Deterministic and stochastic survival models of injured ozonated Giardia cysts
1Department of Food Science, University of Massachusetts, Amherst, MA, 01003, USA. micha.peleg@foodsci.umass.edu.
Abstract:
Giardia cysts exposed to short sublethal ozonation in lake waters continue to die-off well after the ozone complete dissipation. This delayed inactivation can be the manifestation of injured cysts' mortality, which the traditional Chick-Watson-Hom type models of disinfection do not account for. But it can be described by a slightly modified version of a general microbial survival model adapted for injured cysts or other targeted microorganisms surviving disinfection. The downward concavity of the cysts' semi-logarithmic survival ratio vs. time relationships suggests that the cysts' deaths had unimodal temporal distribution. Indeed, the cumulative (CDF) forms of the Weibull and lognormal distribution functions both had excellent fit to the experimental survival data. Such a survival pattern can also be described by a fully probabilistic model devised from the injured cysts' Markov chain, where the mortality's probability rate rises linearly with time. The stochastic model explains the ubiquitous observation that microbial survival curves become increasingly irregular and irreproducible as the number of survivors dwindles, regardless of their concavity degree and direction. Although based on ozonated Giardia cyst data, the concept should be applicable to the delayed mortality of other microorganisms surviving sublethal treatments of other kinds but unable to recover and/or multiply. KEY POINTS: • Deterministic and stochastic survival models can describe delayed inactivation. • The Weibull and lognormal distributions can describe cysts' times to mortality. • Stochastic model explains the progressively growing scatter in survival curves.
Insights
Delayed inactivation of Giardia cysts after ozone disinfection can be modeled using modified microbial survival models. Both deterministic and stochastic approaches, including Weibull and lognormal distributions, accurately describe cyst mortality patterns.
Area of Science:
- Environmental microbiology
- Water treatment technologies
- Public health
Background:
- Giardia cysts exhibit delayed inactivation post-ozonation, a phenomenon not explained by traditional disinfection models.
- Sublethal ozone exposure can injure cysts, leading to prolonged mortality after ozone dissipation.
Purpose of the Study:
- To investigate and model the delayed inactivation of Giardia cysts following sublethal ozonation.
- To adapt microbial survival models for injured microorganisms and assess their applicability to Giardia cyst inactivation.
Main Methods:
- Analysis of Giardia cyst survival data after exposure to sublethal ozone levels in lake water.
- Application of modified general microbial survival models, including Weibull and lognormal distribution functions (CDF).
- Development and application of a stochastic model based on a Markov chain for injured cysts.
Main Results:
- Delayed inactivation of Giardia cysts was observed, extending beyond ozone dissipation.
- Weibull and lognormal distribution functions provided an excellent fit to the experimental survival data.
- A stochastic model, with a linearly increasing mortality rate, accurately described the survival patterns and explained increasing scatter in survival curves.
Conclusions:
- Modified deterministic and stochastic models effectively describe delayed microbial inactivation, particularly for injured microorganisms.
- The Weibull and lognormal distributions are suitable for modeling Giardia cyst mortality times.
- The stochastic model provides a framework for understanding the variability in microbial survival curves during disinfection processes.
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