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

Simplified Synchronous Machine Model01:30

Simplified Synchronous Machine Model

204
The Synchronous Machine Model is a fundamental tool in analyzing and ensuring the transient stability of power systems. This model simplifies the representation of a synchronous machine under balanced three-phase positive-sequence conditions, assuming constant excitation and ignoring losses and saturation. The model is pivotal for understanding the behavior of synchronous generators connected to a power grid, particularly during transient events.
In this model, each generator is connected to a...
204
Second Order systems II01:18

Second Order systems II

96
In an underdamped second-order system, where the damping ratio ζ is between 0 and 1, a unit-step input results in a transfer function that, when transformed using the inverse Laplace method, reveals the output response. The output exhibits a damped sinusoidal oscillation, and the difference between the input and output is termed the error signal. This error signal also demonstrates damped oscillatory behavior. Eventually, as the system reaches a steady state, the error diminishes to zero.
96
Oscillations In An LC Circuit01:30

Oscillations In An LC Circuit

2.2K
An idealized LC circuit of zero resistance can oscillate without any source of emf by shifting the energy stored in the circuit between the electric and magnetic fields. In such an LC circuit, if the capacitor contains a charge q before the switch is closed, then all the energy of the circuit is initially stored in the electric field of the capacitor. This energy is given by
2.2K
RLC Circuit as a Damped Oscillator01:30

RLC Circuit as a Damped Oscillator

903
An RLC circuit combines a resistor, inductor, and capacitor, connected in a series or parallel combination.
Consider a series RLC circuit. Here, the presence of resistance in the circuit leads to energy loss due to joule heating in the resistance. Therefore, the total electromagnetic energy in the circuit is no longer constant and decreases with time. Since the magnitude of charge, current, and potential difference continuously decreases, their oscillations are said to be damped. This is...
903
Linear time-invariant Systems01:23

Linear time-invariant Systems

232
A system is linear if it displays the characteristics of homogeneity and additivity, together termed the superposition property. This principle is fundamental in all linear systems. Linear time-invariant (LTI) systems include systems with linear elements and constant parameters.
The input-output behavior of an LTI system can be fully defined by its response to an impulsive excitation at its input. Once this impulse response is known, the system's reaction to any other input can be...
232
Routh-Hurwitz Criterion I01:15

Routh-Hurwitz Criterion I

195
Consider an electrical power grid, where stability is essential to prevent blackouts. The Routh-Hurwitz criterion is a valuable tool for assessing system stability under varying load conditions or faults. By analyzing the closed-loop transfer function, the Routh-Hurwitz criterion helps determine whether the system remains stable.
To apply the Routh-Hurwitz criterion, a Routh table is constructed. The table's rows are labeled with powers of the complex frequency variable s, starting from the...
195

You might also read

Related Articles

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

Sort by
Same author

A computational model of spatial politics: Hotelling-downs model as statistical physics.

PloS one·2026
Same author

Frustrated supermolecules: The high-pressure phases of crystalline methane.

The Journal of chemical physics·2026
Same author

Field-induced phase transitions in ferro-antiferromagnetic diblock copolymers.

The Journal of chemical physics·2026
Same author

An empirical network study of the antimalarial supply chain in Ghana.

PloS one·2026
Same author

Hydrogen Vacancy Induced Superconductivity Collapse in A15 Lanthanum Hydride.

Physical review letters·2026
Same author

Supercoiling DNA with a free end.

Soft matter·2026
Same journal

The male-biased sex ratio in humans and its role in the transition from promiscuity to pair bonding.

Journal of theoretical biology·2026
Same journal

Quantifying the counter-intuitive effects of vaccination by coupling the transmission dynamics of COVID-19 and the evolution of human behaviors.

Journal of theoretical biology·2026
Same journal

An integrative model of FGF2-induced signaling and muscle cell proliferation.

Journal of theoretical biology·2026
Same journal

A hybrid reaction-diffusion and mechanical stimulus model for mandibular bone remodeling under chewing and vibratory loading.

Journal of theoretical biology·2026
Same journal

Integrated tick management strategies in fragmented peridomestic environments.

Journal of theoretical biology·2026
Same journal

Joint likelihood-free inference of the number of selected single nucleotide polymorphisms and their selection coefficients in an evolving population.

Journal of theoretical biology·2026
See all related articles

Related Experiment Video

Updated: Jun 16, 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

10.7K

Oscillation in the SIRS model.

Davide Marenduzzo1, Aidan T Brown1, Craig W Miller1

  • 1School of Physics and Astronomy, University of Edinburgh, Edinburgh, EH9 3FD, UK.

Journal of Theoretical Biology
|June 14, 2025
PubMed
Summary
This summary is machine-generated.

The SIRS epidemic model reveals intrinsic, non-seasonal oscillations. This boom-and-bust cycle, driven by waning immunity, explains recurring epidemics like COVID-19 without external factors.

Keywords:
EndemicEpidemic modelOmicron variant SARS-cov2OscillationsSIRS

More Related Videos

Observational Study Protocol for Repeated Clinical Examination and Critical Care Ultrasonography Within the Simple Intensive Care Studies
10:38

Observational Study Protocol for Repeated Clinical Examination and Critical Care Ultrasonography Within the Simple Intensive Care Studies

Published on: January 16, 2019

20.2K
A Reproducible Intensive Care Unit-Oriented Endotoxin Model in Rats
05:56

A Reproducible Intensive Care Unit-Oriented Endotoxin Model in Rats

Published on: February 20, 2021

2.0K

Related Experiment Videos

Last Updated: Jun 16, 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

10.7K
Observational Study Protocol for Repeated Clinical Examination and Critical Care Ultrasonography Within the Simple Intensive Care Studies
10:38

Observational Study Protocol for Repeated Clinical Examination and Critical Care Ultrasonography Within the Simple Intensive Care Studies

Published on: January 16, 2019

20.2K
A Reproducible Intensive Care Unit-Oriented Endotoxin Model in Rats
05:56

A Reproducible Intensive Care Unit-Oriented Endotoxin Model in Rats

Published on: February 20, 2021

2.0K

Area of Science:

  • Epidemiology
  • Mathematical Biology
  • Computational Science

Background:

  • The SIRS (Susceptible-Infected-Recovered-Susceptible) model describes disease dynamics.
  • Traditional models identify stable states: disease-free (I=0) and endemic (I>0).
  • External factors like seasonality are often invoked to explain epidemic fluctuations.

Purpose of the Study:

  • To investigate the intrinsic dynamics of the SIRS model.
  • To explore the emergence of oscillatory behavior in epidemic models.
  • To determine if waning immunity alone can drive regular epidemic cycles.

Main Methods:

  • Analytical investigation of the SIRS model.
  • Numerical simulations on a square lattice with noise.
  • Analysis of model solutions to identify stable states and oscillations.

Main Results:

  • The SIRS model exhibits two stable states: disease-free and endemic.
  • Implementation with noise or on a lattice reveals a third state: regular oscillations.
  • These oscillations represent intrinsic boom-and-bust epidemic cycles driven by waning immunity.

Conclusions:

  • Oscillatory epidemic behavior is an intrinsic property of the SIRS model.
  • Waning immunity, on a timescale of approximately ten weeks, can explain non-seasonal oscillations.
  • This intrinsic oscillatory behavior offers an explanation for patterns observed in diseases like COVID-19 (e.g., Omicron variant).