Cryptosporidium dose-response studies: variation between hosts

Occurrence, transmission and risks assessment of pathogens in aquatic environments accessible to humans

Pathogens are ubiquitously detected in various natural and engineered water systems, posing potential threats to public health. However, it remains unclear which human-accessible waters are hotspots for pathogens, how pathogens transmit to these waters, and what level of health risk associated with pathogens in these environments. This review collaboratively focuses and summarizes the contamination levels of pathogens on the 5 water systems accessible to humans (natural water, drinking water, recreational water, wastewater, and reclaimed water). Then, we showcase the pathways, influencing factors and simulation models of pathogens transmission and survival. Further, we compare the health risk levels of various pathogens through Quantitative Microbial Risk Assessment (QMRA), and assess the limitations of water-associated QMRA application. Pathogen levels in wastewater are consistently higher than in other water systems, with no significant variation for Cryptosporidium spp. among five water systems. Hydraulic conditions primarily govern the transmission of pathogens into human-accessible waters, while environmental factors such as temperature impact pathogens survival. The median and mean values of computed public health risk levels posed by pathogens consistently surpass safety thresholds, particularly in the context of recreational waters. Despite the highest pathogens levels found in wastewater, the calculated health risk is significantly lower than in other water systems. Except pathogens concentration, variables like the exposure mode, extent, and frequency are also crucial factors influencing the public health risk in water systems. This review shares valuable insights to the more accurate assessment and comprehensive management of public health risk in human-accessible water environments.

Cross-connections in drinking water distribution networks: Quantitative microbial risk assessment in combination with fault tree analysis and hydraulic modelling

Deficiencies in drinking water distribution networks, such as cross-connections, may lead to contamination of the drinking water and pose a serious health risk to consumers. Cross-connections and backflows are considered among the most severe public health risks in distribution networks. The aim of this paper was to provide a framework for estimating the risk of infection from cross-connection and backflow events. Campylobacter, norovirus, and Cryptosporidium were chosen as reference pathogens for this study. The theoretical framework was constructed based on the fault tree analysis methodology. National aggregated cross-connection incident data was used to calculate the probability of a contamination event occurring in Swedish networks. Three risk cases were evaluated: endemic, elevated, and extreme. Quantitative microbial risk assessment (QMRA) was used to assess daily risk of infection for average national estimates. The framework was also evaluated using local data from the Gothenburg network. The daily risk of infection from cross-connection and backflow events in Swedish networks was generally above an acceptable target level of 10^-6 for all reference pathogens and modelled cases; the exception was for the Gothenburg system where the risk was lower than 10^-7. An outbreak case study was used to validate the framework results. For the outbreak case study, contaminant transport in the network was simulated using hydraulic modelling (EPANET), and risk estimates were calculated using QMRA. The outbreak simulation predicted between 97 and 148 symptomatic infections, while the epidemiological survey conducted during the outbreak reported 179 cases of illness. The fault tree analysis framework was successfully validated using an outbreak case study, though it was shown on the example of Gothenburg that local data is still needed for well-performing systems. The framework can help inform microbial risk assessments for drinking water suppliers, especially ones with limited resources and expertise in this area.

Review of generic screening level assumptions for quantitative microbial risk assessment (QMRA) for estimating public health risks from Australian drinking water sources contaminated with Cryptosporidium by recreational activities

As urban communities continue to grow, demand for recreational access (including swimming) in drinking water sources have increased, yet relatively little is understood about the public health implications this poses for drinking water consumers. Preventative risk-based approaches to catchment management, informed by quantitative microbial risk assessment (QMRA), requires accurate input data to effectively model risks. A sound understanding of the knowledge gaps is also important to comprehend levels of uncertainty and help prioritise research needs. Cryptosporidium is one of the most important causes of waterborne outbreaks of gastroenteritis globally due to its resistance to chlorine. This review was undertaken by Water Research Australia to provide the most up-to-date information on current Cryptosporidium epidemiological data and underlying assumptions for exposure assessment, dose response and risk assessment for generic components of QMRA for Cryptosporidium and highlights priorities for common research. Key interim recommendations and guidelines for numerical values for relatively simple screening level QMRA modelling are provided to help support prospective studies of risks to drinking water consumers from Cryptosporidium due to body-contact recreation in source water. The review does not cover site-specific considerations, such as the levels of activity in the source water, the influence of dilution and inactivation in reservoirs, or water treatment. Although the focus is Australia, the recommendations and numerical values developed in this review, and the highlighted research priorities, are broadly applicable across all drinking source water sources that allow recreational activities.

Environmental risk assessment by using disability adjusted life year via constructing of a generalized linear model for morbidity estimation of waterborne pathogens

The Environmental burden of disease (EBD) quantitatively evaluates the health impacts of pathogens by using the disability-adjusted life year (DALY) method. The life loss due to morbidity is a general expression for the EBD outcome and, thus, morbidity analysis is indispensable. Considering the deficiency of previous morbidity analysis methods, the objective of this study was to construct a linear morbidity model by using a generalized linear model (GLM) as a template and introducing exposure dose, pathogen toxicity and human immunity as impact variables. Human experimental data were collected for model fitting, and the results indicated a good fit of the majority of the pathogen data. Consequently, two practical cases of water reuse in Xi'an Siyuan University (Case 1) and Lake Cui, Kunming (Case 2) were selected for model validation. Results for case 1 indicated the major EBD to be attributed to rotaviruses (5.57 × 10^-7 DALYs, 95% confidence interval (CI): 4.46 × 10^-7-1.72 × 10^-4 DALYs) and sprinkling irrigation (5.12 × 10^-7 DALYs, 95% CI: 1.95 × 10^-7-1.47 × 10¹ DALYs). Conversely, that for case 2 is mainly attributed to noroviruses (1.42 × 10^-7 DALYs, 95% CI: 7.51 × 10^-11-2.67 × 10^-4 DALYs) and road flushing (1.62 × 10^-7 DALYs, 95% CI: 1.16 × 10^-7-2.67 × 10^-4 DALYs). However, comparison with the suggested threshold of 10^-6 DALYs indicated the EBDs for both cases are acceptable and, thus, water reuse is confirmed to be safe. The methodology for morbidity modelling proposed in this research can effectively compensate for missing data in DALY calculation and, thereby, help to optimize the process for EBD evaluation.

Evaluation of real-time qPCR-based methods to detect the DNA of the three protozoan parasites Cryptosporidium parvum, Giardia duodenalis and Toxoplasma gondii in the tissue and hemolymph of blue mussels (M. edulis)

The protozoan parasites Cryptosporidium spp., Giardia duodenalis and Toxoplasma gondii can be transmitted to humans through shellfish consumption. No standardized methods are available for their detection in these foods, and the performance of the applied methods are rarely described in occurrence studies. Through spiking experiments, we characterized different performance criteria (e.g. sensitivity, estimated limit of detection (eLD95_METH), parasite DNA recovery rates (DNA-RR)) of real-time qPCR based-methods for the detection of the three protozoa in mussel's tissues and hemolymph. Digestion of mussels tissues by trypsin instead of pepsin and the use of large buffer volumes was the most efficient for processing 50g-sample. Trypsin digestion followed by lipids removal and DNA extraction by thermal shocks and a BOOM-based technique performed poorly (e.g. eLD95_METH from 30 to >3000 parasites/g). But trypsin digestion and direct DNA extraction by bead-beating and FastPrep homogenizer achieved higher performance (e.g. eLD95_METH: 4-400 parasites/g, DNA-RR: 19-80%). Direct DNA recovery from concentrated hemolymph, by thermal shocks and cell lysis products removal was not efficient to sensitively detect the protozoa (e.g. eLD95_METH: 10-1000 parasites/ml, DNA-RR ≤ 24%). The bead-beating DNA extraction based method is a rapid and simple approach to sensitively detect the three protozoa in mussels using tissues, that can be standardized to different food matrices. However, quantification in mussels remains an issue.

Changes in Escherichia coli to enteric protozoa ratios in rivers: Implications for risk-based assessment of drinking water treatment requirements

Minimum treatment requirements are set in response to established or anticipated levels of enteric pathogens in the source water of drinking water treatment plants (DWTPs). For surface water, contamination can be determined directly by monitoring reference pathogens or indirectly by measuring fecal indicators such as Escherichia coli (E. coli). In the latter case, a quantitative interpretation of E. coli for estimating reference pathogen concentrations could be used to define treatment requirements. This study presents the statistical analysis of paired E. coli and reference protozoa (Cryptosporidium, Giardia) data collected monthly for two years in source water from 27 DWTPs supplied by rivers in Canada. E. coli/Cryptosporidium and E. coli/Giardia ratios in source water were modeled as the ratio of two correlated lognormal variables. To evaluate the potential of E. coli for defining protozoa treatment requirements, risk-based critical mean protozoa concentrations in source water were determined with a reverse quantitative microbial risk assessment (QMRA) model. Model assumptions were selected to be consistent with the World Health Organization (WHO) Guidelines for drinking-water quality. The sensitivity of mean E. coli concentration trigger levels to identify these critical concentrations in source water was then evaluated. Results showed no proportionalities between the log of mean E. coli concentrations and the log of mean protozoa concentrations. E. coli/protozoa ratios at DWTPs supplied by small rivers in agricultural and forested areas were typically 1.0 to 2.0-log lower than at DWTPs supplied by large rivers in urban areas. The seasonal variations analysis revealed that these differences were related to low mean E. coli concentrations during winter in small rivers. To achieve the WHO target of 10^-6 disability-adjusted life year (DALY) per person per year, a minimum reduction of 4.0-log of Cryptosporidium would be required for 20 DWTPs, and a minimum reduction of 4.0-log of Giardia would be needed for all DWTPs. A mean E. coli trigger level of 50 CFU 100 mL^-1 would be a sensitive threshold to identify critical mean concentrations for Cryptosporidium but not for Giardia. Treatment requirements higher than 3.0-log would be needed at DWTPs with mean E. coli concentrations as low as 30 CFU 100 mL^-1 for Cryptosporidium and 3 CFU 100 mL^-1 for Giardia. Therefore, an E. coli trigger level would have limited value for defining health-based treatment requirements for protozoa at DWTPs supplied by small rivers in rural areas.

Risk assessment of parasites in Norwegian drinking water: opportunities and challenges

Despite the relative prosperity of Scandinavian countries, contamination of the drinking water supply with parasites has occurred on various occasions in the last few decades. These events have resulted in outbreaks of disease involving several thousand cases and/or the necessity for implementation of boil-water advisories. Against this background, in 2008, and again in 2019, the Norwegian Food Safety Authority requested a risk assessment from an independent scientific body regarding parasites in Norwegian drinking water. On each occasion, it was requested that specific questions were addressed.

For the first assessment, data, both of general relevance and specific for Norway, were collected from appropriate sources, as available. Based on some of this information, a quantitative probability model was established and run to estimate the number of cases of waterborne cryptosporidiosis and giardiasis that may be expected in Norway, both in the general public and the immunocompromised, and under conditions where water treatment should be optimal, and also when water treatment efficacy may be compromised by weather conditions.

For the second assessment, approximately a decade after the first, an update on the previous assessment was requested. Differences in information availability and other changes between the two assessments were described; although more data were available at the second assessment, considerable gaps still remained. For both assessments, data on the occurrence of these parasites in the Norwegian population, particularly those infected in Norway, were considered a challenge. However, due to changes in reporting requirements in 2020, the situation was improved for the second assessment. In addition, data were lacking for both assessments on whether animals or humans are most likely to contaminate water sources, and the species and genotypes of these parasites in Norwegian animals. It was also noted that some of the newer data on parasite numbers detected in water samples should be treated with caution. Due to this, further modelling was not conducted. The relevance of risk-based sampling rather than ad hoc sampling of water sources was also addressed.

Despite the data gaps, this article provides an overview of the opportunities provided by conducting such assessments. In addition, some of the challenges encountered in attempting to estimate the risk posed from parasite contamination of water sources in Norway, particularly under predicted conditions of climate change, are described.

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Norwegian drinking water has been contaminated with Cryptosporidium and Giardia.

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Risk was assessed in both 2008–2009 and 2019–2020 by an independent body.

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A model approach was used in the first assessment and data gaps identified.

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In the second assessment, more data were available, but data gaps remained.

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Main challenges were lack of reliable data on infection and contamination.

Noroviruses are highly infectious but there is strong variation in host susceptibility and virus pathogenicity

Noroviruses are a major public health concern: their high infectivity and environmental persistence have been documented in several studies. Genetic sequencing shows that noroviruses are highly variable, and exhibit rapid evolution. A few human challenge studies have been performed with norovirus, leading to estimates of their infectivity. However, such incidental estimates do not provide insight into the biological variation of the virus and the interaction with its human host. To study the variation in infectivity and pathogenicity of norovirus, multiple challenge studies must be analysed jointly, to compare their differences and describe how virus infectivity and host susceptibility vary. Since challenge studies can only provide a small sample of the diversity in the natural norovirus population, outbreaks should be exploited as an additional source of information. The present study shows how challenge studies and 'natural experiments' can be combined in a multilevel dose response framework. Infectivity and pathogenicity are analysed by secretor status as a host factor, and genogroup as a pathogen factor. Infectivity, characterized as the estimated mean infection risk when exposed to 1 genomic copy (qPCR unit)is 0.28 for GI norovirus, and 0.076 for GII virus, both in Se⁺ subjects. The corresponding risks of acute enteric illness are somewhat lower, about 0.2 (GI) and 0.035 (GII), in outbreaks. Se^- subjects are protected, with substantially lower risks of infection (0.00007 and 0.015 at a dose of 1 GC of GI and GII virus, respectively). The present study shows there is considerable variability in risk of infection and especially risk of acute symptoms following infection with norovirus. These challenge and outbreak data consistently indicate high infectivity among secretor positives and protection in secretor negatives.

Outbreak-Based Giardia Dose-Response Model Using Bayesian Hierarchical Markov Chain Monte Carlo Analysis

Giardia is a zoonotic gastrointestinal parasite responsible for a substantial global public health burden, and quantitative microbial risk assessment (QMRA) is often used to forecast and manage this burden. QMRA requires dose-response models to extrapolate available dose-response data, but the existing model for Giardia ignores valuable dose-response information, particularly data from several well-documented waterborne outbreaks of giardiasis. The current study updates Giardia dose-response modeling by synthesizing all available data from outbreaks and experimental studies using a Bayesian random effects dose-response model. For outbreaks, mean doses (D) and the degree of spatial and temporal aggregation among cysts were estimated using exposure assessment implemented via two-dimensional Monte Carlo simulation, while potential overreporting of outbreak cases was handled using published overreporting factors and censored binomial regression. Parameter estimation was by Markov chain Monte Carlo simulation and indicated that a typical exponential dose-response parameter for Giardia is r = 1.6 × 10^-2 [3.7 × 10^-3 , 6.2 × 10^-2 ] (posterior median [95% credible interval]), while a typical morbidity ratio is m = 3.8 × 10^-1 [2.3 × 10^-1 , 5.5 × 10^-1 ]. Corresponding (logistic-scale) variance components were σ_r = 5.2 × 10^-1 [1.1 × 10^-1 , 9.6 × 10^-1 ] and σ_m = 9.3 × 10^-1 [7.0 × 10^-2 , 2.8 × 10⁰ ], indicating substantial variation in the Giardia dose-response relationship. Compared to the existing Giardia dose-response model, the current study provides more representative estimation of uncertainty in r and novel quantification of its natural variability. Several options for incorporating variability in r (and m) into QMRA predictions are discussed, including incorporation via Monte Carlo simulation as well as evaluation of the current study's model using the approximate beta-Poisson.

Optimizing the performance of conventional water treatment system using quantitative microbial risk assessment, Tehran, Iran

The performance of conventional drinking water treatment plants (WTPs) can be improved using quantitative microbial risk assessment (QMRA). A QMRA study on Cryptosporidium using actual pathogen density was conducted to examine the performance of Jalaliyeh WTP in Tehran, Iran. The infection risk and the burden of disease attributed to the parasite presence in finished water were estimated incorporating physical and chemical log reduction values (LRVs), using stochastic modeling and disinfection profiling. The risk and burden of disease were compared with health-based targets, i.e. one case of infection per 10,000 people or 10^-6 DALYs per person per year. The parasite's LRVs were 2.31 and 0.034 log provided by physico-chemical treatment and disinfection processes, respectively. The mean of estimated risk (111 cases per 10⁴ people per year) and the burden of disease (11.7 DALYs per 10⁶ people per year) both exceeded the targets. To control the excess risk, three QMRA-based disinfection scenarios were examined including: (1) employing chlorine dioxide (ClO₂) instead of chlorine (2) ozonation with a concentration of 0.75 mg/L (Ct = 22.5 min mg/L) and (3) UV irradiation with a dose of 10 mJ/cm². The LRV of parasite may be increased to 3.0, 5.1 and 4.9 log by employing ClO₂, ozonation and UV irradiation, respectively. The use of ozone or UV as alternative disinfectants, could enhance the disinfection efficacy and provide sufficient additional treatment against the excess risk of parasite. QMRA could make it easier applying appropriate improvement to conventional WTPs in order to increase the system performance in terms of health-based measures.

The application of quantitative microbial risk assessment to natural recreational waters: A review

This review examines the aims of and approaches to the Quantitative Microbial Risk Assessment (QMRA) of untreated recreational waters. The literature search was conducted on four databases and yielded 54 papers, which were analyzed on a quantitative (time-trend, geographical distribution, water type) and qualitative (aims, source of microbial data, pathogens and their measurement or estimation, ways to address variability and uncertainty, sensitivity analysis) basis. In addition, the parameters, implications, and limitations were discussed for each QMRA step. Since 2003, the number of papers has greatly increased, highlighting the importance of QMRA for the risk management of recreational waters. Nevertheless, QMRA still exhibits critical issues, above all regarding contamination data and dose-response relationships. To our knowledge, this is the first review to give a wide panoramic view on QMRA in relation to recreational exposure to untreated waters. This could be useful in identifying the current knowledge gaps and research needs.

Efficacy of Flushing and Chlorination in Removing Microorganisms from a Pilot Drinking Water Distribution System

To ensure delivery of microbiologically safe drinking water, the physical integrity of the distribution system is an important control measure. During repair works or an incident the drinking water pipe is open and microbiologically contaminated water or soil may enter. Before taking the pipe back into service it must be cleaned. The efficacy of flushing and shock chlorination was tested using a model pipe-loop system with a natural or cultured biofilm to which a microbial contamination (Escherichia coli, Clostridium perfringens spores and phiX174) was added. On average, flushing removed 1.5–2.7 log microorganisms from the water, but not the biofilm. In addition, sand added to the system was not completely removed. Flushing velocity (0.3 or 1.5 m/s) did not affect the efficacy. Shock chlorination (10 mg/L, 1–24 h) was very effective against E. coli and phiX174, but C. perfringens spores were partly resistant. Chlorination was slightly more effective in pipes with a natural compared to a cultured biofilm. Flushing alone is thus not sufficient after high risk repair works or incidents, and shock chlorination should be considered to remove microorganisms to ensure microbiologically safe drinking water. Prevention via hygienic working procedures, localizing and isolating the contamination source and issuing boil water advisories remain important, especially during confirmed contamination events.

Construction of a Dose-Illness Relationship via Modeling Morbidity and Application to Risk Assessment of Wastewater Reuse

A disease burden (DB) evaluation for environmental pathogens is generally performed using disability-adjusted life years with the aim of providing a quantitative assessment of the health hazard caused by pathogens. A critical step in the preparation for this evaluation is the estimation of morbidity between exposure and disease occurrence. In this study, the method of a traditional dose-response analysis was first reviewed, and then a combination of the theoretical basis of a "single-hit" and an "infection-illness" model was performed by incorporating two critical factors: the "infective coefficient" and "infection duration." This allowed a dose-morbidity model to be built for direct use in DB calculations. In addition, human experimental data for typical intestinal pathogens were obtained for model validation, and the results indicated that the model was well fitted and could be further used for morbidity estimation. On this basis, a real case of a water reuse project was selected for model application, and the morbidity as well as the DB caused by intestinal pathogens during water reuse was evaluated. The results show that the DB attributed to Enteroviruses was significant, while that for enteric bacteria was negligible. Therefore, water treatment technology should be further improved to reduce the exposure risk of Enteroviruses. Since road flushing was identified as the major exposure route, human contact with reclaimed water through this pathway should be limited. The methodology proposed for model construction not only makes up for missing data of morbidity during risk evaluation, but is also necessary to quantify the maximum possible DB.

Acute illness from Campylobacter jejuni may require high doses while infection occurs at low doses

Data from a set of different studies on the infectivity and pathogenicity of Campylobacter jejuni were analyzed with a multilevel model, allowing for effects of host species (nonhuman primates and humans) and different strains of the pathogen. All challenge studies involved high doses of the pathogen, resulting in all exposed subjects to become infected. In only one study a dose response effect (increasing trend with dose) for infection was observed. High susceptibility to infection with C. jejuni was found in a joint analysis of outbreaks and challenge studies. For that reason four outbreaks, associated with raw milk consumption, were also included in the present study. The high doses used for inoculation did not cause all infected subjects to develop acute enteric symptoms. The observed outcomes are consistent with a dose response effect for acute symptoms among infected subjects: a conditional illness dose response relation. Nonhuman primates and human volunteers did not appear to have different susceptibilities for developing enteric symptoms, but exposure in outbreaks (raw milk) did lead to a higher probability of symptomatic campylobacteriosis.

A risk-based approach for developing standards for irrigation with reclaimed water

A generalised quantitative risk assessment (QRA) is developed to assess the potential harm to human health resulting from irrigation with reclaimed water. The QRA is conducted as a backward calculation starting from a pre-defined acceptable risk level at the receptor point (defined as an annual infection risk of 10^-4 for pathogens and by reference doses (RfD) for chemical hazards) and results in an estimate of the corresponding acceptable concentration levels of the given hazards in the effluent. In this way the QRA is designed to inform the level of water treatment required to achieve an acceptable risk level and help establish reclaimed water quality standards. The QRA considers the exposure of human receptors to microbial and chemical hazards in the effluent through various exposure pathways and routes depending on the specific irrigation scenario. By considering multiple pathways and routes, a number of key aspects relevant to estimating human exposure to recycled water can be accounted for, including irrigation and crop handling practices (e.g., non-edible vs edible, spray vs. drip, withholding time) and volumes consumed (directly vs indirectly). The QRA relies on a large number of inputs, many of which were found to be highly uncertain. A possibilistic approach, based on fuzzy set theory, was used to propagate the uncertain input values through the QRA model to estimate the possible range of hazard concentrations that are deemed acceptable/safe for reclaimed water irrigation. Two scenarios were considered: amenity irrigation and irrigation of ready-to-eat food crops, and calculations were carried out for six example hazards (norovirus, Cryptosporidium, cadmium, lead, PCB118 and naphthalene) and using UK-specific input values. The human health risks associated with using reclaimed water for amenity irrigation were overall deemed low, i.e. the calculated acceptable concentration levels for most of the selected hazards were generally far greater than levels typically measured in effluent from wastewater treatment plants; however the predicted acceptable concentration levels for norovirus and Cryptosporidium suggested that disinfection by UV may be required before use. It was found that stricter concentration standards were required for hazards that are more strongly bound to soil and/or are more toxic/infectious. It was also found that measures that reduce the amount of effluent directly ingested by the receptor would significantly reduce the risks (by up to 2 orders of magnitude for the two pathogens). The results for the food crop irrigation scenario showed that stricter concentration standards are required to ensure the effluent is safe to use. For pathogens, the dominant exposure route was found to be ingestion of effluent captured on the surface of the crops indicating that risks could be significantly reduced by restricting irrigation to the non-edible parts of the crop. The results also showed that the exposure to some organic compounds and heavy metals through plant uptake and attached soil particles could be high and possibly pose unacceptable risk to human health. For both scenarios, we show that the predicted acceptable concentration levels are associated with large uncertainty and discuss the implications this has for defining quality standards and how the uncertainty can be reduced.

Quantification of Salmonella Survival and Infection in an In vitro Model of the Human Intestinal Tract as Proxy for Foodborne Pathogens

Different techniques are available for assessing differences in virulence of bacterial foodborne pathogens. The use of animal models or human volunteers is not expedient for various reasons; the use of epidemiological data is often hampered by lack of crucial data. In this paper, we describe a static, sequential gastrointestinal tract (GIT) model system in which foodborne pathogens are exposed to simulated gastric and intestinal contents of the human digestive tract, including the interaction of pathogens with the intestinal epithelium. The system can be employed with any foodborne bacterial pathogens. Five strains of Salmonella Heidelberg and one strain of Salmonella Typhimurium were used to assess the robustness of the system. Four S. Heidelberg strains originated from an outbreak, the fifth S. Heidelberg strain and the S. Typhimurium strain originated from routine meat inspections. Data from plate counts, collected for determining the numbers of surviving bacteria in each stage, were used to quantify both the experimental uncertainty and biological variability of pathogen survival throughout the system. For this, a hierarchical Bayesian framework using Markov chain Monte Carlo (MCMC) was employed. The model system is able to distinguish serovars/strains for in vitro infectivity when accounting for within strain biological variability and experimental uncertainty.

Cryptosporidium Infection Risk: Results of New Dose-Response Modeling

Cryptosporidium human dose-response data from seven species/isolates are used to investigate six models of varying complexity that estimate infection probability as a function of dose. Previous models attempt to explicitly account for virulence differences among C. parvum isolates, using three or six species/isolates. Four (two new) models assume species/isolate differences are insignificant and three of these (all but exponential) allow for variable human susceptibility. These three human-focused models (fractional Poisson, exponential with immunity and beta-Poisson) are relatively simple yet fit the data significantly better than the more complex isolate-focused models. Among these three, the one-parameter fractional Poisson model is the simplest but assumes that all Cryptosporidium oocysts used in the studies were capable of initiating infection. The exponential with immunity model does not require such an assumption and includes the fractional Poisson as a special case. The fractional Poisson model is an upper bound of the exponential with immunity model and applies when all oocysts are capable of initiating infection. The beta Poisson model does not allow an immune human subpopulation; thus infection probability approaches 100% as dose becomes huge. All three of these models predict significantly (>10x) greater risk at the low doses that consumers might receive if exposed through drinking water or other environmental exposure (e.g., 72% vs. 4% infection probability for a one oocyst dose) than previously predicted. This new insight into Cryptosporidium risk suggests additional inactivation and removal via treatment may be needed to meet any specified risk target, such as a suggested 10^-4 annual risk of Cryptosporidium infection.

Application of disease burden to quantitative assessment of health hazards for a decentralized water reuse system

The aim of this article is to introduce the methodology of disease burden (DB) to quantify the health impact of microbial regrowth during wastewater reuse, using the case study of a decentralized water reuse system in Xi'an Si-yuan University, located in Xi'an, China. Based on field investigation findings, Escherichia coli (E. coli), Salmonella and rotavirus were selected as typical regrowth pathogens causing potential health hazards during the reuse of reclaimed water. Subsequently, major exposure routes including sprinkler irrigation, landscape fountains and toilet flushing were identified. Mathematical models were established to build the relationship between exposure dose and disease burden by calculating the disability adjusted life year (DALY). Results of disease burden for this case study show that DALYs attributed to E. coli were significantly greater than those caused by other pathogens, and DALYs associated with sprinkler irrigation were higher than those originating from other routes. A correlation between exposure dose and disease was obtained by introducing a modified calculation of morbidity, which can extend the assessment endpoint of health risk to disease burden from the conventional infection rate.

QMRA for Drinking Water: 1. Revisiting the Mathematical Structure of Single-Hit Dose-Response Models

Dose-response models are essential to quantitative microbial risk assessment (QMRA), providing a link between levels of human exposure to pathogens and the probability of negative health outcomes. In drinking water studies, the class of semi-mechanistic models known as single-hit models, such as the exponential and the exact beta-Poisson, has seen widespread use. In this work, an attempt is made to carefully develop the general mathematical single-hit framework while explicitly accounting for variation in (1) host susceptibility and (2) pathogen infectivity. This allows a precise interpretation of the so-called single-hit probability and precise identification of a set of statistical independence assumptions that are sufficient to arrive at single-hit models. Further analysis of the model framework is facilitated by formulating the single-hit models compactly using probability generating and moment generating functions. Among the more practically relevant conclusions drawn are: (1) for any dose distribution, variation in host susceptibility always reduces the single-hit risk compared to a constant host susceptibility (assuming equal mean susceptibilities), (2) the model-consistent representation of complete host immunity is formally demonstrated to be a simple scaling of the response, (3) the model-consistent expression for the total risk from repeated exposures deviates (gives lower risk) from the conventional expression used in applications, and (4) a model-consistent expression for the mean per-exposure dose that produces the correct total risk from repeated exposures is developed.

Modelling microbial health risk of wastewater reuse: A systems perspective

There is a widespread need for the use of quantitative microbial risk assessment (QMRA) to determine reclaimed water quality for specific uses, however neither faecal indicator levels nor pathogen concentrations alone are adequate for assessing exposure health risk. The aim of this study was to build a conceptual model representing factors contributing to the microbiological health risks of reusing water treated in maturation ponds. This paper describes the development of an unparameterised model that provides a visual representation of theoretical constructs and variables of interest. Information was collected from the peer-reviewed literature and through consultation with experts from regulatory authorities and academic disciplines. In this paper we explore how, considering microbial risk as a modular system, following the QMRA framework enables incorporation of the many factors influencing human exposure and dose response, to better characterise likely human health impacts. By using and expanding upon the QMRA framework we deliver new insights into this important field of environmental exposures. We present a conceptual model of health risk of microbial exposure which can be used for maturation ponds and, more importantly, as a generic tool to assess health risk in diverse wastewater reuse scenarios.

Microbial dose response modeling: past, present, and future

The understanding of the risk to humans from exposure to pathogens has been firmly put into a risk assessment framework. A key element of applying this approach is the understanding of the relationship between dose and response for particular pathogens. This understanding has progressed from early use of threshold concepts ("minimal infectious dose") thru multiple generations of models. Generation 1 models describe probability of response to exposed dose. Generation 2 models incorporate host factors (e.g., age) and/or pathogen factors (e.g., particle size of inhaled agents). Generation 3 models describe the rate at which effects develop, i.e. the epidemic curve. These (generation 1 through three models) have been developed and used in multiple contexts. Beyond Generation 3 lies an opportunity for the deep incorporation of in vivo physiological responses and the coupling of the individual host dynamics to the dynamics of spread of contagious diseases in the population. This would enable more direct extrapolation from controlled dosing studies to estimate population level effects. There remain also needs to understand broader categories of infectious agents, including pathogenic amoebae and fungi. More advanced models need to be validated against well-characterized human outbreak data.

Considering the risk of infection by cryptosporidium via consumption of municipally treated drinking water from a surface water source in a Southwestern Ontario community

Through the use of case-control analyses and quantitative microbial risk assessment (QMRA), relative risks of transmission of cryptosporidiosis have been evaluated (recreational water exposure vs. drinking water consumption) for a Canadian community with higher than national rates of cryptosporidiosis. A QMRA was developed to assess the risk of Cryptosporidium infection through the consumption of municipally treated drinking water. Simulations were based on site-specific surface water contamination levels and drinking water treatment log₁₀ reduction capacity for Cryptosporidium. Results suggested that the risk of Cryptosporidium infection via drinking water in the study community, assuming routine operation of the water treatment plant, was negligible (6 infections per 10¹³ persons per day--5th percentile: 2 infections per 10¹⁵ persons per day; 95th percentile: 3 infections per 10¹² persons per day). The risk is essentially nonexistent during optimized, routine treatment operations. The study community achieves between 7 and 9 log₁₀ Cryptosporidium oocyst reduction through routine water treatment processes. Although these results do not preclude the need for constant vigilance by both water treatment and public health professionals in this community, they suggest that the cause of higher rates of cryptosporidiosis are more likely due to recreational water contact, or perhaps direct animal contact. QMRA can be successfully applied at the community level to identify data gaps, rank relative public health risks, and forecast future risk scenarios. It is most useful when performed in a collaborative way with local stakeholders, from beginning to end of the risk analysis paradigm.

QMRAspot: a tool for Quantitative Microbial Risk Assessment from surface water to potable water

In the Netherlands, a health based target for microbially safe drinking water is set at less than one infection per 10,000 persons per year. For the assessment of the microbial safety of drinking water, Dutch drinking water suppliers must conduct a Quantitative Microbial Risk Assessment (QMRA) at least every three years for the so-called index pathogens enterovirus, Campylobacter, Cryptosporidium and Giardia. In order to collect raw data in the proper format and to automate the process of QMRA, an interactive user-friendly computational tool, QMRAspot, was developed to analyze and conduct QMRA for drinking water produced from surface water. This paper gives a description of the raw data requirements for QMRA as well as a functional description of the tool. No extensive prior knowledge about QMRA modeling is required by the user, because QMRAspot provides guidance to the user on the quantity, type and format of raw data and performs a complete analysis of the raw data to yield a risk outcome for drinking water consumption that can be compared with other production locations, a legislative standard or an acceptable health based target. The uniform approach promotes proper collection and usage of raw data and, warrants quality of the risk assessment as well as enhances efficiency, i.e., less time is required. QMRAspot may facilitate QMRA for drinking water suppliers worldwide. The tool aids policy makers and other involved parties in formulating mitigation strategies, and prioritization and evaluation of effective preventive measures as integral part of water safety plans.

Quantitative health risk assessment of Cryptosporidium in rivers of southern China based on continuous monitoring

The concentrations of Cryptosporidium in the source water of several cities of Zhejiang Province, China were determined to be in the range of 0-17 oocysts/10 L in the rainy season in 2008, with a mean value of 7 oocysts/10 L. Based on the investigation data, comprehensive risk assessment of Cryptosporidium infection was performed by considering different water intake routes as well as water consumption. Intakes of unboiled tapwater (including drinking and tooth-brushing and food and dish washing) and source water (through swimming in rivers) were estimated to be 2.59-25.9 and 0.32-0.74 L/year-person, respectively. The mortality due to Cryptosporidium infection for people in this region, excluding HIV-infected patients, was calculated as 0-0.0146 per 10(5) persons using a conditional probability formula. Disability-adjusted life years (DALYs) were used to quantify the risk of Cryptosporidium infection, for which uncertainty was analyzed. For people who consumed conventionally treated water, the DALYs due to Cryptosporidium infection were 6.51 per 10(5) (95% CI: 2.16 × 10(-5)-22.35 × 10(-5)) persons, which were higher than a risk judged acceptable by some (1.97 × 10(-5) DALYs per year), and the risk for those consuming ozone-treated water became 0.0689 × 10(-5) DALYs per year. The major risk of infection resulted from swimming in the river. This study provides a method to establish the risk of Cryptosporidium infection and optimize the scheme for reducing the risk effectively, which is useful for the modification of water quality standards based on cost utility analysis given use of DALYs.

The European rabbit (Oryctolagus cuniculus), a source of zoonotic cryptosporidiosis

Cryptosporidium spp. have been found in the faeces of over 150 mammalian host species, but the risks to public health from wildlife are poorly understood. In summer 2008, the Cryptosporidium sp. rabbit genotype was identified as the aetiological agent in an outbreak of waterborne human cryptosporidiosis. The source was a wild rabbit that had entered a treated water tank. To establish current knowledge about Cryptosporidium spp. infecting lagomorphs, especially the host range and biological characteristics of the rabbit genotype, and the potential risks to public health that rabbits may pose in the transmission of zoonotic cryptosporidiosis, we undertook a literature and data review. The literature returned demonstrates that although the European rabbit (Oryctolagus cuniculus) has been the most widely studied lagomorph, few large scale studies were found. The prevalence of Cryptosporidium spp. in wild rabbit populations in the two large scale studies was 0.9% (95%CI 0.2-5.0) and 0.0% (95%CI 0.0-1.6). Neither study provided age nor sex profiles nor typing of Cryptosporidium isolates. The infecting Cryptosporidium species was confirmed in just four other studies of rabbits, all of which showed the rabbit genotype. Human-infectious Cryptosporidium species including Cryptosporidium parvum have caused experimental infections in rabbits and it is likely that this may also occur naturally. No published studies of the host range and biological features of the Cryptosporidium rabbit genotype were identified, but information was generated on the identification and differentiation of the rabbit genotype at various genetic loci. Both pet and wild rabbits are a potential source of human cryptosporidiosis and as such, good hygiene practices are recommended during and after handling rabbits or exposure to their faeces, or potentially contaminated surfaces. Water supplies should be protected against access by wildlife, including rabbits.

Quantitative microbial risk assessment of cryptosporidiosis and giardiasis from very small private water supplies

This article reports a quantitative microbial risk assessment of the risk of Giardia and Cryptosporidium in very small private water supplies. Both pathogens have been implicated in causing outbreaks of waterborne disease associated with such supplies, though the risk of endemic disease is not known. For exposure assessments, we used existing data to derive regression equations describing the relationships between the concentration of these pathogens and Escherichia coli in private water supplies. Pathogen concentrations were then estimated using national surveillance data of E. coli in private water supplies in England and France. The estimated risk of infection was very high with the median annual risk being of the order of 25-28% for Cryptosporidium and 0.4% to 0.7% for Giardia, though, in the poorer quality supplies the risk could be much higher. These risks are substantially greater than for public water supplies and well above the risk considered tolerable. The observation that observed infection rates are generally much lower may indicate increased immunity in people regularly consuming water from private supplies. However, this increased immunity is presumed to derive from increased disease risk in young children, the group most at risk from severe disease.

A risk assessment model to evaluate the role of fecal contamination in recreational water on the incidence of cryptosporidiosis at the community level in Ontario

A quantitative microbial risk assessment model was developed to simulate the role of recreational water contact in the transmission of cryptosporidiosis in a model Ontario community. Stochastic simulations were based on plausible modes of contamination of a pool (literature derived), river (site-specific), and recreational lakes (literature derived). The highest estimated risks of infection were derived from the (highly contaminated) recreational lake scenario, considered the upper end for risk of infection for both children (10 infections per 1,000 swims [5 per thousand: two infections per 1,000 swims; 95 per thousand: three infections per 100 swims]) and adults (four infections per 1,000 swims [5 per thousand: four infections per 1,000 swims; 95 per thousand: one infection per 100 swims]). Simulating the likely Cryptosporidium oocyst concentration in a lane pool that a child would be exposed to following a diarrheal fecal release event resulted in the third highest mean risk of infection (four infections per 10,000 swims [5 per thousand: three infections per 100,000; 95 per thousand: 10 infections per 10,000 swims]). The findings from this study illustrate the need for systematic and standardized research to quantify Cryptosporidium oocyst levels in Canadian public pools and recreational beaches. There is also a need to capture the swimming practices of the Canadian public, including most common forms and frequency measures. The study findings suggest that swimming in natural swim environments and in pools following a recent fecal contamination event pose significant public health risks. When considering these risks relative to other modes of cryptosporidiosis transmission, they are significant.

Immune defence, parasite evasion strategies and their relevance for 'macroscopic phenomena' such as virulence

The discussion of host-parasite interactions, and of parasite virulence more specifically, has so far, with a few exceptions, not focused much attention on the accumulating evidence that immune evasion by parasites is not only almost universal but also often linked to pathogenesis, i.e. the appearance of virulence. Now, the immune evasion hypothesis offers a deeper insight into the evolution of virulence than previous hypotheses. Sensitivity analysis for parasite fitness and life-history theory shows promise to generate a more general evolutionary theory of virulence by including a major element, immune evasion to prevent parasite clearance from the host. Also, the study of dose-response relationships and multiple infections should be particularly illuminating to understand the evolution of virulence. Taking into account immune evasion brings immunological processes to the core of understanding the evolution of parasite virulence and for a range of related issues such as dose, host specificity or immunopathology. The aim of this review is to highlight the mechanism underlying immune evasion and to discuss possible consequences for the evolutionary ecology analysis of host-parasite interactions.

Hierarchical dose response of E. coli O157:H7 from human outbreaks incorporating heterogeneity in exposure

The infectivity of pathogenic microorganisms is a key factor in the transmission of an infectious disease in a susceptible population. Microbial infectivity is generally estimated from dose-response studies in human volunteers. This can only be done with mildly pathogenic organisms. Here a hierarchical Beta-Poisson dose-response model is developed utilizing data from human outbreaks. On the lowest level each outbreak is modelled separately and these are then combined at a second level to produce a group dose-response relation. The distribution of foodborne pathogens often shows strong heterogeneity and this is incorporated by introducing an additional parameter to the dose-response model, accounting for the degree of overdispersion relative to Poisson distribution. It was found that heterogeneity considerably influences the shape of the dose-response relationship and increases uncertainty in predicted risk. This uncertainty is greater than previously reported surrogate and outbreak models using a single level of analysis. Monte Carlo parameter samples (alpha, beta of the Beta-Poisson model) can be readily incorporated in risk assessment models built using tools such as S-plus and @ Risk.

Predictive Bayesian microbial dose-response assessment based on suggested self-organization in primary illness response: Cryptosporidium parvum

The probability of illness caused by very low doses of pathogens cannot generally be tested due to the numbers of subjects that would be needed, though such assessments of illness dose response are needed to evaluate drinking water standards. A predictive Bayesian dose-response assessment method was proposed previously to assess the unconditional probability of illness from available information and avoid the inconsistencies of confidence-based approaches. However, the method uses knowledge of the conditional dose-response form, and this form is not well established for the illness endpoint. A conditional parametric dose-response function for gastroenteric illness is proposed here based on simple numerical models of self-organized host-pathogen systems and probabilistic arguments. In the models, illnesses terminate when the host evolves by processes of natural selection to a self-organized critical value of wellness. A generalized beta-Poisson illness dose-response form emerges for the population as a whole. Use of this form is demonstrated in a predictive Bayesian dose-response assessment for cryptosporidiosis. Results suggest that a maximum allowable dose of 5.0 x 10(-7) oocysts/exposure (e.g., 2.5 x 10(-7) oocysts/L water) would correspond with the original goals of the U.S. Environmental Protection Agency Surface Water Treatment Rule, considering only primary illnesses resulting from Poisson-distributed pathogen counts. This estimate should be revised to account for non-Poisson distributions of Cryptosporidium parvum in drinking water and total response, considering secondary illness propagation in the population.

ADVANCES IN RISK ASSESSMENT AND COMMUNICATION

Risk analysis continues to evolve. There is increasing depth and breadth to each component of the four-step risk-assessment paradigm of hazard identification, dose-response analysis, exposure assessment, and risk characterization. Basic conceptual approaches to understanding how people perceive risk are being tested against a growing body of empirical observations, many involving stakeholders. Emerging ideas such as the precautionary principle have provided challenges that have led to a rethinking of the role of risk assessment in environmental health. Newer problems, such as intergenerational issues posed by long-lasting radiation pollution, environmental justice, and the assessment and communication of risks related to terrorism, have spurred innovative approaches to risk analysis.

Land application of treated sewage sludge: quantifying pathogen risks from consumption of crops

AIMS

To predict the number of humans in the UK infected through consumption of root crops grown on agricultural land to which treated sewage sludge has been applied in accordance with the current regulations and guidance (Safe Sludge Matrix).

METHODS AND RESULTS

Quantitative risk assessments based on the source, pathway, receptor approach are developed for seven pathogens, namely salmonellas, Listeria monocytogenes, campylobacters, Escherichia coli O157, Cryptosporidium parvum, Giardia, and enteroviruses. Using laboratory data for pathogen destruction by mesophilic anaerobic digestion, and not extrapolating experimental data for pathogen decay in soil to the full 30-month harvest interval specified by the Matrix, predicts 50 Giardia infections per year, but less than one infection per year for the other six pathogens. Assuming linear decay in the soil, a 12-month harvest interval eliminates the risks from all seven pathogens; the highest predicted being one infection of C. parvum in the UK every 45 years. Computer simulations show that a protective effect from binding of pathogens to particulate matter could potentially exaggerate the observed rate of decay in experimental systems.

CONCLUSIONS

The results confirm, assuming pathogens behave according to our current understanding, that the risks to humans from consumption of vegetable crops are remote. Furthermore the harvest intervals stipulated by the Safe Sludge Matrix compensate for potential lapses in the operational efficiency of sludge treatment.

SIGNIFICANCE AND IMPACT OF THE STUDY

The models demonstrate the huge potential impact of decay in the soil over the 12/30-month intervals specified by the Matrix, although lack of knowledge on the exact nature of soil decay processes is a source of uncertainty. The models enable the sensitivity of the predicted risks to changes in the operational efficiency of sewage sludge treatment to be assessed.

Dose response for infection by Escherichia coli O157:H7 from outbreak data

In 1996, an outbreak of E. coli O157:H7-associated illness occurred in an elementary school in Japan. This outbreak has been studied in unusual detail, making this an important case for quantitative risk assessment. The availability of stored samples of the contaminated food allowed reliable estimation of exposure to the pathogens. Collection of fecal samples allowed assessment of the numbers infected, including asymptomatic cases. Comparison to other published dose-response studies for E. coli O157:H7 show that the strain that caused the outbreak studied here must have been considerably more infectious. We use this well-documented incident as an example to demonstrate how such information on the response to a single dose can be used for dose-response assessment. In particular, we demonstrate how the high infectivity limits the uncertainty in the low-dose region.

Cryptosporidiosis susceptibility and risk: a case study

Regional estimates of cryptosporidiosis risks from drinking water exposure were developed and validated, accounting for AIDS status and age. We constructed a model with probability distributions and point estimates representing Cryptosporidium in tap water, tap water consumed per day (exposure characterization); dose response, illness given infection, prolonged illness given illness; and three conditional probabilities describing the likelihood of case detection by active surveillance (health effects characterization). The model predictions were combined with population data to derive expected case numbers and incidence rates per 100,000 population, by age and AIDS status, borough specific and for New York City overall in 2000 (risk characterization). They were compared with same-year surveillance data to evaluate predictive ability, assumed to represent true incidence of waterborne cryptosporidiosis. The predicted mean risks, similar to previously published estimates for this region, overpredicted observed incidence-most extensively when accounting for AIDS status. The results suggest that overprediction may be due to conservative parameters applied to both non-AIDS and AIDS populations, and that biological differences for children need to be incorporated. Interpretations are limited by the unknown accuracy of available surveillance data, in addition to variability and uncertainty of model predictions. The model appears sensitive to geographical differences in AIDS prevalence. The use of surveillance data for validation and model parameters pertinent to susceptibility are discussed.

A quantitative risk assessment of waterborne cryptosporidiosis in France using second-order Monte Carlo simulation

A pragmatic quantitative risk assessment (QRA) of the risks of waterborne Cryptosporidium parvum infection and cryptosporidiosis in immunocompetent and immunodeficient French populations is proposed. The model takes into account French specificities such as the French technique for oocyst enumeration performance and tap water consumption. The proportion of infective oocysts is based on literature review and expert knowledge. The probability of infection for a given number of ingested viable oocysts is modeled using the exponential dose-response model applied on published data from experimental infections in immunocompetent human volunteers challenged with the IOWA strain. Second-order Monte Carlo simulations are used to characterize the uncertainty and variability of the risk estimates. Daily risk of infection and illness for the immunocompetent and the immunodeficient populations are estimated according to the number of oocysts observed in a single storage reservoir water sample. As an example, the mean daily risk of infection in the immunocompetent population is estimated to be 1.08 x 10(-4) (95% confidence interval: [0.20 x 10(-4); 6.83 x 10(-4)]) when five oocysts are observed in a 100 L storage reservoir water sample. Annual risks of infection and disease are estimated from a set of oocyst enumeration results from distributed water samples, assuming a negative binomial distribution of day-to-day contamination variation. The model and various assumptions used in the model are fully explained and discussed. While caveats of this model are well recognized, this pragmatic QRA could represent a useful tool for the French Food Safety Agency (AFSSA) to define recommendations in case of water resource contamination by C. parvum whose infectivity is comparable to the IOWA strain.

Rapid displacement of Cryptosporidium parvum type 1 by type 2 in mixed infections in piglets

Genotypes 1 and 2 of Cryptosporidium parvum are the primary types associated with infections in humans, with type 1 being by far the predominant genotype. The frequency of mixed infection with both genotypes in humans is relatively rare, while type 1, which experimentally infects other mammals, has been found to naturally infect almost exclusively humans. One possible explanation for the absence of type 1 in other mammals and the low frequency of mixed infections in humans is the inability of type 1 to compete with type 2 in nature when both occur simultaneously. To investigate this, we challenged gnotobiotic piglets with equal number of oocysts of type 1 and type 2, given either simultaneously or with type 2 given 24 or 48 h after type 1. The genotype of the oocysts excreted in feces and the relative distribution of each of the genotypes throughout the gut at necropsy were determined. Regardless of the time interval between challenges with the two genotypes, type 2 invariably displaced type 1. The rate of displacement was rapid when both genotypes were given simultaneously, after which no traces of type 1 were detected in the feces or in gut sections by PCR. Infection with type 1 24 or 48 h before challenge with type 2, while permitting type 1 to become established, was still rapidly eliminated within 3 days after challenge with type 2. These observations have major implications regarding the relative perpetuation and survival of these two genotypes in mammals.