Search Results Heading

MBRLSearchResults

mbrl.module.common.modules.added.book.to.shelf
Title added to your shelf!
View what I already have on My Shelf.
Oops! Something went wrong.
Oops! Something went wrong.
While trying to add the title to your shelf something went wrong :( Kindly try again later!
Are you sure you want to remove the book from the shelf?
Oops! Something went wrong.
Oops! Something went wrong.
While trying to remove the title from your shelf something went wrong :( Kindly try again later!
    Done
    Filters
    Reset
  • Discipline
      Discipline
      Clear All
      Discipline
  • Is Peer Reviewed
      Is Peer Reviewed
      Clear All
      Is Peer Reviewed
  • Item Type
      Item Type
      Clear All
      Item Type
  • Subject
      Subject
      Clear All
      Subject
  • Year
      Year
      Clear All
      From:
      -
      To:
  • More Filters
1 result(s) for "Shinkle, Logan W."
Sort by:
Application and significance of SIRVB model in analyzing COVID-19 dynamics
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.