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Estimating pathogen spread using structured coalescent and birth-death models: A quantitative comparison.

Sophie Seidel1, Tanja Stadler1, Timothy G Vaughan1

  • 1Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland; Swiss Institute of Bioinformatics (SIB), Basel, Switzerland.

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Summary
This summary is machine-generated.

Comparing phylodynamic models for disease spread reveals the birth-death model excels in epidemic outbreaks, while both models perform well for endemic diseases. Accounting for population dynamics is key for accurate migration rate inference.

Keywords:
Birth–deathCoalescentPathogen spreadPhylodynamicsPhylogenetics

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Area of Science:

  • Epidemiology
  • Genomic Epidemiology
  • Phylodynamics

Background:

  • Understanding disease transmission between subpopulations is vital for effective control strategies.
  • Genomic epidemiology and phylodynamics utilize pathogen phylogenies to estimate disease spread.
  • Structured phylodynamic models, including coalescent and birth-death models, are commonly used but have distinct assumptions impacting migration rate accuracy.

Purpose of the Study:

  • To compare the accuracy of migration rate inference between the structured coalescent model (constant population size) and the multitype birth-death model (constant rate).
  • To evaluate model performance across various migration rates in both endemic disease and epidemic outbreak scenarios.

Main Methods:

  • A simulation study was conducted to contrast inferential outcomes of two structured phylodynamic models.
  • The models compared were the structured coalescent model with constant population size and the multitype birth-death model with a constant rate.
  • Simulations covered a range of migration rates relevant to endemic diseases and epidemic outbreaks.

Main Results:

  • For epidemic outbreaks, the birth-death model demonstrated superior accuracy in retrieving migration rates compared to the coalescent model.
  • In endemic disease scenarios, both models yielded comparable accuracy and coverage, with the coalescent model providing more precise estimates.
  • Both models accurately estimated disease source locations across all tested scenarios.

Conclusions:

  • For endemic diseases, either the coalescent or birth-death model can be used for migration rate estimation.
  • For epidemic outbreaks or scenarios with changing population sizes, the structured coalescent model with constant population size should be avoided due to potential inaccuracies.
  • Birth-death models or coalescent models that incorporate varying population sizes are recommended for epidemic scenarios; capturing exponential growth dynamics can enhance structured coalescent models.