Consecutive Rate Model for Covid Infections and Deaths and Prediction of Level-Off Time

  • Amila Madiligama
  • , Zachary Vandervort
  • , Arshad Khan

Research output: Contribution to journalArticlepeer-review

Abstract

Covid-19 infection and death rates are predicted based on a simple two-step consecutive reaction rate model. The infection rate is analogous to the first step of a consecutive reaction that results in an intermediate, and the death rate is analogous to the second step of the consecutive reaction in which a small fraction of the intermediate terminates in a product formation irreversibly. The model has been thoroughly tested, especially with infection data from different countries and two of the USA states California and New York, and predicts a linear infection-time relationship in the early stage of Covid infection. That is, the number of infections in 6 days is double the number of infections in 3 days, and infections in 9 days is 3 times the number of infections in 3 days, etc. In the later stage, the infection curve deviates from the linear relationship and follows a first-order constant "half-life"relationship. In the time interval of one half-life, the infection rises to 50% of the level-off value (maximum); during the second half-life, it rises by another 25% (50/2); and in the third half-life, it rises by another 12.5% (25/2), etc. That is, the infection curve reaches 50% (one "half-life"), 75% (two half-lives), 87.5% (three half-lives), etc. of the level off value after the time interval of one to three half-lives. Available data support our predictions.

Original languageEnglish (US)
Pages (from-to)48059-48066
Number of pages8
JournalACS Omega
Volume7
Issue number51
DOIs
StatePublished - Dec 27 2022

All Science Journal Classification (ASJC) codes

  • General Chemistry
  • General Chemical Engineering

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