex is denoted by a. Perpendicular to the transverse...
399

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Niaoduqing particles ameliorated tubulointerstitial fibrosis by suppressing IκB/NF-κB signalling pathway via inhibiting host- and gut microbiota-mediated tryptophan co-metabolism.

Microbiological research·2026
Same author

Emergence of spatiotemporal patterns beyond Turing-Hopf bifurcation in semi-arid vegetation systems.

Mathematical biosciences·2026
Same author

A systematic comparison of methodologies for the estimation of the serial interval.

Infectious Disease Modelling·2026
Same author

Association Between Preoperative Dyslipidemia and the Prognosis of Patients With Endometrial Cancer: A Retrospective Cohort Study.

The Kaohsiung journal of medical sciences·2026
Same author

Prevalence and Genotype of <i>Pentatrichomonas hominis</i> in Farmed Arctic Foxes (<i>Vulpes lagopus</i>) in Northern China.

Vector borne and zoonotic diseases (Larchmont, N.Y.)·2026
Same author

Efficacy of acupoint catgut embedding therapy for phlegm-turbidity and blood-stasis metabolic dysfunction-associated fatty liver disease.

World journal of gastrointestinal surgery·2026
Same journal

Dynamical thermalization and turbulence in social stratification models.

Chaos (Woodbury, N.Y.)·2026
Same journal

Endogenous regime switching driven by scalar-irreducible learning dynamics.

Chaos (Woodbury, N.Y.)·2026
Same journal

The coherence analysis and Laplacian spectrum applications of cycle-based iterative networks.

Chaos (Woodbury, N.Y.)·2026
Same journal

Hitting times, recurrence, and local dimension under nonstationary forcing with applications to climate data.

Chaos (Woodbury, N.Y.)·2026
Same journal

Multiscale deep reservoir computing for predicting chaotic dynamical systems.

Chaos (Woodbury, N.Y.)·2026
Same journal

Chaotic decoherence under finite resolution: Lyapunov-controlled interference suppression.

Chaos (Woodbury, N.Y.)·2026
查看所有相关文章

相关实验视频

Updated: Jan 18, 2026

Quantitative Analysis of Cell Edge Dynamics during Cell Spreading
10:54

Quantitative Analysis of Cell Edge Dynamics during Cell Spreading

Published on: May 22, 2021

5.9K

超级边缘大小驱动的多尺度流行病动态在超级图表上

Shu-Ling Yan1, Yun-Fei Wang2, Yi-Hong Li1

  • 1School of Mathematics, North University of China, Taiyuan 030051, Shanxi, China.

Chaos (Woodbury, N.Y.)
|January 16, 2026
PubMed
概括
此摘要是机器生成的。

高阶网络揭示了群体规模如何影响传染病的传播. 传染概率可能是恒定的,因附加效应和时间尺度而产生变化,影响流行病动态.

更多相关视频

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.6K
Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology
09:44

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Published on: March 8, 2024

5.8K

相关实验视频

Last Updated: Jan 18, 2026

Quantitative Analysis of Cell Edge Dynamics during Cell Spreading
10:54

Quantitative Analysis of Cell Edge Dynamics during Cell Spreading

Published on: May 22, 2021

5.9K
Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline
10:44

Inherent Dynamics Visualizer, an Interactive Application for Evaluating and Visualizing Outputs from a Gene Regulatory Network Inference Pipeline

Published on: December 7, 2021

2.6K
Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology
09:44

Author Spotlight: Advancing Large-Scale Neural Dynamics Through HD-MEA Technology

Published on: March 8, 2024

5.8K

科学领域:

  • 流行病学 流行病学
  • 网络科学 网络科学
  • 数学生物学 数学生物学

背景情况:

  • 传染病是全球主要的健康威胁.
  • 高级网络模型基于组的传输动态.
  • 群体大小对传播概率的影响尚未完全理解.

研究的目的:

  • 调查群体大小对流行病动态的多尺度影响.
  • 在超图上提出一个多尺度的流行病模型,包括两体和三体相互作用.
  • 分析添加效应和异质时间尺度对疾病传播的影响.

主要方法:

  • 在超图上开发了一种多尺度的流行病模型,具有两体和三体相互作用.
  • 统一的异质时间尺度使用传输强度.
  • 导出了基本的繁殖号码 (R0) 并进行了分叉分析.
  • 进行蒙特卡洛和数值模拟.

主要成果:

  • R0取决于双向和三向传输强度.
  • 个人传输显示向前分叉; 群组传输显示向后分叉.
  • 三元传输强度显著影响R0,稳定状态和溶液分布.

结论:

  • 群体互动的附加效应推动了多个规模的流行病动态.
  • 高阶相互作用,特别是三级相互作用,对于了解疾病传播至关重要.
  • 这些发现为群体传染病传播的机制提供了新的见解.