Modeling the Dose Response Relationship of Waterborne Acanthamoeba.

This study developed dose response models for determining the probability of eye or central nervous system infections from previously conducted studies using different strains of Acanthamoeba spp. The data were a result of animal experiments using mice and rats exposed corneally and intranasally to the pathogens. The corneal inoculations of Acanthamoeba isolate Ac 118 included varied amounts of Corynebacterium xerosis and were best fit by the exponential model. Virulence increased with higher levels of C. xerosis. The Acanthamoeba culbertsoni intranasal study with death as an endpoint of response was best fit by the beta-Poisson model. The HN-3 strain of A. castellanii was studied with an intranasal exposure and three different endpoints of response. For all three studies, the exponential model was the best fit. A model based on pooling data sets of the intranasal exposure and death endpoint resulted in an LD50 of 19,357 amebae. The dose response models developed in this study are an important step towards characterizing the risk associated with free-living amoeba like Acanthamoeba in drinking water distribution systems. Understanding the human health risk posed by free-living amoeba will allow for quantitative microbial risk assessments that support building design decisions to minimize opportunities for pathogen growth and survival.

Analysis of the persistence of enteric markers in sewage polluted water on a solid matrix and in liquid suspension.

Addressing the persistence of bacterial indicators using qPCR and their respective DNA targets under various conditions is a critical part of risk assessment for water quality monitoring. The goal of this study was to examine the persistence of fecal indicator bacteria (FIB) via Escherichia coli uidA, enterococci 23S rDNA and Bacteroides thetataiotaomicron 1,6 alpha mannanase from cells attached to a solid matrix and in suspension. Raw sewage (10% vol/vol) was seeded into autoclaved river water with half of the sample volume in suspension and the other half was filtered onto membranes and stored at 4°, 27° and 37°C for up to 28 days. At various time points, DNA from cells was extracted, markers were quantified, and were fit to linear and non-linear models (first order exponential, biphasic (double) exponential, two-staged, log-logistic, and Gompertz 3-parameter). First order and biphasic exponential models fit 73% of the experimental data. Persistence increased significantly when the cells were stored in an attached state (p < 0.001). Increasing temperature had an inverse effect on persistence for the cells in suspension. Bacterial cells could be stored on a solid matrix at 4°, 27° and 37 °C for up to 27, 18, and 3 days, respectively, with <90% decay. The least stable indicator at 4°, 27° and 37 °C was B. thetataiotaomicron in suspension with T90 = 9.6, 1.8, and 1.1 days, respectively. The most persistent indicator was enterococci, with T90 > 28 days in an attached state at all temperatures.

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 model of murine typhus (Rickettsia typhi): time post inoculation and host age dependency analysis.

BACKGROUND: Rickettsia typhi (R. mooseri) is the causative agent of murine typhus. It is one of the most widely distributed flea-borne diseases with a relatively mild febrile initial illness with six to 14 days of incubation period. The bacterium is gram negative and an obligate intracellular pathogen. The disease is transmitted to humans and vertebrate host through fleabites or via contact with infected feces. This paper develops dose-response models of different routes of exposure for typhus in rodents. METHODS: Data from published articles were analyzed using parametric dose-response relationship models. Dose-response relationships were fit to data using the method of maximum likelihood estimation (MLE). RESULTS: Dose-response models quantifying the effects of different ages of rats and time post inoculation in BALB/c mice were analyzed in the study. Both the adult rats (inoculated intradermally) and newborn rats (inoculated subcutaneously) were best fit by exponential models and both distributions could be described by a single dose-response relationship. The BALB/C mice inoculated subcutaneously were best fit by Beta-Poisson models. The time post inoculation analysis showed that there was a definite time and response relationship existed in this case. CONCLUSIONS: Intradermally or subcutaneously inoculated rats (adult and newborn) models suggest that less than 1 plaque-forming unit (PFU) (1.33 to 0.38 in 95% confidence limits) of the pathogen is enough to seroconvert 50% of the exposed population on average. For the BALB/c mouse time post inoculation model, an average dose of 0.28 plaque-forming units (PFU) (0.75 to 0.11 in 95% confidence limits) will seroconvert 50% of the exposed mice.

Dose-response model of Rocky Mountain spotted fever (RMSF) for human.

Rickettsia rickettsii is the causative agent of Rocky Mountain spotted fever (RMSF) and is the prototype bacterium in the spotted fever group of rickettsiae, which is found in North, Central, and South America. The bacterium is gram negative and an obligate intracellular pathogen. The disease is transmitted to humans and vertebrate host through tick bites; however, some cases of aerosol transmission also have been reported. The disease can be difficult to diagnose in the early stages, and without prompt and appropriate treatment, it can be fatal. This article develops dose-response models of different routes of exposure for RMSF in primates and humans. The beta-Poisson model provided the best fit to the dose-response data of aerosol-exposed rhesus monkeys, and intradermally inoculated humans (morbidity as end point of response). The average 50% infectious dose among (ID50) exposed human population, N50, is 23 organisms with 95% confidence limits of 1 to 89 organisms. Similarly, ID10 and ID20 are 2.2 and 5.0, respectively. Moreover, the data of aerosol-exposed rhesus monkeys and intradermally inoculated humans could be pooled. This indicates that the dose-response models fitted to different data sets are not significantly different and can be described by the same relationship.

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.