A generalized model for bacterial disinfection: Stochastic approach

Andres Argoti, Ronaldo G. Maghirang, Andrés Fernando González Barrios, Song Tien Chou, L. T. Fan

Research output: Contribution to journalArticlepeer-review


This work proposes a novel, generalized model for bacterial disinfection formulated in light of a stochastic paradigm. The model's formulation is based on an intensity of transition that is proportional to the product of general power functions of the bacteria's number concentration and time; thus, the generalized stochastic model embodies the results obtained from our earlier models. The proposed model gives rise to linear and non-linear cases of the master equation whose solution can be obtained analytically as well as numerically via Monte Carlo simulation. Moreover, the generalized stochastic model has been validated with a specific instance of bacterial disinfection. The model's analytical and numerical results are in excellent accord among themselves as well as with those obtained from our earlier models; in addition, the model's results tend to describe the available experimental data reasonably well.

Original languageEnglish (US)
Pages (from-to)218-225
Number of pages8
JournalBiochemical Engineering Journal
StatePublished - Oct 15 2016
Externally publishedYes


  • Bacteria
  • Disinfection
  • Dynamic modelling
  • Dynamic simulation
  • Kinetic parameters
  • Modelling

ASJC Scopus subject areas

  • Biotechnology
  • Bioengineering
  • Environmental Engineering
  • Biomedical Engineering


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