Journal Article

Application and significance of SIRVB model in analyzing COVID-19 dynamics

Ayyash, Jonathan S., Ramasinghe, Lumbini P., Shinkle, Logan W., Zuercher, Aoife M., Plant-Collins, Terry A., Kelley, Tyler M., Ariyaratne, Pavithra, Chen, Jixin

2025

Overview

In the summer of 2024, COVID-19 positive cases spiked in many countries, but it is no longer a deadly pandemic thanks to global herd immunity to the SARS-CoV-2 viruses. In our physical chemistry lab in spring 2024, students practice kinetic models, SIR (Susceptible, Infected, and Recovered) and SIRV (Susceptible, Infected, Recovered, Vaccinated) using COVID-19 positive cases and vaccination data from World Health Organization (WHO). In this report, we further introduce virus breakthrough to the existing model updating it the SIRVB (Susceptible, Infectious, Recovered, Vaccinated, Breakthrough) model. We believe this is the simplest model possible to explain the COVID-19 kinetics/dynamics in all countries in the past four years. Parameters obtained from such practice correlate with many indices of different countries. These models and parameters have significant value to researchers and policymakers in predicting the stages of future outbreaks of infectious diseases.

• Publisher: Nature Publishing Group UK,Nature Publishing Group,Nature Portfolio
• Subject: 631/114 / 631/57 / 639/705 / 692/420 / COVID kinetic models / COVID-19 / COVID-19 - epidemiology / COVID-19 - immunology / COVID-19 - prevention & control / COVID-19 - virology / COVID-19 vaccines / Data analysis / Disease transmission / Epidemics / Global data analysis / Herd immunity / Humanities and Social Sciences / Humans / Immunity (Disease) / Immunity, Herd / Infectious diseases / Influenza / Kinetics / Models, Theoretical / multidisciplinary / Pandemics / Physical chemistry / Public health / SARS-CoV-2 / Science / Science (multidisciplinary) / Severe acute respiratory syndrome coronavirus 2 / SIR / SIRV / SIRVB / Teaching / Undergraduate teaching / Vaccination / Viruses