Modelling COVID-19 mutant dynamics: understanding the interplay between viral evolution and disease transmission
Fernando Saldaña1, Nico Stollenwerk1, Maíra Aguiar1,2
1Basque Center for Applied Mathematics (BCAM), Bilbao, Spain.
Royal Society Open Science
|November 4, 2024
Summary
Virus mutations drive complex dynamics. Milder variants may spread faster but lead to more hospitalizations due to wider, harder-to-control infections, impacting public health strategies.
Area of Science:
- Epidemiology
- Virology
- Mathematical Modeling
Background:
- Virus mutations create complex multi-strain dynamics often not fully represented in current models.
- Understanding factors influencing variant fitness and evolution is crucial for effective public health interventions.
Purpose of the Study:
- To explore virus spreading scenarios and gain qualitative insights into factors determining variant predominance.
- To propose a stochastic model for analyzing viral evolution and transmission dynamics.
Main Methods:
- Development of a two-strain stochastic model incorporating asymptomatic transmission, mutations, and disease import.
- Simulation of various virus spreading scenarios to analyze variant fitness and population-level predominance.
Main Results:
- Variants with milder symptoms tend to spread faster due to delayed detection and isolation.
- Increased transmissibility of milder variants can paradoxically lead to higher overall hospitalizations and fatalities.
- The model demonstrates a significant interplay between viral evolution and transmission dynamics.
Conclusions:
- The study provides a nuanced understanding of factors influencing the spread of different virus variants.
- The proposed model serves as a foundation for developing improved public health interventions and mitigation strategies.
Keywords:
COVID-19asymptomatic transmissiondisease importationinfectious disease modellingmutationsspillover eventstwo-strain dynamicsMore Related Videos
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