Epidemiological study of zoonoses derived from humans in captive chimpanzees

Emerging infectious diseases (EIDs) in wildlife are major threats both to human health and to biodiversity conservation. An estimated 71.8 % of zoonotic EID events are caused by pathogens in wildlife and the incidence of such diseases is increasing significantly in humans. In addition, human diseases are starting to infect wildlife, especially non-human primates. The chimpanzee is an endangered species that is threatened by human activity such as deforestation, poaching, and human disease transmission. Recently, several respiratory disease outbreaks that are suspected of having been transmitted by humans have been reported in wild chimpanzees. Therefore, we need to study zoonotic pathogens that can threaten captive chimpanzees in primate research institutes. Serological surveillance is one of several methods used to reveal infection history. We examined serum from 14 captive chimpanzees in Japanese primate research institutes for antibodies against 62 human pathogens and 1 chimpanzee-borne infectious disease. Antibodies tested positive against 29 pathogens at high or low prevalence in the chimpanzees. These results suggest that the proportions of human-borne infections may reflect the chimpanzee’s history, management system in the institute, or regional epidemics. Furthermore, captive chimpanzees are highly susceptible to human pathogens, and their induced antibodies reveal not only their history of infection, but also the possibility of protection against human pathogens.     

同一健康理念下中国野生动物源疫病监测及响应体系发展对策

现代人类新发传染病中, 有60.3%是人兽共患病, 其中71.8%源于野生动物。野生动物是许多病原体的贮存库, 对人类和饲养动物会产生潜在的生物安全威胁。目前, 中国针对饲养动物疫病的监测检测系统和法律法规较为健全, 但针对野生动物的疫源疫病监测仍比较薄弱。根据“One Health”的理念, 野生动物疫源疫病的有效监测与相应防治措施的落实, 不仅可以为人兽共患病的大规模流行做出预警并降低其几率, 同时也为野生动物种群的健康提供了保障。本研究通过国际案例的比较分析, 提出有效的野生动物疫源疫病监测系统特征。同时, 通过对我国现有监测体系的研究分析, 结合利益相关方访谈以及实地调查, 提出了完善现有系统的主要措施建议。建议包括: (1)推进不同政府部门间的资源互通, 提高国家疫病监测体系应对跨学科、跨领域问题的综合能力; (2)针对人及饲养动物与野生动物接触频繁的生产生活方式, 应建立重点监测管理和响应机制; (3)提高对科学技术的重视, 包括建立野生动物疫病参考实验室、提升相关工作人员的技术能力等, 保障科学的监测方案和检测方法; (4)建立基于公众和现有监测资源的信息上报、汇总系统, 提升野生动物疫病监测的公众参与度和信息透明度。     

Emerging Infectious Diseases in Free-Ranging Wildlife–Australian Zoo Based Wildlife Hospitals Contribute to National Surveillance

Emerging infectious diseases are increasingly originating from wildlife. Many of these diseases have significant impacts on human health, domestic animal health, and biodiversity. Surveillance is the key to early detection of emerging diseases. A zoo based wildlife disease surveillance program developed in Australia incorporates disease information from free-ranging wildlife into the existing national wildlife health information system. This program uses a collaborative approach and provides a strong model for a disease surveillance program for free-ranging wildlife that enhances the national capacity for early detection of emerging diseases.     

Constructing Rigorous and Broad Biosurveillance Networks for Detecting Emerging Zoonotic Outbreaks

Determining optimal surveillance networks for an emerging pathogen is difficult since it is not known beforehand what the characteristics of a pathogen will be or where it will emerge. The resources for surveillance of infectious diseases in animals and wildlife are often limited and mathematical modeling can play a supporting role in examining a wide range of scenarios of pathogen spread. We demonstrate how a hierarchy of mathematical and statistical tools can be used in surveillance planning help guide successful surveillance and mitigation policies for a wide range of zoonotic pathogens. The model forecasts can help clarify the complexities of potential scenarios, and optimize biosurveillance programs for rapidly detecting infectious diseases. Using the highly pathogenic zoonotic H5N1 avian influenza 2006-2007 epidemic in Nigeria as an example, we determined the risk for infection for localized areas in an outbreak and designed biosurveillance stations that are effective for different pathogen strains and a range of possible outbreak locations. We created a general multi-scale, multi-host stochastic SEIR epidemiological network model, with both short and long-range movement, to simulate the spread of an infectious disease through Nigerian human, poultry, backyard duck, and wild bird populations. We chose parameter ranges specific to avian influenza (but not to a particular strain) and used a Latin hypercube sample experimental design to investigate epidemic predictions in a thousand simulations. We ranked the risk of local regions by the number of times they became infected in the ensemble of simulations. These spatial statistics were then complied into a potential risk map of infection. Finally, we validated the results with a known outbreak, using spatial analysis of all the simulation runs to show the progression matched closely with the observed location of the farms infected in the 2006-2007 epidemic.     

The ecology of chronic wasting disease in wildlife

Prions are misfolded infectious proteins responsible for a group of fatal neurodegenerative diseases termed transmissible spongiform encephalopathy or prion diseases. Chronic Wasting Disease (CWD) is the prion disease with the highest spillover potential, affecting at least seven Cervidae (deer) species. The zoonotic potential of CWD is inconclusive and cannot be ruled out. A risk of infection for other domestic and wildlife species is also plausible. Here, we review the current status of the knowledge with respect to CWD ecology in wildlife. Our current understanding of the geographic distribution of CWD lacks spatial and temporal detail, does not consider the biogeography of infectious diseases, and is largely biased by sampling based on hunters' cooperation and funding available for each region. Limitations of the methods used for data collection suggest that the extent and prevalence of CWD in wildlife is underestimated. If the zoonotic potential of CWD is confirmed in the short term, as suggested by recent results obtained in experimental animal models, there will be limited accurate epidemiological data to inform public health. Research gaps in CWD prion ecology include the need to identify specific biological characteristics of potential CWD reservoir species that better explain susceptibility to spillover, landscape and climate configurations that are suitable for CWD transmission, and the magnitude of sampling bias in our current understanding of CWD distribution and risk. Addressing these research gaps will help anticipate novel areas and species where CWD spillover is expected, which will inform control strategies. From an ecological perspective, control strategies could include assessing restoration of natural predators of CWD reservoirs, ultrasensitive CWD detection in biotic and abiotic reservoirs, and deer density and landscape modification to reduce CWD spread and prevalence.     

Predicting Disease Risk,Identifying Stakeholders,and Informing Control Strategies: A Case Study of Anthrax in Montana

Infectious diseases that affect wildlife and livestock are challenging to manage and can lead to large-scale die-offs, economic losses, and threats to human health. The management of infectious diseases in wildlife and livestock is made easier with knowledge of disease risk across space and identifying stakeholders associated with high-risk landscapes. This study focuses on anthrax, caused by the bacterium Bacillus anthracis, risk to wildlife and livestock in Montana. There is a history of anthrax in Montana, but the spatial extent of disease risk and subsequent wildlife species at risk are not known. Our objective was to predict the potential geographic distribution of anthrax risk across Montana, identify wildlife species at risk and their distributions, and define stakeholders. We used an ecological niche model to predict the potential distribution of anthrax risk. We overlaid susceptible wildlife species distributions and land ownership delineations on our risk map. We found that there was an extensive region across Montana predicted as potential anthrax risk. These potentially risky landscapes overlapped the ranges of all 6 ungulate species considered in the analysis and livestock grazing allotments, and this overlap was on public and private land for all species. Our findings suggest that there is the potential for a multi-species anthrax outbreak on multiple landscapes across Montana. Our potential anthrax risk map can be used to prioritize landscapes for surveillance and for implementing livestock vaccination programs.     

Public health surveillance and infectious disease detection

Emerging infectious diseases, such as HIV/AIDS, SARS, and pandemic influenza, and the anthrax attacks of 2001, have demonstrated that we remain vulnerable to health threats caused by infectious diseases. The importance of strengthening global public health surveillance to provide early warning has been the primary recommendation of expert groups for at least the past 2 decades. However, despite improvements in the past decade, public health surveillance capabilities remain limited and fragmented, with uneven global coverage. Recent initiatives provide hope of addressing this issue, and new technological and conceptual advances could, for the first time, place capability for global surveillance within reach. Such advances include the revised International Health Regulations (IHR 2005) and the use of new data sources and methods to improve global coverage, sensitivity, and timeliness, which show promise for providing capabilities to extend and complement the existing infrastructure. One example is syndromic surveillance, using nontraditional and often automated data sources. Over the past 20 years, other initiatives, including ProMED-mail, GPHIN, and HealthMap, have demonstrated new mechanisms for acquiring surveillance data. In 2009 the U.S. Agency for International Development (USAID) began the Emerging Pandemic Threats (EPT) program, which includes the PREDICT project, to build global capacity for surveillance of novel infections that have pandemic potential (originating in wildlife and at the animal-human interface) and to develop a framework for risk assessment. Improved understanding of factors driving infectious disease emergence and new technological capabilities in modeling, diagnostics and pathogen identification, and communications, such as using the increasing global coverage of cellphones for public health surveillance, can further enhance global surveillance.     

Model-guided fieldwork: practical guidelines for multidisciplinary research on wildlife ecological and epidemiological dynamics

Infectious disease ecology has recently raised its public profile beyond the scientific community due to the major threats that wildlife infections pose to biological conservation, animal welfare, human health and food security. As we start unravelling the full extent of emerging infectious diseases, there is an urgent need to facilitate multidisciplinary research in this area. Even though research in ecology has always had a strong theoretical component, cultural and technical hurdles often hamper direct collaboration between theoreticians and empiricists. Building upon our collective experience of multidisciplinary research and teaching in this area, we propose practical guidelines to help with effective integration among mathematical modelling, fieldwork and laboratory work. Modelling tools can be used at all steps of a field-based research programme, from the formulation of working hypotheses to field study design and data analysis. We illustrate our model-guided fieldwork framework with two case studies we have been conducting on wildlife infectious diseases: plague transmission in prairie dogs and lyssavirus dynamics in American and African bats. These demonstrate that mechanistic models, if properly integrated in research programmes, can provide a framework for holistic approaches to complex biological systems.     

Parasites, emerging disease and wildlife conservation

In this review some emerging issues of parasite infections in wildlife, particularly in Australia, are considered. We discuss the importance of understanding parasite biodiversity in wildlife in terms of conservation, the role of wildlife as reservoirs of parasite infection, and the role of parasites within the broader context of the ecosystem. Using a number of parasite species, the value of undertaking longitudinal surveillance in natural systems using non-invasive sampling and molecular tools to characterise infectious agents is illustrated in terms of wildlife health, parasite biodiversity and ecology.     

Integrating Survey and Molecular Approaches to Better Understand Wildlife Disease Ecology

Infectious wildlife diseases have enormous global impacts, leading to human pandemics, global biodiversity declines and socio-economic hardship. Understanding how infection persists and is transmitted in wildlife is critical for managing diseases, but our understanding is limited. Our study aim was to better understand how infectious disease persists in wildlife populations by integrating genetics, ecology and epidemiology approaches. Specifically, we aimed to determine whether environmental or host factors were stronger drivers of Salmonella persistence or transmission within a remote and isolated wild pig (Sus scrofa) population. We determined the Salmonella infection status of wild pigs. Salmonella isolates were genotyped and a range of data was collected on putative risk factors for Salmonella transmission. We a priori identified several plausible biological hypotheses for Salmonella prevalence (cross sectional study design) versus transmission (molecular case series study design) and fit the data to these models. There were 543 wild pig Salmonella observations, sampled at 93 unique locations. Salmonella prevalence was 41% (95% confidence interval [CI]: 37–45%). The median Salmonella DICE coefficient (or Salmonella genetic similarity) was 52% (interquartile range [IQR]: 42–62%). Using the traditional cross sectional prevalence study design, the only supported model was based on the hypothesis that abundance of available ecological resources determines Salmonella prevalence in wild pigs. In the molecular study design, spatial proximity and herd membership as well as some individual risk factors (sex, condition score and relative density) determined transmission between pigs. Traditional cross sectional surveys and molecular epidemiological approaches are complementary and together can enhance understanding of disease ecology: abundance of ecological resources critical for wildlife influences Salmonella prevalence, whereas Salmonella transmission is driven by local spatial, social, density and individual factors, rather than resources. This enhanced understanding has implications for the control of diseases in wildlife populations. Attempts to manage wildlife disease using simplistic density approaches do not acknowledge the complexity of disease ecology.     

Occupational Risks and Exposures Among Wildlife Health Professionals

Most emerging infectious diseases are zoonotic in origin, with wildlife a frequent source of zoonotic disease events. Although individuals with extensive wildlife contact may be at the greatest risk of contracting novel infectious agents, the occupational risk of those working closely with wildlife has not been well studied. This study assessed the occupational exposures among wildlife health professionals working in multiple countries worldwide. An occupational risk survey of past and present exposures was developed and administered online in a confidential manner to wildlife workers recruited through an ongoing international wildlife pathogen surveillance project. Surveys were completed by 71 participants in 14 countries. Significant lifetime exposures reported included bites from bats and rodents and touching dead animals. Completion of training in occupational safety was reported by 75% of respondents. While gloves were used for most tasks, use of N95 respirators and other personal protective equipment varied by task. Eighty percent of workers reported rabies vaccination. Some respondents indicated interest in enhanced occupational health services targeting their unique needs. Wildlife workers represent an occupational population at risk of zoonotic infection and injury. Enhanced occupational health services targeting wildlife workers could reduce the risk and sequelae of zoonotic exposure and infection.     

Bayesian latent class models for identifying canine visceral leishmaniosis using diagnostic tests in the absence of a gold standard

BackgroundLike many infectious diseases, there is no practical gold standard for diagnosing clinical visceral leishmaniasis (VL). Latent class modeling has been proposed to estimate a latent gold standard for identifying disease. These proposed models for VL have leveraged information from diagnostic tests with dichotomous serological and PCR assays, but have not employed continuous diagnostic test information.Methods/Principal findingsIn this paper, we employ Bayesian latent class models to improve the identification of canine visceral leishmaniasis using the dichotomous PCR assay and the Dual Path Platform (DPP) serology test. The DPP test has historically been used as a dichotomous assay, but can also yield numerical information via the DPP reader. Using data collected from a cohort of hunting dogs across the United States, which were identified as having either negative or symptomatic disease, we evaluate the impact of including numerical DPP reader information as a proxy for immune response. We find that inclusion of DPP reader information allows us to illustrate changes in immune response as a function of age.Conclusions/SignificanceUtilization of continuous DPP reader information can improve the correct discrimination between individuals that are negative for disease and those with clinical VL. These models provide a promising avenue for diagnostic testing in contexts with multiple, imperfect diagnostic tests. Specifically, they can easily be applied to human visceral leishmaniasis when diagnostic test results are available. Also, appropriate diagnosis of canine visceral leishmaniasis has important consequences for curtailing spread of disease to humans.     

Spatial Epidemiology and GIS in Marine Mammal Conservation Medicine and Disease Research

The use of spatial epidemiology and geographical information systems (GIS) facilitates the incorporation of spatial relationships into epidemiological investigations of marine mammal diseases and conservation medicine. Spatial epidemiology is the study of the spatial variation in disease risk or incidence and explicitly addresses spatial structures and functions that factor into disease. The GIS consists of input, management, analysis, and presentation of spatial disease data and can act as an integrative tool so that a range of varied data sources can be combined to describe different environmental aspects of wild animals and their diseases. The use of modern spatial analyses and GIS is becoming well developed in the field of marine mammal ecology and biology, but has just recently started to gain more use in disease research. The use of GIS methodology and spatial analysis in nondisease marine mammal studies is briefly discussed, while examples of the specific uses of these tools in mapping, surveillance and monitoring, disease cluster detection, identification of environmental predictors of disease in wildlife populations, risk assessment, and modeling of diseases, is presented. Marine mammal disease investigations present challenges, such as less consistent access to animals for sampling, fewer baseline data on diseases in wild populations, and less robust epidemiologic study designs, but several recommendations for future research are suggested. Since location is an integral part of investigating disease, spatial epidemiology and GIS should be incorporated as a data management and analysis tool in the study of marine mammal diseases and conservation medicine.     

A network control theory approach to modeling and optimal control of zoonoses: case study of brucellosis transmission in sub-Saharan Africa

Background

Developing control policies for zoonotic diseases is challenging, both because of the complex spread dynamics exhibited by these diseases, and because of the need for implementing complex multi-species surveillance and control efforts using limited resources. Mathematical models, and in particular network models, of disease spread are promising as tools for control-policy design, because they can provide comprehensive quantitative representations of disease transmission.

Methodology/Principal Findings

A layered dynamical network model for the transmission and control of zoonotic diseases is introduced as a tool for analyzing disease spread and designing cost-effective surveillance and control. The model development is achieved using brucellosis transmission among wildlife, cattle herds, and human sub-populations in an agricultural system as a case study. Precisely, a model that tracks infection counts in interacting animal herds of multiple species (e.g., cattle herds and groups of wildlife for brucellosis) and in human subpopulations is introduced. The model is then abstracted to a form that permits comprehensive targeted design of multiple control capabilities as well as model identification from data. Next, techniques are developed for such quantitative design of control policies (that are directed to both the animal and human populations), and for model identification from snapshot and time-course data, by drawing on recent results in the network control community.

Conclusions/Significance

The modeling approach is shown to provide quantitative insight into comprehensive control policies for zoonotic diseases, and in turn to permit policy design for mitigation of these diseases. For the brucellosis-transmission example in particular, numerous insights are obtained regarding the optimal distribution of resources among available control capabilities (e.g., vaccination, surveillance and culling, pasteurization of milk) and points in the spread network (e.g., transhumance vs. sedentary herds). In addition, a preliminary identification of the network model for brucellosis is achieved using historical data, and the robustness of the obtained model is demonstrated. As a whole, our results indicate that network modeling can aid in designing control policies for zoonotic diseases.     

Serological diagnostic tools for the major tick-borne protozoan diseases of livestock

Tick-borne protozoan diseases, babesiosis and theileriosis, are among the most important diseases affecting the productivity of livestock worldwide and resulting in high economic losses. A prerequisite for the control of these diseases is to study their epidemiology by mapping their distribution and seasonality. As clinical diagnostic and surveillance tools, serological tests such as the complement fixation test (CFT), the indirect fluorescent antibody test (IFAT) and the enzyme linked immunosorbent assay (ELISA) have been successfully used over decades. With the development in molecular biology, recombinantly expressed parasite molecules have emerged and substituted crude parasite antigen used in serology. A popular format of these tests is the antibody binding competitive inhibition and the indirect antibody detection ELISA. Under the precondition that these tests are correctly designed and validated, they provide a powerful tool for epidemiology, with greater advantages of affordability and amenability to standardization. This paper reviews the pathogenic tick-borne protozoan diseases and the respective diagnostic ELISA based serological tests currently available for serosurveillance.     

Has the Time Come for Big Science in Wildlife Health?

The consequences of wildlife emerging diseases are global and profound with increased burden on the public health system, negative impacts on the global economy, declines and extinctions of wildlife species, and subsequent loss of ecological integrity. Examples of health threats to wildlife include Batrachochytrium dendrobatidis, which causes a cutaneous fungal infection of amphibians and is linked to declines of amphibians globally; and the recently discovered Pseudogymnoascus (Geomyces) destructans, the etiologic agent of white nose syndrome which has caused precipitous declines of North American bat species. Of particular concern are the novel pathogens that have emerged as they are particularly devastating and challenging to manage. A big science approach to wildlife health research is needed if we are to make significant and enduring progress in managing these diseases. The advent of new analytical models and bench assays will provide us with the mathematical and molecular tools to identify and anticipate threats to wildlife, and understand the ecology and epidemiology of these diseases. Specifically, new molecular diagnostic techniques have opened up avenues for pathogen discovery, and the application of spatially referenced databases allows for risk assessments that can assist in targeting surveillance. Long-term, systematic collection of data for wildlife health and integration with other datasets is also essential. Multidisciplinary research programs should be expanded to increase our understanding of the drivers of emerging diseases and allow for the development of better disease prevention and management tools, such as vaccines. Finally, we need to create a National Fish and Wildlife Health Network that provides the operational framework (governance, policies, procedures, etc.) by which entities with a stake in wildlife health cooperate and collaborate to achieve optimal outcomes for human, animal, and ecosystem health.     

Zoonotic viruses associated with illegally imported wildlife products

The global trade in wildlife has historically contributed to the emergence and spread of infectious diseases. The United States is the world's largest importer of wildlife and wildlife products, yet minimal pathogen surveillance has precluded assessment of the health risks posed by this practice. This report details the findings of a pilot project to establish surveillance methodology for zoonotic agents in confiscated wildlife products. Initial findings from samples collected at several international airports identified parts originating from nonhuman primate (NHP) and rodent species, including baboon, chimpanzee, mangabey, guenon, green monkey, cane rat and rat. Pathogen screening identified retroviruses (simian foamy virus) and/or herpesviruses (cytomegalovirus and lymphocryptovirus) in the NHP samples. These results are the first demonstration that illegal bushmeat importation into the United States could act as a conduit for pathogen spread, and suggest that implementation of disease surveillance of the wildlife trade will help facilitate prevention of disease emergence.     

Applications and advances in acoustic monitoring for infectious disease epidemiology

Emerging infectious diseases continue to pose a significant burden on global public health, and there is a critical need to better understand transmission dynamics arising at the interface of human activity and wildlife habitats. Passive acoustic monitoring (PAM), more typically applied to questions of biodiversity and conservation, provides an opportunity to collect and analyse audio data in relative real time and at low cost. Acoustic methods are increasingly accessible, with the expansion of cloud-based computing, low-cost hardware, and machine learning approaches. Paired with purposeful experimental design, acoustic data can complement existing surveillance methods and provide a novel toolkit to investigate the key biological parameters and ecological interactions that underpin infectious disease epidemiology.     

Anthropogenic noise pollution and wildlife diseases

There is a global rise in anthropogenic noise and a growing awareness of its negative effects on wildlife, but to date the consequences for wildlife diseases have received little attention. In this paper, we discuss how anthropogenic noise can affect the occurrence and severity of infectious wildlife diseases. We argue that there is potential for noise impacts at three main stages of pathogen transmission and disease development: (i) the probability of preinfection exposure, (ii) infection upon exposure, and (iii) severity of postinfection consequences. We identify potential repercussions of noise pollution effects for wildlife populations and call for intensifying research efforts. We provide an overview of knowledge gaps and outline avenues for future studies into noise impacts on wildlife diseases.