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 Experiment Videos

Viral host jumps: moving toward a predictive framework.

Juliet R C Pulliam1

  • 1Ecology & Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA. jrpulli@emory.edu

Ecohealth
|July 24, 2008
PubMed
Summary
This summary is machine-generated.

Related Concept Videos

You might also read

Related Articles

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

Sort by
Same author

Burden of SARS-CoV-2 infection and severe illness in South Africa (March 2020-August 2022): a synthesis of epidemiological data.

BMJ public health·2025
Same author

Simulation-based validation of a method to detect changes in SARS-CoV-2 reinfection risk.

PLoS computational biology·2025
Same author

A generalised catalytic model to assess changes in risk for multiple reinfections with SARS-CoV-2.

PloS one·2025
Same author

Best practices for estimating and reporting epidemiological delay distributions of infectious diseases.

PLoS computational biology·2024
Same author

Modelling outbreak response impact in human vaccine-preventable diseases: A systematic review of differences in practices between collaboration types before COVID-19.

Epidemics·2023
Same author

Estimating the time-varying reproduction number for COVID-19 in South Africa during the first four waves using multiple measures of incidence for public and private sectors across four waves.

PloS one·2023
Same journal

Do One Health Networks Compete, Coordinate, or Both? Insights from a Cross-Network Dialogue.

EcoHealth·2026
Same journal

Antimicrobial Resistance in Staphylococcus aureus from Bats in Pakistan.

EcoHealth·2026
Same journal

Ecological Dynamics of Culex quinquefasciatus Larval Habitats in Purulia, India.

EcoHealth·2026
Same journal

Implementation of a One Health Surveillance System in the Democratic Republic of the Congo.

EcoHealth·2026
Same journal

Phylogenetic Analysis of bla<sub>CTX-M</sub> and bla<sub>TEM</sub> Genes in E. coli from Hospital Wastewater.

EcoHealth·2026
Same journal

Correction: Antimicrobial Resistance and Biofilm in Bacteria from Rehabilitated Sapajus libidinosus.

EcoHealth·2026
See all related articles

Predicting viral pathogen emergence requires understanding distinct processes. This study uses molecular features to rank virus families by their potential for host jump, aiding in predicting zoonotic disease risks.

Area of Science:

  • Virology
  • Epidemiology
  • Molecular Biology

Background:

  • Predicting viral pathogen emergence is crucial for public health.
  • Emergence involves complex processes, including host jumps.
  • Understanding factors driving viral emergence is a key challenge.

Purpose of the Study:

  • To develop a framework for predicting viral pathogen emergence in new host species.
  • To assess the utility of molecular characteristics in predicting viral emergence.
  • To distinguish between different processes of pathogen emergence.

Main Methods:

  • Outlined a framework using molecular characteristics to rank virus families.
  • Evaluated the a priori ability of viruses to complete emergence steps: encounter, infection, and propagation.

Related Experiment Videos

  • Compared molecular-based predictions with empirical observations of animal viruses infecting humans.

    • Main Results:

    • Molecular characteristics can predict viral families' potential for host jumps.
    • The framework aligns with observed patterns of animal viruses infecting humans.
    • Identified limitations of molecular-only approaches for predicting encounter and propagation.

    Conclusions:

    • Molecular features provide a basis for predicting viral emergence potential.
    • Ecology and host-specific factors are essential for comprehensive emergence prediction.
    • A multi-faceted approach is needed to accurately forecast viral pathogen emergence.