NATURAL INACTIVATION KINETICS MODELING FOR A WATERBORNE ENTERIC VIRUS IN SURFACE WATER USING SPARSE REGRESSION AND HIERARCHICAL BAYESIAN ESTIMATION

Abstract

 Unplanned and planned wastewater reuse are increasing and promising practices for a sustainable surface water resource management. However, pathogenic risk associated with wastewater reuse is a main concern due to the presence of negligible number of infectious enteric viruses in wastewater treatment effluent. A natural inactivation kinetics model of a pathogenic microorganism is essential to fully implement the HACCP approach into the sanitation safety planning. This study aimed to develop a natural inactivation kinetics model of an enteric virus of which predictors were measurable chemical and physical indicators of water matrix. First, the dataset of the time-course decay of the genus enterovirus and the chemical and physical indicators were collected through a literature review to be applied to the model construction. Second, we employed the sparse regression to select the model explanatory variables among temperature, acidic pH, alkaline pH and virus initial concentration. The inactivation rate constant of the Hom model was expressed as a function of alkaline pH, logarithm of the virus initial concentration, squared temperature and squared acidic pH, and the empirical constant was expressed as a function of the inactivation rate constant and temperature. The model parameters were estimated using the hierarchical Bayesian estimation, which provided the 95% credible interval of the time-course decay of enterovirus under varied pH and temperature. Finally, we validated the model with the measured natural decay of Enterovirus 71 (EV71) in buffer solutions (pH 7.0, 7.5, 8.0 and 4oC, 20oC, respectively), and demonstrated that the EV71 concentration was successfully predicted within the 95% credible intervals under the tested environmental conditions. Further studies need to include the contribution of other virucidal factors such as sunlight irradiations and suspended solid to the inactivation kinetics model.