Hierarchical Bayesian modeling for predictive environmental microbiology toward a safe use of human excreta: Systematic review and meta-analysis.

The pathogen concentration in human excreta needs to be managed appropriately, but a predictive approach has yet to be implemented due to a lack of kinetics models for pathogen inactivation that are available under varied environmental conditions. Our goals were to develop inactivation kinetics models of microorganisms applicable under varied environmental conditions of excreta matrices and to identify the appropriate indicators that can be monitored during disinfection processes. We conducted a systematic review targeting previous studies that presented time-course decay of a microorganism and environmental conditions of matrices. Defined as a function of measurable factors including treatment time, pH, temperature, ammonia concentration and moisture content, the kinetic model parameters were statistically estimated using hierarchical Bayesian modeling. The inactivation kinetics models were constructed for Escherichia coli, Salmonella, Enterococcus, Ascaris eggs, bacteriophage MS2, enterobacteria phage phiX174 and adenovirus. The inactivation rates of a microorganism were predicted using the established model. Ascaris eggs were identified as the most tolerant microorganisms, followed by bacteriophage MS2 and Enterococcus. Ammonia concentration, temperature and moisture content were the critical factors for the Ascaris inactivation. Our model predictions coincided with the current WHO guidelines. The developed inactivation kinetics models enable us to predict microbial concentration in excreta matrices under varied environmental conditions, which is essential for microbiological risk management in emerging resource recovery practices from human excreta.

Viral Interference as a Factor of False-Negative in the Infectious Adenovirus Detection Using Integrated Cell Culture-PCR with a BGM Cell Line.

This study investigated the influence of viral interference on the detection of enteric viruses using the integrated cell culture (ICC)-PCR with a BGM cell line. It was possible to detect 102 plaque-forming units (PFU)/flask of enterovirus 71 (EV71) in spite of the presence of 104 PFU/flask of adenovirus 40 (AdV40). Meanwhile, 104 PFU/flask of AdV40 was not detected in the presence of 102 PFU/flask of EV71. This inhibition of AdV40 detection using ICC-PCR was attributable to the growth of EV71, because the addition of a growth inhibitor of EV71 (rupintrivir) neutralized the detection inhibition of AdV40. The growth inhibition of AdV40 under co-infection with EV71 is probably caused by the immune responses of EV71-infected cells. AdV is frequently used as a fecal contamination indicator of environmental water, but this study demonstrated that false-negative detection of infectious AdV using ICC-PCR could be caused by the co-existence of infectious EV in a water sample. The addition of rupintrivir could prevent false-negative detection of AdV using ICC-PCR. This study, therefore, emphasizes the importance of confirming the presence of multiple enteric viruses in a sample derived from environmental water prior to the application of ICC-PCR because the viral interference phenomenon may lead to the false-negative detection of target viruses.