A quantitative microbial risk assessment model for Legionnaires' disease: animal model selection and dose-response modeling

Microbial health risks associated with exposure to stormwater in a water plaza

Climate change scenarios predict an increase of intense rainfall events in summer in Western Europe. Current urban drainage systems cannot cope with such intense precipitation events. Cities are constructing stormwater storage facilities to prevent pluvial flooding. Combining storage with other functions, such as recreation, may lead to exposure to contaminants. This study assessed the microbial quality of rainwater collected in a water plaza and the health risks associated with recreational exposure. The water plaza collects street run-off, diverges first flush to the sewer system and stores the rest of the run-off in the plaza as open water. Campylobacter, Cryptosporidium and Legionella pneumophila were the pathogens investigated. Microbial source tracking tools were used to determine the origin (human, animal) of the intestinal pathogens. Cryptosporidium was not found in any sample. Campylobacter was found in all samples, with higher concentrations in samples containing human Bacteroides than in samples with zoonotic contamination (15 vs 3.7 gc (genomic copies)/100 mL). In both cases, the estimated disease risk associated with Campylobacter and recreational exposure was higher than the Dutch national incidence. This indicates that the health risk associated with recreational exposure to the water plaza is significant. L. pneumophila was found only in two out of ten pond samples. Legionnaire's disease risks were lower than the Dutch national incidence. Presence of human Bacteroides indicates possible cross-connections with the CSS that should be identified and removed.

Uncertainties associated with assessing the public health risk from Legionella

Legionella is an opportunistic pathogen of public health concern. Current regulatory and management guidelines for the control of this organism are informed by risk assessments. However, there are many unanswered questions and uncertainties regarding Legionella epidemiology, strain infectivity, infectious dose, and detection methods. This review follows the EnHealth Risk Assessment Framework, to examine the current information available regarding Legionella risk and discuss the uncertainties and assumptions. This review can be used as a tool for understanding the uncertainties associated with Legionella risk assessment. It also serves to highlight the areas of Legionella research that require future focus. Improvement of these uncertainties will provide information to enhance risk management practices for Legionella, potentially improving public health protection and reducing the economic costs by streamlining current management practices.

Evaluating the potential for a Helicobacter pylori drinking water guideline

Helicobacter pylori is a microaerophilic, gram-negative bacterium that is linked to adverse health effects including ulcers and gastrointestinal cancers. The goal of this analysis is to develop the necessary inputs for a quantitative microbial risk assessment (QMRA) needed to develop a potential guideline for drinking water at the point of ingestion (e.g., a maximum contaminant level, or MCL) that would be protective of human health to an acceptable level of risk while considering sources of uncertainty. Using infection and gastric cancer as two discrete endpoints, and calculating dose-response relationships from experimental data on humans and monkeys, we perform both a forward and reverse risk assessment to determine the risk from current reported surface water concentrations of H. pylori and an acceptable concentration of H. pylori at the point of ingestion. This approach represents a synthesis of available information on human exposure to H. pylori via drinking water. A lifetime risk of cancer model suggests that a MCL be set at <1 organism/L given a 5-log removal treatment because we cannot exclude the possibility that current levels of H. pylori in environmental source waters pose a potential public health risk. Research gaps include pathogen occurrence in source and finished water, treatment removal rates, and determination of H. pylori risks from other water sources such as groundwater and recreational water.

Assessment of relative potential for Legionella species or surrogates inhalation exposure from common water uses

The Legionella species have been identified as important waterborne pathogens in terms of disease morbidity and mortality. Microbial exposure assessment is a tool that can be utilized to assess the potential of Legionella species inhalation exposure from common water uses. The screening-level exposure assessment presented in this paper developed emission factors to model aerosolization, quantitatively assessed inhalation exposures of aerosolized Legionella species or Legionella species surrogates while evaluating two generalized levels of assumed water concentrations, and developed a relative ranking of six common in-home uses of water for potential Legionella species inhalation exposure. Considerable variability in the calculated exposure dose was identified between the six identified exposure pathways, with the doses differing by over five orders of magnitude in each of the evaluated exposure scenarios. The assessment of exposure pathways that have been epidemiologically associated with legionellosis transmission (ultrasonic and cool mist humidifiers) produced higher estimated inhalation exposure doses than pathways where epidemiological evidence of transmission has been less strong (faucet and shower) or absent (toilets and therapy pool). With consideration of the large uncertainties inherent in the exposure assessment process used, a relative ranking of exposure pathways from highest to lowest exposure doses was produced using culture-based measurement data and the assumption of constant water concentration across exposure pathways. In this ranking, the ultrasonic and cool mist humidifier exposure pathways were estimated to produce the highest exposure doses, followed by the shower and faucet exposure pathways, and then the toilet and therapy pool exposure pathways.

A análise de risco como ferramenta estratégica para o serviço veterinário oficial brasileiro: dificuldades e desafios

O serviço veterinário oficial é responsável por proteger a saúde pública e animal, assegurando a oferta de produtos de origem animal inócuos aos consumidores. Uma ferramenta que auxilia na busca desses objetivos é a análise de risco, que iniciou a ser utilizada na segunda metade da década de 90 pelos serviços veterinários oficiais dos países. Para a realização de uma análise de risco, qualitativa ou quantitativa, inicialmente deve-se identificar o perigo, a qual na área da saúde animal geralmente é o agente patogênico causador de uma doença. A etapa subsequente é a avaliação do risco, na qual devem ser analisados, com suporte de trabalhos científicos ou especialistas na área, as formas possíveis de introdução, exposição e manutenção do agente patogênico na população susceptível, bem como as consequências, biológicas, econômicas, políticas e sociais trazidas pela enfermidade. A terceira etapa da análise de risco refere-se ao manejo dos riscos, que visa propor medidas que mitiguem o risco verificado até o nível desejado, bem como avaliar o custo/benefício de cada medida. A última fase de uma análise de risco é a comunicação dos riscos. Essa etapa é fundamental para o sucesso do estudo e deve ser iniciada juntamente com a análise de risco em si, sempre deixando aberto um canal permanente de comunicação com todos os atores sociais interessados na análise de risco. A análise de risco tornou-se um importante instrumento utilizado pelos gestores dos serviços veterinários oficiais na tomada de decisões, contribuindo para a escolha de alternativas que confiram, cientificamente, o menor risco sanitário. Este trabalho realizou uma revisão da literatura sobre análise de risco objetivando expor sua definição e processo de elaboração, assim como verificar como ela está sendo utilizada, quais limitações e desafios do uso dessa ferramenta pelo serviço veterinário oficial brasileiro.

Health risk assessment for splash parks that use rainwater as source water

In the Netherlands, rainwater becomes more and more popular as an economic and environmentally sustainable water source for splash parks, however, the associated public health risk and underlying risk factors are unknown. Since splash parks have been associated with outbreaks of infectious diseases, a quantitative microbial risk assessment was performed using Legionella pneumophila as a target pathogen to quantify the risk of infection for exposure due to inhalation and Campylobacter jejuni for ingestion. Data for L. pneumophila and C. jejuni concentrations in rainfall generated surface runoff from streets were extracted from literature. Data for exposure were obtained by observing 604 people at splash parks, of whom 259 were children. Exposure volumes were estimated using data from literature to determine the volume of exposure through inhalation at 0.394 μL/min (95% CI-range 0.0446-1.27 μL/min), hand-to-mouth contact at 22.6 μL/min, (95% CI-range 2.02-81.0 μL/min), ingestion of water droplets at 94.4 μL/min (95% CI-range 5.1-279 μL/min) and ingestion of mouthfuls of water at 21.5·10(3) μL/min (95% CI-range 1.17 ·10(3)-67.0·10(3) μL/min). The corresponding risk of infection for the mean exposure duration of 3.5 min was 9.3·10(-5) (95% CI-range 0-2.4·10(-4)) for inhalation of L. pneumophila and 3.6·10(-2) (95% CI-range 0-5.3·10(-1)) for ingestion of C. jejuni. This study provided a methodology to quantify exposure volumes using observations on site. We estimated that using rainwater as source water for splash parks may pose a health risk, however, further detailed quantitative microbial analysis is required to confirm this finding. Furthermore we give insight into the effect of water quality standards, which may limit infection risks from exposure at splash parks.

Opportunistic pathogens in roof-captured rainwater samples, determined using quantitative PCR

In this study, quantitative PCR (qPCR) was used for the detection of four opportunistic bacterial pathogens in water samples collected from 72 rainwater tanks in Southeast Queensland, Australia. Tank water samples were also tested for fecal indicator bacteria (Escherichia coli and Enterococcus spp.) using culture-based methods. Among the 72 tank water samples tested, 74% and 94% samples contained E. coli and Enterococcus spp., respectively, and the numbers of E. coli and Enterococcus spp. in tank water samples ranged from 0.3 to 3.7 log₁₀ colony forming units (CFU) per 100 mL of water. In all, 29%, 15%, 13%, and 6% of tank water samples contained Aeromonas hydrophila, Staphylococcus aureus, Pseudomonas aeruginosa and Legionella pneumophila, respectively. The genomic units (GU) of opportunistic pathogens in tank water samples ranged from 1.5 to 4.6 log₁₀ GU per 100 mL of water. A significant correlation was found between E. coli and Enterococcus spp. numbers in pooled tank water samples data (Spearman's rs = 0.50; P < 0.001). In contrast, fecal indicator bacteria numbers did not correlate with the presence/absence of opportunistic pathogens tested in this study. Based on the results of this study, it would be prudent, to undertake a Quantitative Microbial Risk Assessment (QMRA) analysis of opportunistic pathogens to determine associated health risks for potable and nonpotable uses of tank water.

Bayesian development of a dose-response model for Aspergillus fumigatus and invasive aspergillosis

Invasive aspergillosis (IA) is a major cause of mortality in immunocompromized hosts, most often consecutive to the inhalation of spores of Aspergillus. However, the relationship between Aspergillus concentration in the air and probability of IA is not quantitatively known. In this study, this relationship was examined in a murine model of IA. Immunosuppressed Balb/c mice were exposed for 60 minutes at day 0 to an aerosol of A. fumigatus spores (Af293 strain). At day 10, IA was assessed in mice by quantitative culture of the lungs and galactomannan dosage. Fifteen separate nebulizations with varying spore concentrations were performed. Rates of IA ranged from 0% to 100% according to spore concentrations. The dose-response relationship between probability of infection and spore exposure was approximated using the exponential model and the more flexible beta-Poisson model. Prior distributions of the parameters of the models were proposed then updated with data in a Bayesian framework. Both models yielded close median dose-responses of the posterior distributions for the main parameter of the model, but with different dispersions, either when the exposure dose was the concentration in the nebulized suspension or was the estimated quantity of spores inhaled by a mouse during the experiment. The median quantity of inhaled spores that infected 50% of mice was estimated at 1.8 × 10(4) and 3.2 × 10(4) viable spores in the exponential and beta-Poisson models, respectively. This study provides dose-response parameters for quantitative assessment of the relationship between airborne exposure to the reference A. fumigatus strain and probability of IA in immunocompromized hosts.

Quantitative risk estimation for a Legionella pneumophila infection due to whirlpool use

Quantitative microbiological risk assessment was used to quantify the risk associated with the exposure to Legionella pneumophila in a whirlpool. Conceptually, air bubbles ascend to the surface, intercepting Legionella from the traversed water. At the surface the bubble bursts into dominantly noninhalable jet drops and inhalable film drops. Assuming that film drops carry half of the intercepted Legionella, a total of four (95% interval: 1-9) and 4.5×10(4) (4.4×10(4) - 4.7×10(4) ) cfu/min were estimated to be aerosolized for concentrations of 1 and 1,000 legionellas per liter, respectively. Using a dose-response model for guinea pigs to represent humans, infection risks for active whirlpool use with 100 cfu/L water for 15 minutes were 0.29 (∼0.11-0.48) for susceptible males and 0.22 (∼0.06-0.42) for susceptible females. A L. pneumophila concentration of ≥1,000 cfu/L water was estimated to nearly always cause an infection (mean: 0.95; 95% interval: 0.9-∼1). Estimated infection risks were time-dependent, ranging from 0.02 (0-0.11) for 1-minute exposures to 0.93 (0.86-0.97) for 2-hour exposures when the L. pneumophila concentration was 100 cfu/L water. Pool water in Dutch bathing establishments should contain <100 cfu Legionella/L water. This study suggests that stricter provisions might be required to assure adequate public health protection.

Assessing the risk of Legionnaires' disease: the inhalation exposure model and the estimated risk in residential bathrooms

Legionella are widely found in the built environment. Patients with Legionnaires' disease have been increasing in Japan; however, health risks from Legionella bacteria in the environment are not appropriately assessed. We performed a quantitative health risk assessment modeled on residential bathrooms in the Adachi outbreak area and estimated risk levels. The estimated risks in the Adachi outbreak approximately corresponded to the risk levels exponentially extrapolated into lower levels on the basis of infection and mortality rates calculated from actual outbreaks, suggesting that the model of Legionnaires' disease in residential bathrooms was adequate to predict disease risk for the evaluated outbreaks. Based on this model, the infection and mortality risk levels per year in 10 CFU/100 ml (100 CFU/L) of the Japanese water quality guideline value were approximately 10(-2) and 10(-5), respectively. However, acceptable risk levels of infection and mortality from Legionnaires' disease should be adjusted to approximately 10(-4) and 10(-7), respectively, per year. Therefore, a reference value of 0.1 CFU/100 ml (1 CFU/L) as a water quality guideline for Legionella bacteria is recommended. This value is occasionally less than the actual detection limit. Legionella levels in water system should be maintained as low as reasonably achievable (<1 CFU/L).

Benchmark dose analysis for Bacillus anthracis inhalation exposures in the nonhuman primate

There is considerable variability in the published lethality values for inhalation exposures of Bacillus anthracis. The lack of consensus on an acceptable dose-response relationship poses a significant challenge in the development of risk-based management approaches for use following a terrorist release of B. anthracis spores. This article reviewed available B. anthracis dose-response modeling and literature for the nonhuman primate, evaluated the use of the U.S. Environmental Protection Agency's Benchmark Dose Software (BMDS) to fit mathematical dose-response models to these data, and reported results of the benchmark dose analysis of suitable data sets. The BMDS was found to be a useful tool to evaluate dose-response relationships in microbial data, including that from B. anthracis exposure. An evaluation of the sources of variability identified in the published lethality data and the corresponding BMDS-derived lethality values found that varying levels of physical characterization of the spore product, differing receptor-specific exposure assumptions, choice of dose metrics, and the selected statistical methods all contributed to differences in lethality estimates. Recognition of these contributors to variability could ultimately facilitate agreement on a B. anthracis dose-response relationship through provision of a common description of necessary study considerations for acceptable dose-response data sets.

Dose-response time modelling for highly pathogenic avian influenza A (H5N1) virus infection

Aims:  To develop time‐dependent dose–response models for highly pathogenic avian influenza A (HPAI) of the H5N1 subtype virus.

Methods and Results:  A total of four candidate time‐dependent dose–response models were fitted to four survival data sets for animals (mice or ferrets) exposed to graded doses of HPAI H5N1 virus using the maximum‐likelihood estimation. A beta‐Poisson dose–response model with the N₅₀ parameter modified by an exponential‐inverse‐power time dependency or an exponential dose–response model with the k parameter modified by an exponential‐inverse time dependency provided a statistically adequate fit to the observed survival data.

Conclusions:  We have successfully developed the time‐dependent dose–response models to describe the mortality of animals exposed to an HPAI H5N1 virus. The developed model describes the mortality over time and represents observed experimental responses accurately.

Significance and Impact of the Study:  This is the first study describing time‐dependent dose–response models for HPAI H5N1 virus. The developed models will be a useful tool for estimating the mortality of HPAI H5N1 virus, which may depend on time postexposure, for the preparation of a future influenza pandemic caused by this lethal virus.

Use of risk assessment and likelihood estimation to analyze spatial distribution pattern of respiratory infection cases

Obvious spatial infection patterns are often observed in cases associated with airborne transmissible diseases. Existing quantitative infection risk assessment models analyze the observed cases by assuming a homogeneous infectious particle concentration and ignore the spatial infection pattern, which may cause errors. This study aims at developing an approach to analyze spatial infection patterns associated with infectious respiratory diseases or other airborne transmissible diseases using infection risk assessment and likelihood estimation. Mathematical likelihood, based on binomial probability, was used to formulate the retrospective component with some additional mathematical treatments. Together with an infection risk assessment model that can address spatial heterogeneity, the method can be used to analyze the spatial infection pattern and retrospectively estimate the influencing parameters causing the cases, such as the infectious source strength of the pathogen. A Varicella outbreak was selected to demonstrate the use of the new approach. The infectious source strength estimated by the Wells-Riley concept using the likelihood estimation was compared with the estimation using the existing method. It was found that the maximum likelihood estimation matches the epidemiological observation of the outbreak case much better than the estimation under the assumption of homogeneous infectious particle concentration. Influencing parameters retrospectively estimated using the new approach can be used as input parameters in quantitative infection risk assessment of the disease under other scenarios. The approach developed in this study can also serve as an epidemiological tool in outbreak investigation. Limitations and further developments are also discussed.

The role of exposure reconstruction in occupational human health risk assessment: current methods and a recommended framework

Exposure reconstruction for substances of interest to human health is a process that has been used, with various levels of sophistication, as far back as the 1930s. The importance of robust and high-quality exposure reconstruction has been recognized by many researchers. It has been noted that misclassification of reconstructed exposures is relatively common and can result in potentially significant effects on the conclusions of a human health risk assessment or epidemiology study. In this analysis, a review of the key exposure reconstruction approaches described in over 400 papers in the peer-reviewed literature is presented. These approaches have been critically evaluated and classified according to quantitative, semiquantitative, and qualitative approaches. Our analysis indicates that much can still be done to improve the overall quality and consistency of exposure reconstructions and that a systematic framework would help to standardize the exposure reconstruction process in the future. The seven recommended steps in the exposure reconstruction process include identifying the goals of the reconstruction, organizing and ranking the available data, identifying key data gaps, selecting the best information sources and methodology for the reconstruction, incorporating probabilistic methods into the reconstruction, conducting an uncertainty analysis, and validating the results of the reconstruction. Influential emerging techniques, such as Bayesian data analysis, are highlighted. Important issues that will likely influence the conduct of exposure reconstruction into the future include improving statistical analysis methods, addressing the issue of chemical mixtures, evaluating aggregate exposures, and ensuring transparency with respect to variability and uncertainty in the reconstruction effort.

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.

Review and comparison between the Wells-Riley and dose-response approaches to risk assessment of infectious respiratory diseases

Infection risk assessment is very useful in understanding the transmission dynamics of infectious diseases and in predicting the risk of these diseases to the public. Quantitative infection risk assessment can provide quantitative analysis of disease transmission and the effectiveness of infection control measures. The Wells-Riley model has been extensively used for quantitative infection risk assessment of respiratory infectious diseases in indoor premises. Some newer studies have also proposed the use of dose-response models for such purpose. This study reviews and compares these two approaches to infection risk assessment of respiratory infectious diseases. The Wells-Riley model allows quick assessment and does not require interspecies extrapolation of infectivity. Dose-response models can consider other disease transmission routes in addition to airborne route and can calculate the infectious source strength of an outbreak in terms of the quantity of the pathogen rather than a hypothetical unit. Spatial distribution of airborne pathogens is one of the most important factors in infection risk assessment of respiratory disease. Respiratory deposition of aerosol induces heterogeneous infectivity of intake pathogens and randomness on the intake dose, which are not being well accounted for in current risk models. Some suggestions for further development of the risk assessment models are proposed.

PRACTICAL IMPLICATIONS

This review article summarizes the strengths and limitations of the Wells-Riley and the dose-response models for risk assessment of respiratory diseases. Even with many efforts by various investigators to develop and modify the risk assessment models, some limitations still persist. This review serves as a reference for further development of infection risk assessment models of respiratory diseases. The Wells-Riley model and dose-response model offer specific advantages. Risk assessors can select the approach that is suitable to their particular conditions to perform risk assessment.

Mathematical models for assessing the role of airflow on the risk of airborne infection in hospital wards

Understanding the risk of airborne transmission can provide important information for designing safe healthcare environments with an appropriate level of environmental control for mitigating risks. The most common approach for assessing risk is to use the Wells-Riley equation to relate infectious cases to human and environmental parameters. While it is a simple model that can yield valuable information, the model used as in its original presentation has a number of limitations. This paper reviews recent developments addressing some of the limitations including coupling with epidemic models to evaluate the wider impact of control measures on disease progression, linking with zonal ventilation or computational fluid dynamics simulations to deal with imperfect mixing in real environments and recent work on dose-response modelling to simulate the interaction between pathogens and the host. A stochastic version of the Wells-Riley model is presented that allows consideration of the effects of small populations relevant in healthcare settings and it is demonstrated how this can be linked to a simple zonal ventilation model to simulate the influence of proximity to an infector. The results show how neglecting the stochastic effects present in a real situation could underestimate the risk by 15 per cent or more and that the number and rate of new infections between connected spaces is strongly dependent on the airflow. Results also indicate the potential danger of using fully mixed models for future risk assessments, with quanta values derived from such cases less than half the actual source value.