A Critical Review on the Factors that Influence Opportunistic Premise Plumbing Pathogens: From Building Entry to Fixtures in Residences.

Residential buildings provide unique conditions for opportunistic premise plumbing pathogen (OPPP) exposure via aerosolized water droplets produced by showerheads, faucets, and tubs. The objective of this review was to critically evaluate the existing literature that assessed the impact of potentially enhancing conditions to OPPP occurrence associated with residential plumbing and to point out knowledge gaps. Comprehensive studies on the topic were found to be lacking. Major knowledge gaps identified include the assessment of OPPP growth in the residential plumbing, from building entry to fixtures, and evaluation of the extent of the impact of typical residential plumbing design (e.g., trunk and branch and manifold), components (e.g., valves and fixtures), water heater types and temperature setting of operation, and common pipe materials (copper, PEX, and PVC/CPVC). In addition, impacts of the current plumbing code requirements on OPPP responses have not been assessed by any study and a lack of guidelines for OPPP risk management in residences was identified. Finally, the research required to expand knowledge on OPPP amplification in residences was discussed.

What Can Utilities Expect from New Lead Fifth-Liter Sampling Based on Historic First-Draw Data?

The United States Environmental Protection Agency recently released their most sweeping overhaul to the Lead and Copper Rule in three decades. One of the most significant changes is requiring a fifth-liter (L5) sample at homes with lead service lines (LSLs) rather than the original first-liter (L1) sample for a demonstration of compliance with water lead level (WLL) limits. We analyzed sequential sampling data from three large water systems and compliance data from Michigan utilities-which base compliance on the 90th percentile of the greater of L1 and L5 samples-to evaluate whether L5 WLLs better represent water in contact with LSLs and to explore regulatory impacts of including L5 samples in compliance monitoring. The sequential sampling data demonstrated that it is impossible to use a single sample volume within a sequential profile to universally capture the volume of water in an LSL. While L5 is not always a reliable indicator of water in contact with an LSL, Michigan compliance data showed that the L5 sample is more likely to be from an LSL and can identify utilities that benefit from an improved corrosion control treatment. Michigan compliance data indicate that it is likely that L5 sampling will result in more systems having a higher 90th percentile WLL and that a high proportion of the systems likely to exceed regulatory action levels based on L5 samples can be identified through a retrospective analysis of historic L1 data. The impact of the switch to L5 sampling on the effectiveness of corrosion control treatment over time has yet to be determined.

Analysis of building plumbing system flushing practices and communications.

Drinking water distribution system contamination incidents can prompt public agencies and drinking water utilities to issue do-not-drink and do-not-use advisories. After the contaminant is cleared from distribution mains, consumers are often directed to flush their plumbing. However, little validated guidance and few evaluated communications strategies are available on using flushing to decontaminate building water systems. Additionally, limited data support the effectiveness of current practices and recommendations. In this study, expert elicitation was used to assess existing flushing guidance and develop validated flushing guidance and communications for single-family residences. The resulting guidance recommends progressively opening all cold-water taps from the closest to point of entry to the furthest and allowing the water to run for at least 20 minutes. Hot-water taps should be opened progressively and run for at least 75 minutes. The guidance language and format conformed to grade-level and readability scores within recommended health communication ranges. The readability of eight other flushing guidance documents was also evaluated for contamination incidents from 2008-2015. Seven were written at a 10th-12th grade level, above the 6th-7th grade level recommended for health communications.

Modeling Rabbit Responses to Single and Multiple Aerosol Exposures of Bacillus anthracis Spores.

Survival models are developed to predict response and time-to-response for mortality in rabbits following exposures to single or multiple aerosol doses of Bacillus anthracis spores. Hazard function models were developed for a multiple-dose data set to predict the probability of death through specifying functions of dose response and the time between exposure and the time-to-death (TTD). Among the models developed, the best-fitting survival model (baseline model) is an exponential dose-response model with a Weibull TTD distribution. Alternative models assessed use different underlying dose-response functions and use the assumption that, in a multiple-dose scenario, earlier doses affect the hazard functions of each subsequent dose. In addition, published mechanistic models are analyzed and compared with models developed in this article. None of the alternative models that were assessed provided a statistically significant improvement in fit over the baseline model. The general approach utilizes simple empirical data analysis to develop parsimonious models with limited reliance on mechanistic assumptions. The baseline model predicts TTDs consistent with reported results from three independent high-dose rabbit data sets. More accurate survival models depend upon future development of dose-response data sets specifically designed to assess potential multiple-dose effects on response and time-to-response. The process used in this article to develop the best-fitting survival model for exposure of rabbits to multiple aerosol doses of B. anthracis spores should have broad applicability to other host-pathogen systems and dosing schedules because the empirical modeling approach is based upon pathogen-specific empirically-derived parameters.

Dose-response models incorporating aerosol size dependency for Francisella tularensis.

The effect of bioaerosol size was incorporated into predictive dose-response models for the effects of inhaled aerosols of Francisella tularensis (the causative agent of tularemia) on rhesus monkeys and guinea pigs with bioaerosol diameters ranging between 1.0 and 24 µm. Aerosol-size-dependent models were formulated as modification of the exponential and ß-Poisson dose-response models and model parameters were estimated using maximum likelihood methods and multiple data sets of quantal dose-response data for which aerosol sizes of inhaled doses were known. Analysis of F. tularensis dose-response data was best fit by an exponential dose-response model with a power function including the particle diameter size substituting for the rate parameter k scaling the applied dose. There were differences in the pathogen's aerosol-size-dependence equation and models that better represent the observed dose-response results than the estimate derived from applying the model developed by the International Commission on Radiological Protection (ICRP, 1994) that relies on differential regional lung deposition for human particle exposure.

Dose-response assessment for influenza A virus based on data sets of infection with its live attenuated reassortants.

Reported data sets on infection of volunteers challenged with wild-type influenza A virus at graded doses are few. Alternatively, we aimed at developing a dose-response assessment for this virus based on the data sets for its live attenuated reassortants. Eleven data sets for live attenuated reassortants that were fit to beta-Poisson and exponential dose-response models. Dose-response relationships for those reassortants were characterized by pooling analysis of the data sets with respect to virus subtype (H1N1 or H3N2), attenuation method (cold-adapted or avian-human gene reassortment), and human age (adults or children). Furthermore, by comparing the above data sets to a limited number of reported data sets for wild-type virus, we quantified the degree of attenuation of wild-type virus with gene reassortment and estimated its infectivity. As a result, dose-response relationships of all reassortants were best described by a beta-Poisson model. Virus subtype and human age were significant factors determining the dose-response relationship, whereas attenuation method affected only the relationship of H1N1 virus infection to adults. The data sets for H3N2 wild-type virus could be pooled with those for its reassortants on the assumption that the gene reassortment attenuates wild-type virus by at least 63 times and most likely 1,070 times. Considering this most likely degree of attenuation, 10% infectious dose of H3N2 wild-type virus for adults was estimated at 18 TCID50 (95% CI = 8.8-35 TCID50). The infectivity of wild-type H1N1 virus remains unknown as the data set pooling was unsuccessful.

Animal and human dose-response models for Brucella species.

Human Brucellosis is one of the most common zoonotic diseases worldwide. Disease transmission often occurs through the handling of domestic livestock, as well as ingestion of unpasteurized milk and cheese, but can have enhanced infectivity if aerosolized. Because there is no human vaccine available, rising concerns about the threat of Brucellosis to human health and its inclusion in the Center for Disease Control's Category B Bioterrorism/Select Agent List make a better understanding of the dose-response relationship of this microbe necessary. Through an extensive peer-reviewed literature search, candidate dose-response data were appraised so as to surpass certain standards for quality. The statistical programming language, "R," was used to compute the maximum likelihood estimation to fit two models, the exponential and the approximate beta-Poisson (widely used for quantitative risk assessment) to dose-response data. Dose-response models were generated for prevalent species of Brucella: Br. suis, Br. melitensis, and Br. abortus. Dose-response models were created for aerosolized Br. suis exposure to guinea pigs from pooled studies. A parallel model for guinea pigs inoculated through both aerosol and subcutaneous routes with Br. melitensis showed that the median infectious dose corresponded to a 30 colony-forming units (CFU) dose of Br. suis, much less than the N(50) dose of about 94 CFU for Br. melitensis organisms. When Br. melitensis was tested subcutaneously on mice, the N(50) dose was higher, 1,840 CFU. A dose-response model was constructed from pooled data for mice, rhesus macaques, and humans inoculated through three routes (subcutaneously/aerosol/intradermally) with Br. melitensis.

Dose-response model of Coxiella burnetii (Q fever).

Q fever is a zoonotic disease caused by the intracellular gram-negative bacterium Coxiella burnetii (C. burnetii), which only multiplies within the phagolysosomal vacuoles. Q fever may manifest as acute or chronic disease. The acute form is generally not fatal and manifestes as self-controlled febrile illness. Chronic Q fever is usually characterized by endocarditis. Many animal models, including humans, have been studied for Q fever infection through various exposure routes. The studies considered different endpoints including death for animal models and clinical signs for human infection. In this article, animal experimental data available in the open literature were fit to suitable dose-response models using maximum likelihood estimation. Research results for tests of severe combined immunodeficient mice inoculated intraperitoneally (i.p.) with C. burnetii were best estimated with the Beta-Poisson dose-response model. Similar inoculation (i.p.) trial outcomes conducted on C57BL/6J mice were best fit by an exponential model, whereas those tests run on C57BL/10ScN mice were optimally represented by a Beta-Poisson dose-response model.

Development of a dose-response model for SARS coronavirus.

In order to develop a dose-response model for SARS coronavirus (SARS-CoV), the pooled data sets for infection of transgenic mice susceptible to SARS-CoV and infection of mice with murine hepatitis virus strain 1, which may be a clinically relevant model of SARS, were fit to beta-Poisson and exponential models with the maximum likelihood method. The exponential model (k= 4.1 x l0(2)) could describe the dose-response relationship of the pooled data sets. The beta-Poisson model did not provide a statistically significant improvement in fit. With the exponential model, the infectivity of SARS-CoV was calculated and compared with those of other coronaviruses. The does of SARS-CoV corresponding to 10% and 50% responses (illness) were estimated at 43 and 280 PFU, respectively. Its estimated infectivity was comparable to that of HCoV-229E, known as an agent of human common cold, and also similar to those of some animal coronaviruses belonging to the same genetic group. Moreover, the exponential model was applied to the analysis of the epidemiological data of SARS outbreak that occurred at an apartment complex in Hong Kong in 2003. The estimated dose of SARS-CoV for apartment residents during the outbreak, which was back-calculated from the reported number of cases, ranged from 16 to 160 PFU/person, depending on the floor. The exponential model developed here is the sole dose-response model for SARS-CoV at the present and would enable us to understand the possibility for reemergence of SARS.

Dose-response models for inhalation of Bacillus anthracis spores: interspecies comparisons.

Because experiments with Bacillus anthracis are costly and dangerous, the scientific, public health, and engineering communities are served by thorough collation and analysis of experiments reported in the open literature. This study identifies available dose-response data from the open literature for inhalation exposure to B. anthracis and, via dose-response modeling, characterizes the response of nonhuman animal models to challenges. Two studies involving four data sets amenable to dose-response modeling were found in the literature: two data sets of response of guinea pigs to intranasal dosing with the Vollum and ATCC-6605 strains, one set of responses of rhesus monkeys to aerosol exposure to the Vollum strain, and one data set of guinea pig response to aerosol exposure to the Vollum strain. None of the data sets exhibited overdispersion and all but one were best fit by an exponential dose-response model. The beta-Poisson dose-response model provided the best fit to the remaining data set. As indicated in prior studies, the response to aerosol challenges is a strong function of aerosol diameter. For guinea pigs, the LD(50) increases with aerosol size for aerosols at and above 4.5 mum. For both rhesus monkeys and guinea pigs there is about a 15-fold increase in LD(50) when aerosol size is increased from 1 mum to 12 mum. Future experimental research and dose-response modeling should be performed to quantify differences in responses of subpopulations to B. anthracis and to generate data allowing development of interspecies correction factors.

Wastewater disinfection by peracetic acid: assessment of models for tracking residual measurements and inactivation.

With its potential for low (if any) disinfection byproduct formation and easy retrofit for chlorine contactors, peracetic acid (PAA) or use of PAA in combination with other disinfectant technologies may be an attractive alternative to chlorine-based disinfection. Examples of systems that might benefit from use of PAA are water reuse schemes or plants discharging to sensitive receiving water bodies. Though PAA is in use in numerous wastewater treatment plants in Europe, its chemical kinetics, microbial inactivation rates, and mode of action against microorganisms are not thoroughly understood. This paper presents results from experimental studies of PAA demand, PAA decay, and microbial inactivation, with a complementary modeling analysis. Model results are used to evaluate techniques for measurement of PAA concentration and to develop hypotheses regarding the mode of action of PAA in bacterial inactivation. Kinetic and microbial inactivation rate data were collected for typical wastewaters and may be useful for engineers in evaluating whether to convert from chlorine to PAA disinfection.