A Bayesian method of estimating kinetic parameters for the inactivation of Cryptosporidium parvum oocysts with chlorine dioxide and ozone.
The main objective of this paper is to use Bayesian methods to estimate the kinetic parameters for the inactivation kinetics of Cryptosporidium parvum oocysts with chlorine dioxide or ozone which are characterized by the delayed Chick-Watson model, i.e., a lag phase or shoulder followed by pseudo-first-order rate of inactivation. As the length of the lag phase (CT(lag)) is not known, Bayesian statistics provides a more accurate approach than traditional statistical methods to fitting the delayed Chick-Watson kinetics. Markov Chain Monte Carlo method is used to estimate CT(lag) and first-order rate constant values. This method is also used to estimate the minimum CT requirement (with safety factor) for 99% inactivation of C. parvum oocysts.
D000818:Animals; D001499:Bayes Theorem; D017606:Chlorine Compounds / Q000494:pharmacology*; D016785:Cryptosporidium parvum / Q000472:pathogenicity*; D005544:Forecasting; D007700:Kinetics; D033661:Oocysts; D010083:Oxidants, Photochemical / Q000494:pharmacology*; D010087:Oxides / Q000494:pharmacology*; D010126:Ozone / Q000494:pharmacology*; D018508:Water Purification / Q000379:methods*
D017606:Chlorine Compounds; D010083:Oxidants, Photochemical; D010087:Oxides; D010126:Ozone; C025109:chlorine dioxide