Disease risk analysis: a tool for primate conservation planning and decision making

Concern about emerging and re-emerging diseases plays an increasing role in conservation and management of both captive and free-ranging nonhuman primates (NHPs). Managers and policy makers must formulate conservation plans in an arena plagued by uncertainty, complexity, emotion, and politics. The risk analysis paradigm provides a framework that brings together scientists and policy experts to make better decisions for both people and animals. Risk analysis is a multidisciplinary, science-based process that provides an organized and logical approach for incorporating scientific information into policy development in the real world. By blending four specific goal-oriented stages-hazard identification, risk assessment, risk management, and risk communication-one can logically assess the probability that an adverse event, such as the introduction of an emerging disease into a na?ve population, will occur. The following is a review of this process as it pertains to NHP conservation and risks associated with infectious diseases.     

Risk assessment: A model for predicting cross-species transmission of simian foamy virus from macaques (M. fascicularis) to humans at a monkey temple in Bali, Indonesia

Contact between humans and nonhuman primates (NHPs) frequently occurs at monkey temples (religious sites that have become associated with free-ranging populations of NHPs) in Asia, creating the potential for NHP-human disease transmission. In March 2003 a multidisciplinary panel of experts participated in a workshop designed to model the risk of NHP-human pathogen transmission. The panel developed a risk assessment model to describe the likelihood of cross-species transmission of simian foamy virus (SFV) from temple macaques (Macaca fascicularis) to visitors at monkey temples. SFV is an enzootic simian retrovirus that has been shown to be transmitted from NHPs to humans. In operationalizing the model field data, laboratory data and expert opinions were used to estimate the likelihood of SFV transmission within this context. This model sets the stage for a discussion about modeling as a risk assessment tool and the kinds of data that are required to accurately predict transmission.     

Factors Associated with Unplanned Dialysis Starts in Patients followed by Nephrologists: A Retropective Cohort Study

The number of patients starting dialysis is increasing world wide. Unplanned dialysis starts (patients urgently starting dialysis in hospital) is associated with increased costs and high morbidity and mortality. Risk factors for starting dialysis urgently in hospital have not been well studied. The primary objective of this study was to identify risk factors for unplanned dialysis starts in patients followed in a multidisciplinary chronic kidney disease (CKD) clinic. We performed a retrospective cohort study of 649 advanced CKD patients followed in a multidisciplinary CKD clinic at a tertiary care hospital from January 01, 2010 to April 30, 2013. Patients were classified as unplanned start (in hospital) or elective start. Multivariable logistic regression was used to identify variables associated with unplanned dialysis initiation. 184 patients (28.4%) initiated dialysis, of which 76 patients (41.3%) initiated dialysis in an unplanned fashion and 108 (58.7%) starting electively. Unplanned start patients were more likely to have diabetes (68.4% versus 51.9%; p = 0.04), CAD (42.1% versus 24.1%; p = 0.02), congestive heart failure (36.8% versus 17.6%; p = 0.01), and were less likely to receive modality education (64.5% vs 89.8%; p < 0.01) or be assessed by a surgeon for access creation (40.8% vesrus78.7% p < 0.01). On multivariable analysis, higher body mass index (OR 1.07, 95% CI 1.02, 1.13), and a history of congestive heart failure (OR 2.41, 95% CI 1.09, 5.41) were independently associated with an unplanned start. Unplanned dialysis initiation is common among advanced CKD patients, even if they are followed in a multidisciplinary chronic kidney disease clinic. Timely education and access creation in patients at risk may lead to lower costs and less morbidity and mortality.     

One Health for fascioliasis control in human endemic areas

Fasciola hepatica and F. gigantica are liver flukes causing fascioliasis, a worldwide zoonotic, complex disease. Human infection/reinfection occurs in endemic areas where preventive chemotherapy is applied, because of fasciolid transmission ensured by livestock and lymnaeid snail vectors. A One Health control action is the best complement to decrease infection risk. The multidisciplinary framework needs to focus on freshwater transmission foci and their environment, lymnaeids, mammal reservoirs, and inhabitant infection, ethnography and housing. Local epidemiological and transmission knowledge furnished by previous field and experimental research offers the baseline for control design. A One Health intervention should be adapted to the endemic area characteristics. Long-term control sustainability may be achieved by prioritizing measures according to impact depending on available funds.     

Risk analysis: an overview

Risk analysis increasingly is considered as an integral part of the environmental management decision-making process. Risk, defined as the probability of occurrence of a particular adverse effect on human health or the environment, should not be confounded with hazard, defined as a source of potential injury independent of occurrence. Risk analysis has to be followed by risk management. Some opponents of risk analysis make the reproach that the science used in risk analysis is immature and consequently that the entire process in laden with hidden value judgments. Attempts to overcome these critics are increasingly based on the use of robust biologic data the final considered values system being efficacy-based, efficiency-based or equity-based. Globalization has brought with it new problems, and there is an urgent need to improve risk analysts; to increase its public acceptability and to establish consensus regarding solutions to global environmental problems. In this context biologic-based models and biomarkers hold, the greatest promise for improving risk assessment. These considerations are illustrated by a few examples, also pertaining to low-dose extrapolation and to the problem of thresholds for carcinogenesis. Future directions for development are evoked.     

A review of occupational health and safety risk assessment approaches based on multi-criteria decision-making methods and their fuzzy versions

Occupational health and safety (OHS) is a multidisciplinary activity working under the tasks of protection of workers and worksites. Risk assessment, as a compulsory process in implementation of OHS, stands out as evaluating the risks arising from the hazards, taking into account the required control measures, and deciding whether or not the risks can be reduced to an acceptable level. The diversity in risk assessment approaches is such that there are many methods for any industry. Multicriteria decision-making (MCDM)-based approaches contribute to risk assessment knowledge with their ability on solving real-world problems with multiple, conflicting, and incommensurate criteria. This article conducts a critical state-of-the-art review of OHS risk assessment studies using MCDM-based approaches. Additionally, it includes fuzzy versions of MCDM approaches applied to OHS risk assessment. A total of 80 papers are classified in eight different application areas. The papers are reviewed by the points of publication trend, published journal, risk parameters/factors, and tools used. This critical review provides an insight for researchers and practitioners on MCDM-based OHS risk assessment approaches in terms of showing current state and potential areas for attempts to be focused in the future.     

Classification method for disease risk mapping based on discrete hidden Markov random fields

Risk mapping in epidemiology enables areas with a low or high risk of disease contamination to be localized and provides a measure of risk differences between these regions. Risk mapping models for pooled data currently used by epidemiologists focus on the estimated risk for each geographical unit. They are based on a Poisson log-linear mixed model with a latent intrinsic continuous hidden Markov random field (HMRF) generally corresponding to a Gaussian autoregressive spatial smoothing. Risk classification, which is necessary to draw clearly delimited risk zones (in which protection measures may be applied), generally must be performed separately. We propose a method for direct classified risk mapping based on a Poisson log-linear mixed model with a latent discrete HMRF. The discrete hidden field (HF) corresponds to the assignment of each spatial unit to a risk class. The risk values attached to the classes are parameters and are estimated. When mapping risk using HMRFs, the conditional distribution of the observed field is modeled with a Poisson rather than a Gaussian distribution as in image segmentation. Moreover, abrupt changes in risk levels are rare in disease maps. The spatial hidden model should favor smoothed out risks, but conventional discrete Markov random fields (e.g. the Potts model) do not impose this. We therefore propose new potential functions for the HF that take into account class ordering. We use a Monte Carlo version of the expectation-maximization algorithm to estimate parameters and determine risk classes. We illustrate the method's behavior on simulated and real data sets. Our method appears particularly well adapted to localize high-risk regions and estimate the corresponding risk levels.     

A simple method to detect and estimate heterogeneity: application to Huntington disease, diabetes, and HIV seroconversion.

The traditional method for calculating risk in prospective and retrospective studies is based on the assumption that the study population is homogeneous. Risk is therefore estimated as an overall average for the entire population, when in fact some individuals may be at high risk and others at little or no risk. This paper introduces an alternate approach to risk estimation. The calculations are equally simple and utilize the same data. Yet, the new approach allows for heterogeneity and can detect it when it exists. The new method was applied to HIV seroconversion data from a follow-up study, age-at-onset distribution for Huntington disease, and age-specific prevalence of insulin-treated diabetes. These analyses were intended to demonstrate both applicability of the method to different types of data and the accuracy of the estimates when compared with the known parameters. The HIV analysis predicted a high-risk subgroup constituting about 17% of the cohort. This estimate closely approximates the actual 16% who reportedly engaged in high-risk activities and had a 15-fold higher seroconversion rate than the rest of the cohort. There is no evidence from genetic linkage studies for heterogeneity in Huntington disease. The present results, however, suggested that 14%-18% of individuals who are susceptible to the disease have a much lower risk than others. Diabetes data was chosen because the model is clearly too simplistic for this disease, and the analysis did reveal lack of fit of the model.     

Reflections on the European Conference "Molecular Screening of Individuals at High Risk for Developing Cancer: Medical, Ethical, Legal, and Social Issues"

The fascinating progress of molecular biology in the last decades has made possible the early identification of persons at risk of developing malignant neoplasms, such as thyroid, colon, and breast cancer. This has changed conventional medical practice and has raised a number of ethical questions. Despite the fact that there has been substantial development throughout the Western countries in legislation dealing with medical information, there is an acute need for further exploration and assessment of the moral and social dimensions of medical practices to achieve more precise and uniform regulations. These topics were discussed in a multidisciplinary European Conference entitled "Molecular Screening of Individuals at High Risk of Developing Cancer: Medical, Ethical, Legal, and Social Issues," which took place in March, 1999, in Athens, Greece.     

Contribution of Company Affiliation and Social Contacts to Risk Estimates of Between-Farm Transmission of Avian Influenza

Background

Models of between-farm transmission of pathogens have identified service vehicles and social groups as risk factors mediating the spread of infection. Because of high levels of economic organization in much of the poultry industry, we examined the importance of company affiliation, as distinct from social contacts, in a model of the potential spread of avian influenza among broiler poultry farms in a poultry-dense region in the United States. The contribution of company affiliation to risk of between-farm disease transmission has not been previously studied.

Methodology/Principal Findings

We obtained data on the nature and frequency of business and social contacts through a national survey of broiler poultry growers in the United States. Daily rates of contact were estimated using Monte Carlo analysis. Stochastic modeling techniques were used to estimate the exposure risk posed by a single infectious farm to other farms in the region and relative risk of exposure for farms under different scenarios. The mean daily rate of vehicular contact was 0.82 vehicles/day. The magnitude of exposure risk ranged from <1% to 25% under varying parameters. Risk of between-farm transmission was largely driven by company affiliation, with farms in the same company group as the index farm facing as much as a 5-fold increase in risk compared to farms contracted with different companies. Employment of part-time workers contributed to significant increases in risk in most scenarios, notably for farms who hired day-laborers. Social visits were significantly less important in determining risk.

Conclusions/Significance

Biosecurity interventions should be based on information on industry structure and company affiliation, and include part-time workers as potentially unrecognized sources of viral transmission. Modeling efforts to understand pathogen transmission in the context of industrial food animal production should consider company affiliation in addition to geospatial factors and pathogen characteristics. Restriction of social contacts among farmers may be less useful in reducing between-farm transmission.     

Software Review of Risk*Assistant (Version 1.1) and RiskEZ (Version 1), both for Windows

RiskEZ and Risk*Assistant both make site risk assessment more accessible to many users and provide a relatively efficient means for performing screening level risk assessments. The programs perform basic site risk assessment calcu lations for users and provide point estimates of incremental individual cancer risks and non cancer hazard quotients following standard Environmental Pro tection Agency risk assessment guidance documents. Risk*Assistant allows the user to input raw data from which it can perform some dispersion modeling and calculate exposure point concentrations, while RiskEZ takes the exposure point concentrations as inputs. RiskEZ includes features that allow multiple network users to work on the same site and to deal with radioactive contami nants as well as chemical ones, while Risk*Assistant limits access to a site to one user at a time and it includes non radioactive substances. Neither program currently has the capability to perform probabilistic risk analyses, although Risk*Assistant allows the user to peform some sensitivity analysis. This review highlights differences between the programs and demonstrates how selection of a particular program might influence the results.     

Evaluation of the effectiveness of the California mosquito-borne virus surveillance & response plan, 2009–2018

Local vector control and public health agencies in California use the California Mosquito-Borne Virus Surveillance and Response Plan to monitor and evaluate West Nile virus (WNV) activity and guide responses to reduce the burden of WNV disease. All available data from environmental surveillance, such as the abundance and WNV infection rates in Culex tarsalis and the Culex pipiens complex mosquitoes, the numbers of dead birds, seroconversions in sentinel chickens, and ambient air temperatures, are fed into a formula to estimate the risk level and associated risk of human infections. In many other areas of the US, the vector index, based only on vector mosquito abundance and infection rates, is used by vector control programs to estimate the risk of human WNV transmission. We built models to determine the association between risk level and the number of reported symptomatic human disease cases with onset in the following three weeks to identify the essential components of the risk level and to compare California’s risk estimates to vector index. Risk level calculations based on Cx. tarsalis and Cx. pipiens complex levels were significantly associated with increased human risk, particularly when accounting for vector control area and population, and were better predictors than using vector index. Including all potential environmental components created an effective tool to estimate the risk of WNV transmission to humans in California.     

基于多源地理数据精细尺度的武汉市人居环境新型冠状病毒肺炎疫情传播风险评估

新型冠状病毒肺炎的迅速传播和扩散警示着疾病风险评估的重要性。但现有的风险评估方法受数据限制,缺少实时性和准确性。此外,多数研究以行政统计单元作为分析尺度,存在可变面元问题。为解决这些问题,耦合精细尺度下武汉市疫情数据及多源地理数据,基于随机森林算法构建社区尺度的市域疫情传播风险评估模型并进行了疫情风险制图。模型测试精度达到0.85,Kappa系数达到0.70。此外,本研究还建立基于随机森林算法的社区及场所尺度的"空间变量-感染风险"模型,评估了不同场所设施疫情传播的风险程度。研究表明,（1）武汉中心区域感染风险最高并呈现出向外围递减的趋势;（2）感染风险排名前五的一级场所类型分别为购物服务、医疗服务、金融服务、交通设施以及公共设施;（3）小学、中学的疫情传播风险较低,而高等院校传播风险较高;（4）社区尺度下的疫情风险程度,预测购物场所与交通场所是疫情传播风险最高的驱动因子。本研究基于精细尺度提出风险评估新方法,可为未来疾病风险评估提供新思路,为疫情防控提供决策支持,人民群众提供安全保障。     

Heritability and segregation analysis of osteosarcoma in the Scottish deerhound

Osteosarcoma is the most common malignant bone tumor in dogs and, like its human orthologue, is characterized by aggressive local behavior and high metastatic rates. The Scottish deerhound is a breed of dog with a >15% incidence of osteosarcoma and represents an excellent spontaneously occurring large-animal model of the human disease. We modeled the transmission of the osteosarcoma phenotype in a population of over 1000 related deerhounds ascertained as part of a prospective health study. Variance component analysis, segregation analysis, and linear modeling were performed to evaluate heritability, to infer the presumptive transmission model, and to identify covariate effects for this phenotype within the breed, respectively. Based on variance component analysis, heritability (h2) was estimated to be 0.69. Six transmission models were analyzed by segregation analysis; based on Akaike's information criteria, the most parsimonious model was the Mendelian major gene model with dominant expression. Linear modeling identified gender and genotype as significant predictors of disease outcome. Importantly, duration of gonadal hormone exposure, weight, and height at maturity were not significant predictors of outcome. Inheritance of the putative high-risk allele was thus associated with >75% risk of disease occurrence compared to the <5% baseline risk. These results support the hypothesis that a major gene with a dominant effect explains most of the osteosarcoma phenotype within the Scottish deerhound.     

Is There an Association between Dryland Salinity and Ross River Virus Disease in Southwestern Australia?

Land use change has the potential to cause severe ecosystem degradation and drive changes in disease transmission and emergence. Broadscale clearing of native vegetation for agriculture in southwestern Australia has resulted in severe ecosystem degradation, which has been compounded by the subsequent development of large areas of dryland salinity. The mosquito-borne disease, Ross River virus (RRV), has been noted as a potential adverse human health outcome in these salinity affected regions. The association between dryland salinity and RRV disease was therefore tested by undertaking a spatial analysis of disease notification records using standard and Bayesian techniques. To overcome inherent limitations with notification data, serological RRV antibody prevalence was also investigated. Neither method revealed a significant association with dryland salinity, however, the spatial scale imposed limited the sensitivity of both studies. Thus, further multidisciplinary studies are required to overcome these limitations and advance understanding of this ecosystem health issue, particularly using variables that can be investigated on a finer scale.     

Risk factors for uterine fibroids: reduced risk associated with oral contraceptives.

Risk factors for pathologically confirmed uterine leiomyomas (fibroids) were investigated using data from the Oxford Family Planning Association study, a long term follow up study of women using various methods of contraception. For each of 535 women who had had a fibroid an individual control was selected who matched the patient on age, date of entry into the cohort, and family planning clinic at recruitment and who was alive (and still being followed up) at the date the patient underwent surgery for fibroids. Case-control analysis showed that reproductive experiences were closely linked to development of fibroids. Risk of fibroids decreased consistently with increasing number of term pregnancies; women with five term pregnancies had only a quarter of the risk of women who had had none. Risk also decreased consistently with increasing duration of oral contraceptive use; the risk of fibroids was reduced by some 31% in women who had used oral contraceptives for 10 years. Risk was strongly related to weight: women who weighed under 55 kg had a particularly low risk, and overall the risk rose roughly 21% for each 10 kg increase. Cigarette smoking was associated with a decreased risk of fibroids; smokers of 20 cigarettes a day had a risk roughly two thirds that of non-smokers. These risk factors have all previously been identified as risk factors for endometrial cancer; this strongly suggests that the underlying risk factor is "unopposed" oestrogen.     

Application of a risk analysis method to different technologies for producing a monoclonal antibody employed in hepatitis B vaccine manufacturing

CB.Hep-1 monoclonal antibody (mAb) is used for a recombinant Hepatitis B vaccine manufacturing, which is included in a worldwide vaccination program against Hepatitis B disease. The use of this mAb as immunoligand has been addressed into one of the most efficient steps of active pharmaceutical ingredient purification process. Regarding this, Quality Risk Management (QRM) provides an excellent framework for the risk management use in pharmaceutical manufacturing and quality decision-making applications. Consequently, this study sought applying a prospective risk analysis methodology Failure Mode Effects Analysis (FMEA) as QRM tool for analyzing different CB.Hep-1 mAb manufacturing technologies. As main conclusions FMEA was successfully used to assess risks associated with potential problems in CB.Hep-1 mAb manufacturing processes. The severity and occurrence of risks analysis evidenced that the percentage of very high severe risks ranged 31.0-38.7% of all risks and the huge majority of risks have a very low occurrence level (61.9-83.3%) in all assessed technologies. Finally, additive Risk Priority Number, was descending ordered as follow: transgenic plants (2636), ascites (2577), transgenic animals (2046) and hollow fiber bioreactors (1654), which also corroborated that in vitro technology, should be the technology of choice for CB.Hep-1 mAb manufacturing in terms of risks and mAb molecule quality.     

Geographical Information Systems risk assessment models for zoonotic fascioliasis in the South American Andes region

The WHO recognises Fasciola hepatica to be an important human health problem. The Andean countries of Peru, Bolivia and Chile are those most severely affected by this distomatosis, though areas of Ecuador, Colombia and Venezuela are also affected. As part of a multidisciplinary project, we present results of use of a Geographical Information Systems (GIS) forecast model to conduct an epidemiological analysis of human and animal fasciolosis in the central part of the Andes mountains. The GIS approach enabled us to develop a spatial and temporal epidemiological model to map the disease in the areas studied and to classify transmission risk into low, moderate and high risk areas so that areas requiring the implementation of control activities can be identified. Current results are available on a local scale for: (1) the northern Bolivian Altiplano, (2) Puno in the Peruvian Altiplano, (3) the Cajamarca and Mantaro Peruvian valleys, and (4) the Ecuadorian provinces of Azuay, Cotopaxi and Imbabura. Analysis of results demonstrated the validity of a forecast model that combines use of climatic data to calculate of forecast indices with remote sensing data, through the classification of Normalized Difference Vegetation Index (NDVI) maps.     

Ecological Risk Assessment for Terrestrial Ecosystems: The Summary of Discussions and Recommendations from the Adelaide Workshop (April 2004)

The Ecological Risk Assessment (ERA) workshop focused on the anthropogenic contaminants in the terrestrial environment, addressing various components of the ERA process. These included sources, exposure pathways, bioavailability, and toxicity to receptor organisms as well as risk communication. It was concluded that although the overseas experience on ERA for terrestrial ecosystems (e.g., International Standards or guidelines from the European Union and the United States) is very useful, it is not directly applicable to Australia due to the differences in receptor organisms, contaminants, soil, and environmental conditions. Workshop discussions stressed on the need for making ERA locally relevant (in terms of choice of receptor organisms, sampling strategy, and bioavailability considerations). The workshop discussions highlighted the need of better appreciation of both the similarities and the clear differences between aquatic and terrestrial ERAs. The availability of reliable data, problems with databases, estimation of bioavailability, and extrapolations from laboratory to field were noted among the key limitations. ERA—being inherently complex and involving a range of environmental compartments, target receptor, and exposure pathways—at a minimum requires a multidisciplinary approach to address the complexities. Bringing a multidisciplinary team together often proves a major challenge in ERA. The delegates called for continued efforts in this area and formation of a network or working group in Australia.     

Unmanned Aircraft Systems for Studying Spatial Abundance of Ungulates: Relevance to Spatial Epidemiology

Complex ecological and epidemiological systems require multidisciplinary and innovative research. Low cost unmanned aircraft systems (UAS) can provide information on the spatial pattern of hosts’ distribution and abundance, which is crucial as regards modelling the determinants of disease transmission and persistence on a fine spatial scale. In this context we have studied the spatial epidemiology of tuberculosis (TB) in the ungulate community of Doñana National Park (South-western Spain) by modelling species host (red deer, fallow deer and cattle) abundance at fine spatial scale. The use of UAS high-resolution images has allowed us to collect data to model the environmental determinants of host abundance, and in a further step to evaluate their relationships with the spatial risk of TB throughout the ungulate community. We discuss the ecological, epidemiological and logistic conditions under which UAS may contribute to study the wildlife/livestock sanitary interface, where the spatial aggregation of hosts becomes crucial. These findings are relevant for planning and implementing research, fundamentally when managing disease in multi-host systems, and focusing on risky areas. Therefore, managers should prioritize the implementation of control strategies to reduce disease of conservation, economic and social relevance.