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Retroviruses have a single-stranded RNA genome that undergoes a special form of replication. Once the retrovirus has entered the host cell, an enzyme called reverse transcriptase synthesizes double-stranded DNA from the retroviral RNA genome. This DNA copy of the genome is then integrated into the host’s genome inside the nucleus via an enzyme called integrase. Consequently, the retroviral genome is transcribed into RNA whenever the host’s genome is transcribed, allowing the...
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Related Experiment Video

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Daily Transfers, Archiving Populations, and Measuring Fitness in the Long-Term Evolution Experiment with Escherichia coli
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Epidemic evolutionarily stable strategies within an age-structured host population.

Andreas Eilersen1,2, Ottar N Bjørnstad3, Ruiyun Li4,5,6

  • 1Theoretical Biology Group, Department of Environmental Systems Science, ETH Zürich, Zürich 8092, Switzerland.

Proceedings of the National Academy of Sciences of the United States of America
|March 18, 2025
PubMed
Summary

Understanding pathogen evolution is key to infectious disease dynamics. This study models pathogen evolution, revealing that age-dependent host factors shape long-term pandemic outcomes and public health strategies.

Keywords:
demographicsepidemiologyevolutionmodellingtrade-off

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Area of Science:

  • Epidemiology
  • Evolutionary Biology
  • Public Health

Background:

  • Infectious disease dynamics are influenced by host-pathogen ecology and evolution.
  • Societal demographics, especially age structure, are crucial for understanding disease spread.
  • Rapid pathogen evolution, as seen in COVID-19, necessitates considering evolutionary dynamics.

Purpose of the Study:

  • To explore society-specific evolutionarily stable strategies (ESS) for pathogens during pandemics.
  • To investigate the influence of age-dependent host factors on pathogen evolution.
  • To predict long-term public health consequences based on pathogen evolutionary trajectories.

Main Methods:

  • Development of a demographically realistic model.
  • Incorporation of age-specific infection rates and infectivity durations.
  • Analysis of pathogen evolution under varying host frailty and mortality rates.

Main Results:

  • Identified conditions under which an ESS for pathogen evolution may exist.
  • Demonstrated that the pathogen's ESS is contingent upon age-dependent host mortality and frailty.
  • Highlighted the impact of evolutionary scenarios on long-term public health.

Conclusions:

  • Pathogen evolution and host demographics are intertwined, influencing disease dynamics.
  • Age-specific host factors critically shape the evolutionary stable strategies of pathogens.
  • Understanding these evolutionary dynamics is vital for predicting and managing future infectious disease outbreaks.