COVID-19 Dynamics and Mutation: Linking Intra-Host and Inter-Hosts Dynamics Via Agent-Based Modeling Approach

动力学(音乐) 寄主(生物学) 2019年冠状病毒病(COVID-19) 突变 严重急性呼吸综合征冠状病毒2型(SARS-CoV-2) 2019-20冠状病毒爆发 生物 病毒学 遗传学 物理 医学 传染病(医学专业) 爆发 疾病 病理 基因 声学
作者
Matthew O. Adewole,Newton I. Okposo,Farah Aini Abdullah,Majid Khan Majahar Ali
出处
期刊:International Journal of Biomathematics [World Scientific]
标识
DOI:10.1142/s1793524524500955
摘要

The study addresses the global impact of COVID-19 by developing a mathematical model that combines within-host and between-host factors to better understand the disease’s dynamics. It begins by describing SARS-CoV-2 dynamics within individual human hosts using fractional-order differential equations. The model is shown to be Ulam–Hyers stable, ensuring reliable predictions. The research then investigates virus transmission from infected to susceptible individuals using agent-based modeling (ABM). This approach allows us to capture the diversity and heterogeneity among individuals, including variations in internal state of individuals, immune response and responses to interventions, making the model more realistic compared to aggregate models. The agent-based model places individuals on a square lattice, assigns health states (susceptible, infectious, or recovered), and relies on infected individuals’ viral load for transmission. Parameter values are stochastically generated via Latin hypercube sampling. The study further explores the impact of viral mutation and control measures. Simulations demonstrate that vaccination substantially reduces transmission but may not eliminate it entirely. The strategy is more effective when vaccinated individuals are evenly distributed across the population, as opposed to concentrated on one side. The research further reveals that while reducing transmission probability decreases infections by implementing prevention protocols, it does not proportionally correlate with the reduction magnitude. This discrepancy is attributed to the intervention primarily addressing inter-host transmission dynamics without directly influencing intra-host viral dynamics.
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