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

Viral Recombination00:57

Viral Recombination

Cells are sometimes infected by more than one virus at once. When two viruses disassemble to expose their genomes for replication in the same cell, similar regions of their genomes can pair together and exchange sequences in a process called recombination. Alternatively, viruses with segmented genomes can swap segments in a process called reassortment.
Mechanisms of Retrovirus-induced Cancers01:51

Mechanisms of Retrovirus-induced Cancers

Retroviruses are RNA viruses that have been shown to cause cancers in diverse species, including chickens, mice, cats, and monkeys. The RNA genomes of these viruses are first reverse-transcribed into single and then double-stranded DNA (dsDNA) copies. This dsDNA called proviral DNA then integrates into the host genome. Subsequently, the host cell transcribes the proviral DNA in concert with the chromosomal DNA. This leads to the production of viral RNA and proteins that assemble at the host...
Mechanisms of Retrovirus-induced Cancers01:51

Mechanisms of Retrovirus-induced Cancers

Retroviruses are RNA viruses that have been shown to cause cancers in diverse species, including chickens, mice, cats, and monkeys. The RNA genomes of these viruses are first reverse-transcribed into single and then double-stranded DNA (dsDNA) copies. This dsDNA called proviral DNA then integrates into the host genome. Subsequently, the host cell transcribes the proviral DNA in concert with the chromosomal DNA. This leads to the production of viral RNA and proteins that assemble at the host...
Cancers Originate from Somatic Mutations in a Single Cell02:21

Cancers Originate from Somatic Mutations in a Single Cell

Cancer arises from mutations in the critical genes that allow healthy cells to escape cell cycle regulation and acquire the ability to proliferate indefinitely. Though originating from a single mutation event in one of the originator cells, cancer progresses when the mutant cell lines continue to gain more and more mutations, and finally, become malignant. For example, chronic myelogenous leukemia (CML) develops initially as a non-lethal increase in white blood cells, which progressively...
Cancers Originate from Somatic Mutations in a Single Cell02:21

Cancers Originate from Somatic Mutations in a Single Cell

Cancer arises from mutations in the critical genes that allow healthy cells to escape cell cycle regulation and acquire the ability to proliferate indefinitely. Though originating from a single mutation event in one of the originator cells, cancer progresses when the mutant cell lines continue to gain more and more mutations, and finally, become malignant. For example, chronic myelogenous leukemia (CML) develops initially as a non-lethal increase in white blood cells, which progressively...
Infectious Diseases and Their Occurrence01:28

Infectious Diseases and Their Occurrence

Infectious diseases appear in populations through various transmission patterns, influenced by pathogen characteristics, population immunity, environmental conditions, and social behavior. Understanding these patterns is essential for effective public health surveillance and intervention. These categories—sporadic, outbreak, epidemic, pandemic, and endemic—help frame the nature and scope of disease events.Sporadic diseases occur irregularly and infrequently, without a predictable temporal or...

You might also read

Related Articles

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

Sort by
Same author

Effectiveness of screening protocols to reduce MRSA colonization in a pediatric hospital.

International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases·2026
Same author

Mapping the landscape of individual-based models for respiratory pathogen transmission in the pandemic and post-pandemic era (2020-2024): A systematic review.

Epidemics·2026
Same author

Scenario analysis for potential community spread of Andes virus (ANDV).

Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin·2026
Same author

Assessing the annual burden of tick-borne encephalitis virus infections, north-east Italy, 2017 to 2024.

Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin·2026
Same author

Implications for distancing measures on in-person school and work attendance from Italian post-pandemic social contact data.

Communications medicine·2026
Same author

Mosquito-borne disease among individuals experiencing homelessness in the USA: a literature review.

Journal of pest science·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: Jul 3, 2026

Development of Multiplex Real-Time RT-qPCR Assays for the Detection of SARS-CoV-2, Influenza A/B, and MERS-CoV
03:53

Development of Multiplex Real-Time RT-qPCR Assays for the Detection of SARS-CoV-2, Influenza A/B, and MERS-CoV

Published on: November 10, 2023

Coinfection can trigger multiple pandemic waves.

Stefano Merler1, Piero Poletti, Marco Ajelli

  • 1Fondazione Bruno Kessler, via Sommarive 18, Trento, Italy. merler@fbk.eu

Journal of Theoretical Biology
|July 9, 2008
PubMed
Summary
This summary is machine-generated.

Coinfection with acute respiratory infections (ARI) can trigger multiple influenza pandemic waves by increasing virus transmissibility. This model aligns with 1918 Spanish flu data, offering insights for pandemic mitigation strategies.

Related Experiment Videos

Last Updated: Jul 3, 2026

Development of Multiplex Real-Time RT-qPCR Assays for the Detection of SARS-CoV-2, Influenza A/B, and MERS-CoV
03:53

Development of Multiplex Real-Time RT-qPCR Assays for the Detection of SARS-CoV-2, Influenza A/B, and MERS-CoV

Published on: November 10, 2023

Area of Science:

  • Epidemiology
  • Virology
  • Mathematical Modeling

Background:

  • Influenza pandemics exhibit sequential epidemic waves, as seen in the 1918 Spanish flu.
  • Explanations for waves include contact network changes and viral genetic drift impacting herd immunity.
  • Coinfection with acute respiratory infections (ARIs) may enhance influenza virus transmissibility and contribute to pandemic dynamics.

Purpose of the Study:

  • To propose and analyze a mathematical model explaining multiple pandemic waves.
  • To investigate the role of coinfection with ARIs in triggering these waves.
  • To assess the model's congruence with historical pandemic data for mitigation insights.

Main Methods:

  • Development of a mathematical model incorporating coinfection dynamics.
  • Assumption of increased influenza transmissibility in coinfected individuals.
  • Comparison of model outputs with excess mortality data from the 1918 pandemic.

Main Results:

  • The proposed model successfully replicates multiple pandemic wave patterns.
  • Coinfection with ARIs is identified as a significant driver of these waves.
  • Model validation against 1918 pandemic mortality data shows strong agreement.

Conclusions:

  • Coinfection with ARIs can be a key factor in generating sequential waves during influenza pandemics.
  • The model provides a framework for understanding pandemic wave propagation.
  • Findings suggest that managing coinfections could be a crucial element in pandemic mitigation efforts.