Quantifying Water Pathogen Risk in an Epidemiological Framework

Traditionally, microbial risk assessors have used point estimates to evaluate the probability that an individual will become infected. We developed a quantitative approach that shifts the risk characterization perspective from point estimate to distributional estimate, and from individual to population. To this end, we first designed and implemented a dynamic model that tracks traditional epidemiological variables such as the number of susceptible, infected, diseased, and immune, and environmental variables such as pathogen density. Second, we used a simulation methodology that explicitly acknowledges the uncertainty and variability associated with the data. Specifically, the approach consists of assigning probability distributions to each parameter, sampling from these distributions for Monte Carlo simulations, and using a binary classification to assess the output of each simulation. A case study is presented that explores the uncertainties in assessing the risk of giardiasis when swimming in a recreational impoundment using reclaimed water. Using literature-based information to assign parameters ranges, our analysis demonstrated that the parameter describing the shedding of pathogens by infected swimmers was the factor that contributed most to the uncertainty in risk. The importance of other parameters was dependent on reducing the a priori range of this shedding parameter. By constraining the shedding parameter to its lower subrange, treatment efficiency was the parameter most important in predicting whether a simulation resulted in prevalences above or below non outbreak levels. Whereas parameters associated with human exposure were important when the shedding parameter was constrained to a higher subrange. This Monte Carlo simulation technique identified conditions in which outbreaks and/or nonoutbreaks are likely and identified the parameters that most contributed to the uncertainty associated with a risk prediction.     

Burnout and work organization in hospital wards: A cross-validation study

The relationship between nurses' work organization in hospital wards and the level of burnout experienced by them was analysed in two independent and highly comparable samples of nurses. The hypothesis that the greater the number of nurses who are responsible for, or are having contact with, one patient during one work shift, the higher their experienced level of burnout will be, was partially confirmed in one of the two samples. We have attributed the contradictory results to differences in the management of nurses' work organization, and warned against fashionable ideas concerning the ideal type of nurses' work organization in hospital wards.     

基于“蚂蚁金服”事件网评文本的互联网金融监管蕴意挖掘

以“蚂蚁金服”事件网络评论为样本,借鉴生命周期理论划分评论发展阶段,运用词云图与语义网络进行文本特征可视化和关联分析,并基于LDA模型和语义情感分析考察各阶段评论主题演进趋势和特征,从而挖掘事件的互联网金融监管蕴意。研究表明:相关评论主题在不同阶段各有侧重,但总体呈现逐步细化、深入的特征;“平台垄断”“数据保护”主题最为突出;监管参与者范围扩大成为主要关注点;爆发和平息阶段的评论感情倾向变化较大。为此,互联网金融监管应注重平台防垄断、用户数据保护及多主体协同监管,重点关注爆发与平息阶段的互联网金融舆情引导。     

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.     

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.     

Incorporating Time‐Dose‐Response into Legionella Outbreak Models

A novel method was used to incorporate in vivo host–pathogen dynamics into a new robust outbreak model for legionellosis. Dose‐response and time‐dose‐response (TDR) models were generated for Legionella longbeachae exposure to mice via the intratracheal route using a maximum likelihood estimation approach. The best‐fit TDR model was then incorporated into two L. pneumophila outbreak models: an outbreak that occurred at a spa in Japan, and one that occurred in a Melbourne aquarium. The best‐fit TDR from the murine dosing study was the beta‐Poisson with exponential‐reciprocal dependency model, which had a minimized deviance of 32.9. This model was tested against other incubation distributions in the Japan outbreak, and performed consistently well, with reported deviances ranging from 32 to 35. In the case of the Melbourne outbreak, the exponential model with exponential dependency was tested against non‐time‐dependent distributions to explore the performance of the time‐dependent model with the lowest number of parameters. This model reported low minimized deviances around 8 for the Weibull, gamma, and lognormal exposure distribution cases. This work shows that the incorporation of a time factor into outbreak distributions provides models with acceptable fits that can provide insight into the in vivo dynamics of the host‐pathogen system.     

A Risk Analysis Approach to Prioritizing Epidemics: Ebola Virus Disease in West Africa as a Case Study

The 2014 Ebola virus disease (EVD) outbreak affected several countries worldwide, including six West African countries. It was the largest Ebola epidemic in the history and the first to affect multiple countries simultaneously. Significant national and international delay in response to the epidemic resulted in 28,652 cases and 11,325 deaths. The aim of this study was to develop a risk analysis framework to prioritize rapid response for situations of high risk. Based on findings from the literature, sociodemographic features of the affected countries, and documented epidemic data, a risk scoring framework using 18 criteria was developed. The framework includes measures of socioeconomics, health systems, geographical factors, cultural beliefs, and traditional practices. The three worst affected West African countries (Guinea, Sierra Leone, and Liberia) had the highest risk scores. The scores were much lower in developed countries that experienced Ebola compared to West African countries. A more complex risk analysis framework using 18 measures was compared with a simpler one with 10 measures, and both predicted risk equally well. A simple risk scoring system can incorporate measures of hazard and impact that may otherwise be neglected in prioritizing outbreak response. This framework can be used by public health personnel as a tool to prioritize outbreak investigation and flag outbreaks with potentially catastrophic outcomes for urgent response. Such a tool could mitigate costly delays in epidemic response.     

Exposure to Chlorination By-Products from Hot Water Uses

Exposures to chlorination by-products (CBP) within public water supplies are multiroute in water. Cold water is primarily used for ingestion while a mixture of cold water and hot water is used for showering, bathing others, dish washing, etc. These latter two activities result in inhalation and dermal exposure. Heating water was observed to change the concentration of various CBP. An increase in the trihalomethanes (THM) concentrations and a decrease in the haloacetonitriles and halopropanones concentration, though an initial rise in the concentration of dichloropropanone, were observed. The extent of the increase in the THM is dependent on the chlorine residual present. Therefore, estimates of total exposure to CBP from public water supplies need to consider any changes in their concentration with different water uses. The overall THM exposures calculated using the THM concentration in heated water were 50% higher than those calculated using the THM concentration present in cold water. The estimated lifetime cancer risk associated with exposure to THM in water during the shower is therefore underestimated by 50% if the concentration of THM in cold water is used in the risk assessment.     

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.     

An Integrated Risk Model of a Drinking-Water – Borne Cryptosporidiosis Outbreak

A dynamic risk model is developed to track the occurrence and evolution of a drinking-water–borne cryptosporidiosis outbreak. The model characterizes and integrates the various environmental, medical, institutional, and behavioral factors that determine outbreak development and outcome. These include contaminant delivery and detection, water treatment efficiency, the timing of interventions, and the choices that people make when confronted with a known or suspected risk. The model is used to evaluate the efficacy of alternative strategies for improving risk management during an outbreak, and to identify priorities for improvements in the public health system. Modeling results indicate that the greatest opportunity for curtailing a large outbreak is realized by minimizing delays in identifying and correcting a drinking-water problem. If these delays cannot be reduced, then the effectiveness of risk communication in preemptively reaching and persuading target populations to avoid exposure becomes important.     

An integrated risk model of a drinking-water-borne cryptosporidiosis outbreak.

A dynamic risk model is developed to track the occurrence and evolution of a drinking-water-borne cryptosporidiosis outbreak. The model characterizes and integrates the various environmental, medical, institutional, and behavioral factors that determine outbreak development and outcome. These include contaminant delivery and detection, water treatment efficiency, the timing of interventions, and the choices that people make when confronted with a known or suspected risk. The model is used to evaluate the efficacy of alternative strategies for improving risk management during an outbreak, and to identify priorities for improvements in the public health system. Modeling results indicate that the greatest opportunity for curtailing a large outbreak is realized by minimizing delays in identifying and correcting a drinking-water problem. If these delays cannot be reduced, then the effectiveness of risk communication in preemptively reaching and persuading target populations to avoid exposure becomes important.     

Assessment of Airborne Exposure to Trihalomethanes from Tap Water in Residential Showers and Baths

This study evaluates airborne concentrations of common trihalomethane (THM) compounds in bathrooms during showering and bathing in homes supplied with chlorinated tap water. Three homes in an urban area were selected, each having three bedrooms, a full bath, and approximately 1,000 square feet of living area. THMs were concurrently measured in tap water and air in the shower/bath enclosure and the bathroom vanity area using Summa canisters. Chloroform (TCM), bromodichloromethane (BDCM), and chlorodibromomethane (CDBM) were quantified using U.S. Environmental Protection Agency (EPA) Method TO-14. Air samples were collected prior to, during, and after the water-use event for 16 shower and 7 bath events. Flow rate and temperature were measured, but not controlled. The increase in average airborne concentration (+/- standard error) during showers (expressed as microg/m3 in shower enclosure or bathroom air per microg/L in water) was 3.3+/-0.4 for TCM, 1.8+/-0.3 for BDCM, and 0.5+/-0.1 for CDBM (n = 12), and during baths was 1.2+/-0.4 for TCM, 0.59+/-0.21 for BDCM, and 0.15+/-0.05 for CDBM (n = 4). The relative contribution of each chemical to the airborne concentrations was consistent for all shower and bath events, with apparent release of TCM > BDCM > CDBM. The results are therefore consistent with their relative concentration in tap water and their vapor pressures. When the shower findings for TCM are normalized for water concentration, flow rate, shower volume, and duration, the average exposure concentrations in these urban residences are about 30% lower than those reported by other investigators using EPA analytical methods. This difference is likely attributable primarily to greater air exchange rates in residential shower/bath stalls compared to more "airtight" laboratory shower chambers. This appears to be the first field study to thoroughly evaluate THM exposures from residential showers and baths, and can be used to validate previously published models of tap water volatile chemical transfer to indoor air.     

Risk Characterization of Methyl tertiary Butyl Ether (MTBE) in Tap Water

Methyl tertiary butyl ether (MTBE) can enter surface water and groundwater through wet atmospheric deposition or as a result of fuel leaks and spills. About 30% of the U.S. population lives in areas where MTBE is in regular use. Ninety-five percent of this population is unlikely to be exposed to MTBE in tap water at concentrations exceeding 2 ppb, and most will be exposed to concentrations that are much lower and may be zero. About 5% of this population may be exposed to higher levels of MTBE in tap water, resulting from fuel tank leaks and spills into surface or groundwater used for potable water supplies. This paper describes the concentration ranges found and anticipated in surface and groundwater, and estimates the distribution of doses experienced by humans using water containing MTBE to drink, prepare food, and shower/bathe. The toxic properties (including potency) of MTBE when ingested, inhaled, and in contact with the skin are summarized. Using a range of human toxic potency values derived from animal studies, margins of exposure (MOE) associated with alternative chronic exposure scenarios are estimated to range from 1700 to 140,000. Maximum concentrations of MTBE in tap water anticipated not to cause adverse health effects are determined to range from 700 to 14,000 ppb. The results of this analysis demonstrate that no health risks are likely to be associated with chronic and subchronic human exposures to MTBE in tap water. Although some individuals may be exposed to very high concentrations of MTBE in tap water immediately following a localized spill, these exposures are likely to be brief in duration due to large-scale dilution and rapid volatilization of MTBE, the institution of emergency response and remediation measures to minimize human exposures, and the low taste and odor thresholds of MTBE which ensure that its presence in tap water is readily detected at concentrations well below the threshold for human injury.     

Changing Forest Disturbance Regimes and Risk Perceptions in Homer, Alaska

Forest disturbances caused by insects can lead to other disturbances, risks, and changes across landscapes. Evaluating the human dimensions of such disturbances furthers understanding of integrated changes in natural and social systems. This article examines the effects of changing forest disturbance regimes on local risk perceptions and attitudes in Homer, Alaska. Homer experienced a spruce bark beetle (Dendroctonus rufipennis) outbreak with large-scale tree mortality and a 5,000-acre fire in 2005. Qualitative interviews and quantitative analysis of mail surveys are used to examine community risk perception and relationships with land managers pre- and post-fire. Results show a decrease in the saliency of the spruce bark beetle as a community issue, a coalescence of community risk perceptions about fire, and conflicting findings about satisfaction with land managers and its relationship with risk perception.     

Distribution of Arsenic and Copper in Sediment Pore Water: An Ecological Risk Assessment Case Study for Offshore Drilling Waste Discharges

Due to the hydrophobic nature of synthetic based fluids (SBFs), drilling cuttings are not very dispersive in the water column and settle down close to the disposal site. Arsenic and copper are two important toxic heavy metals, among others, found in the drilling waste. In this article, the concentrations of heavy metals are determined using a steady state "aquivalence-based" fate model in a probabilistic mode. Monte Carlo simulations are employed to determine pore water concentrations. A hypothetical case study is used to determine the water quality impacts for two discharge options: 4% and 10% attached SBFs, which correspond to the best available technology option and the current discharge practice in the U.S. offshore. The exposure concentration ( C_E ) is a predicted environmental concentration, which is adjusted for exposure probability and bioavailable fraction of heavy metals. The response of the ecosystem  ( R_E )  is defined by developing an empirical distribution function of predicted no-effect concentration. The pollutants' pore water concentrations within the radius of 750 m are estimated and cumulative distributions of risk quotient  ( RQ = C_E / R_E )  are developed to determine the probability of RQ greater than 1.     

Application of a Risk Analysis Tool to Middle East Respiratory Syndrome Coronavirus (MERS-CoV) Outbreak in Saudi Arabia

The Grunow–Finke assessment tool (GFT) is an accepted scoring system for determining likelihood of an outbreak being unnatural in origin. Considering its high specificity but low sensitivity, a modified Grunow–Finke tool (mGFT) has been developed with improved sensitivity. The mGFT has been validated against some past disease outbreaks, but it has not been applied to ongoing outbreaks. This study is aimed to score the outbreak of Middle East respiratory syndrome coronavirus (MERS-CoV) in Saudi Arabia using both the original GFT and mGFT. The publicly available data on human cases of MERS-CoV infections reported in Saudi Arabia (2012–2018) were sourced from the FluTrackers, World Health Organization, Saudi Ministry of Health, and published literature associated with MERS outbreaks investigations. The risk assessment of MERS-CoV in Saudi Arabia was analyzed using the original GFT and mGFT criteria, algorithms, and thresholds. The scoring points for each criterion were determined by three researchers to minimize the subjectivity. The results showed 40 points of total possible 54 points using the original GFT (likelihood: 74%), and 40 points of a total possible 60 points (likelihood: 67%) using the mGFT, both tools indicating a high likelihood that human MERS-CoV in Saudi Arabia is unnatural in origin. The findings simply flag unusual patterns in this outbreak, but do not prove unnatural etiology. Proof of bioattacks can only be obtained by law enforcement and intelligence agencies. This study demonstrated the value and flexibility of the mGFT in assessing and predicting the risk for an ongoing outbreak with simple criteria.     

Cross‐Sectional Psychological and Demographic Associations of Zika Knowledge and Conspiracy Beliefs Before and After Local Zika Transmission

Perceptions of infectious diseases are important predictors of whether people engage in disease‐specific preventive behaviors. Having accurate beliefs about a given infectious disease has been found to be a necessary condition for engaging in appropriate preventive behaviors during an infectious disease outbreak, while endorsing conspiracy beliefs can inhibit preventive behaviors. Despite their seemingly opposing natures, knowledge and conspiracy beliefs may share some of the same psychological motivations, including a relationship with perceived risk and self‐efficacy (i.e., control). The 2015–2016 Zika epidemic provided an opportunity to explore this. The current research provides some exploratory tests of this topic derived from two studies with similar measures, but different primary outcomes: one study that included knowledge of Zika as a key outcome and one that included conspiracy beliefs about Zika as a key outcome. Both studies involved cross‐sectional data collections that occurred during the same two periods of the Zika outbreak: one data collection prior to the first cases of local Zika transmission in the United States (March–May 2016) and one just after the first cases of local transmission (July–August). Using ordinal logistic and linear regression analyses of data from two time points in both studies, the authors show an increase in relationship strength between greater perceived risk and self‐efficacy with both increased knowledge and increased conspiracy beliefs after local Zika transmission in the United States. Although these results highlight that similar psychological motivations may lead to Zika knowledge and conspiracy beliefs, there was a divergence in demographic association.     

Evaluating Risk Communication about Fish Consumption Advisories: Efficacy of a Brochure versus a Classroom Lesson in Spanish and English

Presentation format can influence the way target audiences understand risk-related information. Brochures or fish fact sheets are the methods traditionally used by state agencies to inform the public about fish consumption advisories and the risks from consuming fish. This study examines the efficacy of presenting information about the risks from consuming contaminated fish and shellfish in two different formats: a brochure and classroom presentation. The two instruments were developed and tested in Spanish and English, reflecting the local ethnic composition in the Newark Bay Complex. The instruments were tested on women of child-bearing age at the Women, Infants, and Children Center in Elizabeth, New Jersey. Detailed diagrams were used in both presentations, including contaminated fish species, fish preparation methods, and food chain bioaccumulation and transmission to the fetus. There were few language-related differences in the efficacy of the classroom lesson, and the main ideas were understood by both groups. Where there were significant differences in understanding about the risks from consuming fish or crabs from the contaminated waters of Newark Bay, in all cases the women exposed to the classroom lesson had a better understanding than those who read the brochure. Ninety-six percent of the women who heard the lesson understood that it was unsafe to eat fish from the port, compared to 72% of those reading the brochure. Both formats succeeded in imparting information to most women about the area under advisories, the fish species under advisories, and transmission of toxins to the fetus. Information on fish preparation was recalled less clearly, partly because women were asked to relate methods to reduce the risk from consuming fish from 11 presented, and most recalled only two or three of the list. The advantages and disadvantages of conducting short classes to women of child-bearing age are discussed.     

Planning a crude oil supply system through simulation

This paper will describe the planning of a marine terminal that will supply the water borne crude requirements of an oil refinery. The refinery has experienced a major shift in supply from domestic pipeline crudes to foreign water borne crudes delivered by increasingly large tankers. Sufficient tankage does not exist at the refinery to allow proper segregation, handling and fluctuations in inventory levels caused by the size and uncertainty of tanker arrivals. The major steps involved in this analysis included developing and evaluating alternative proposals for new tankage at the terminal and the refinery. For this purpose, a model was built to simulate the proposed marine terminal and crude deliveries to the refinery. This combined discrete/continuous simulation model was then used to determine the optimal proposal for tankage.