ArticleJournal of theoretical biology2023
A multi-strain model with asymptomatic transmission: Application to COVID-19 in the US.
Article in Journal of theoretical biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Modeling two-strain competition with reinfection: Mathematical analyses and epidemiological implications.Infectious Disease Modelling · 2026Article
- Uncovering the impact of infection routes on within-host MPXV dynamics: Insights from a mathematical modeling study.PLoS computational biology · 2025Article
- Dynamics of an SVEIR transmission model with protection awareness and two strains.Infectious Disease Modelling · 2025Article
- Using a multi-strain infectious disease model with physical information neural networks to study the time dependence of SARS-CoV-2 variants of concern.PLoS computational biology · 2025Article
- Modeling the XBB strain of SARS-CoV-2: Competition between variants and impact of reinfection.Journal of theoretical biology · 2023Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
COVID-19, induced by the SARS-CoV-2 infection, has caused an unprecedented pandemic in the world. New variants of the virus have emerged and dominated the virus population. In this paper, we develop a multi-strain model with asymptomatic transmission to study how the asymptomatic or pre-symptomatic infection influences the transmission between different strains and control strategies that aim to mitigate the pandemic. Both analytical and numerical results reveal that the competitive exclusion principle still holds for the model with the asymptomatic transmission. By fitting the model to the COVID-19 case and viral variant data in the US, we show that the omicron variants are more transmissible but less fatal than the previously circulating variants. The basic reproduction number for the omicron variants is estimated to be 11.15, larger than that for the previous variants. Using mask mandate as an example of non-pharmaceutical interventions, we show that implementing it before the prevalence peak can significantly lower and postpone the peak. The time of lifting the mask mandate can affect the emergence and frequency of subsequent waves. Lifting before the peak will result in an earlier and much higher subsequent wave. Caution should also be taken to lift the restriction when a large portion of the population remains susceptible. The methods and results obtained her e may be applied to the study of the dynamics of other infectious diseases with asymptomatic transmission using other control measures.
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