From tooth to hoof: treponemes in tissue-destructive diseases

With the advent of new molecular and immunological tools, there is better understanding of the roles that difficult to cultivate bacteria, and not-yet-cultivated bacteria such as spirochaetes, play in polymicrobial diseases. Only relatively recently have studies implicated Treponema spirochaetes in human periodontal disease, a destructive condition of the tissues supporting the teeth. A number of different Treponema species have been isolated and their surface protein components that mediate adhesion, cytotoxicity, and tissue damage have been characterized. More recently Treponema strains closely related to human oral isolates have been cultivated from active lesions of digital dermatitis, an ulcerative condition affecting the feet of cows and sheep. This condition, like periodontal disease, appears to have a polymicrobial aetiology in which enrichment for Treponema may play a crucial part. This article reviews the known mechanisms by which Treponema interact with eukaryotic host cells and tissue proteins, and how these interactions may contribute to pathogenic diversity.     

Pathogen persistence in the environment and insect-baculovirus interactions: disease-density thresholds, epidemic burnout, and insect outbreaks

Classical epidemic theory focuses on directly transmitted pathogens, but many pathogens are instead transmitted when hosts encounter infectious particles. Theory has shown that for such diseases pathogen persistence time in the environment can strongly affect disease dynamics, but estimates of persistence time, and consequently tests of the theory, are extremely rare. We consider the consequences of persistence time for the dynamics of the gypsy moth baculovirus, a pathogen transmitted when larvae consume foliage contaminated with particles released from infectious cadavers. Using field-transmission experiments, we are able to estimate persistence time under natural conditions, and inserting our estimates into a standard epidemic model suggests that epidemics are often terminated by a combination of pupation and burnout rather than by burnout alone, as predicted by theory. Extending our models to allow for multiple generations, and including environmental transmission over the winter, suggests that the virus may survive over the long term even in the absence of complex persistence mechanisms, such as environmental reservoirs or covert infections. Our work suggests that estimates of persistence times can lead to a deeper understanding of environmentally transmitted pathogens and illustrates the usefulness of experiments that are closely tied to mathematical models.     

From host immunity to pathogen invasion: the effects of helminth coinfection on the dynamics of microparasites

Concurrent infections with multiple parasites are ubiquitous in nature. Coinfecting parasites can interact with one another in a variety of ways, including through the host's immune system via mechanisms such as immune trade-offs and immunosuppression. These within-host immune processes mediating interactions among parasites have been described in detail, but how they scale up to determine disease dynamic patterns at the population level is only beginning to be explored. In this review, we use helminth-microparasite coinfection as a model for examining how within-host immunological effects may influence the ecological outcome of microparasitic diseases, with a specific focus on disease invasion. The current literature on coinfection between helminths and major microparasitic diseases includes many studies documenting the effects of helminths on individual host responses to microparasites. In many cases, the observed host responses map directly onto parameters relevant for quantifying disease dynamics; however, there have been few attempts at integrating data on individual-level effects into theoretical models to extrapolate from the individual to the population level. Moreover, there is considerable variability in the particular combination of disease parameters affected by helminths across different microparasite systems. We develop a conceptual framework identifying some potential sources of such variability: Pathogen persistence and severity, and resource availability to hosts. We also generate testable hypotheses regarding diseases and the environmental contexts when the effects of helminths on microparasite dynamics should be most pronounced. Finally, we use a case study of helminth and mycobacterial coinfection in the African buffalo to illustrate both progress and challenges in understanding the population-level consequences of within-host immunological interactions, and conclude with suggestions for future research that will help improve our understanding of the effects of coinfection on dynamics of infectious diseases.     

Pathogeography: leveraging the biogeography of human infectious diseases for global health management

Biogeography is an implicit and fundamental component of almost every dimension of modern biology, from natural selection and speciation to invasive species and biodiversity management. However, biogeography has rarely been integrated into human or veterinary medicine nor routinely leveraged for global health management. Here we review the theory and application of biogeography to the research and management of human infectious diseases, an integration we refer to as ‘pathogeography’. Pathogeography represents a promising framework for understanding and decomposing the spatial distributions, diversity patterns and emergence risks of human infectious diseases into interpretable components of dynamic socio‐ecological systems. Analytical tools from biogeography are already helping to improve our understanding of individual infectious disease distributions and the processes that shape them in space and time. At higher levels of organization, biogeographical studies of diseases are rarer but increasing, improving our ability to describe and explain patterns that emerge at the level of disease communities (e.g. co‐occurrence, diversity patterns, biogeographic regionalisation). Even in a highly globalized world most human infectious diseases remain constrained in their geographic distributions by ecological barriers to the dispersal or establishment of their causal pathogens, reservoir hosts and/or vectors. These same processes underpin the spatial arrangement of other taxa, such as mammalian biodiversity, providing a strong empirical ‘prior’ with which to assess the potential distributions of infectious diseases when data on their occurrence is unavailable or limited. In the absence of quality data, generalized biogeographic patterns could provide the earliest (and in some cases the only) insights into the potential distributions of many poorly known or emerging, or as‐yet‐unknown, infectious disease risks. Encouraging more community ecologists and biogeographers to collaborate with health professionals (and vice versa) has the potential to improve our understanding of infectious disease systems and identify novel management strategies to improve local, global and planetary health.     

Ecophysiology meets conservation: understanding the role of disease in amphibian population declines

Infectious diseases are intimately associated with the dynamics of biodiversity. However, the role that infectious disease plays within ecological communities is complex. The complex effects of infectious disease at the scale of communities and ecosystems are driven by the interaction between host and pathogen. Whether or not a given host-pathogen interaction results in progression from infection to disease is largely dependent on the physiological characteristics of the host within the context of the external environment. Here, we highlight the importance of understanding the outcome of infection and disease in the context of host ecophysiology using amphibians as a model system. Amphibians are ideal for such a discussion because many of their populations are experiencing declines and extinctions, with disease as an important factor implicated in many declines and extinctions. Exposure to pathogens and the host's responses to infection can be influenced by many factors related to physiology such as host life history, immunology, endocrinology, resource acquisition, behaviour and changing climates. In our review, we discuss the relationship between disease and biodiversity. We highlight the dynamics of three amphibian host-pathogen systems that induce different effects on hosts and life stages and illustrate the complexity of amphibian-host-parasite systems. We then review links between environmental stress, endocrine-immune interactions, disease and climate change.     

Animal models simulating anaerobic infections

Animal models simulating human disease have played an important role in our understanding of the pathogenesis and treatment of infections caused by obligately anaerobic bacteria. These models helped document the primary source of such infections as the host's own normal microflora. In addition, the polymicrobial nature of anaerobic infections was documented by using animal models for intraabdominal sepsis. Subsequent studies using animal models have led to an understanding of the nature of the host immune response to abscess causing agents and have been instrumental in defining the molecular basis for the virulence and protection provided by the polysaccharide capsule of Bacteroides fragilis. Animal models have also been important components for studies of toxigenic clostridial diseases, such as antibiotic associated colitis and ulcerative colitis. A discussion of some of these models is provided in this review.     

Dynamics and Control of Diseases in Networks with Community Structure

The dynamics of infectious diseases spread via direct person-to-person transmission (such as influenza, smallpox, HIV/AIDS, etc.) depends on the underlying host contact network. Human contact networks exhibit strong community structure. Understanding how such community structure affects epidemics may provide insights for preventing the spread of disease between communities by changing the structure of the contact network through pharmaceutical or non-pharmaceutical interventions. We use empirical and simulated networks to investigate the spread of disease in networks with community structure. We find that community structure has a major impact on disease dynamics, and we show that in networks with strong community structure, immunization interventions targeted at individuals bridging communities are more effective than those simply targeting highly connected individuals. Because the structure of relevant contact networks is generally not known, and vaccine supply is often limited, there is great need for efficient vaccination algorithms that do not require full knowledge of the network. We developed an algorithm that acts only on locally available network information and is able to quickly identify targets for successful immunization intervention. The algorithm generally outperforms existing algorithms when vaccine supply is limited, particularly in networks with strong community structure. Understanding the spread of infectious diseases and designing optimal control strategies is a major goal of public health. Social networks show marked patterns of community structure, and our results, based on empirical and simulated data, demonstrate that community structure strongly affects disease dynamics. These results have implications for the design of control strategies.     

Seasonal infectious disease epidemiology

Seasonal change in the incidence of infectious diseases is a common phenomenon in both temperate and tropical climates. However, the mechanisms responsible for seasonal disease incidence, and the epidemiological consequences of seasonality, are poorly understood with rare exception. Standard epidemiological theory and concepts such as the basic reproductive number R0 no longer apply, and the implications for interventions that themselves may be periodic, such as pulse vaccination, have not been formally examined. This paper examines the causes and consequences of seasonality, and in so doing derives several new results concerning vaccination strategy and the interpretation of disease outbreak data. It begins with a brief review of published scientific studies in support of different causes of seasonality in infectious diseases of humans, identifying four principal mechanisms and their association with different routes of transmission. It then describes the consequences of seasonality for R0, disease outbreaks, endemic dynamics and persistence. Finally, a mathematical analysis of routine and pulse vaccination programmes for seasonal infections is presented. The synthesis of seasonal infectious disease epidemiology attempted by this paper highlights the need for further empirical and theoretical work.     

Shell disease syndromes of decapod crustaceans

The term shell disease subsumes a number of debilitating conditions affecting the outer integument (the carapace) of decapod crustaceans, such as lobsters and crabs. Herein, we seek to find commonality in the aetiology and pathology of such conditions, and those cases that result in the progressive erosion of the cuticle through to the visceral tissues by a cocktail of microbial-derived enzymes including lipases, proteases and chitinases. Aquimarina spp. are involved in shell disease in many different crustaceans across a wide geographical area, but the overall view is that the condition is polymicrobial in nature leading to dysbiosis within the microbial consortium of the damaged cuticle. The role of environment, decapod behaviour and physiology in triggering this disease is also reviewed. Finally, we provide a conceptual model for disease aetiology and suggest several avenues for future research that could improve our understanding of how such factors trigger, or exacerbate, this condition.     

Transmission dynamics of an emerging infectious disease in wildlife through host reproductive cycles

Emerging infectious diseases are major threats to wildlife populations. To enhance our understanding of the dynamics of these diseases, we investigated how host reproductive behavior and seasonal temperature variation drive transmission of infections among wild hosts, using the model system of cyprinid herpesvirus 3 (CyHV-3) disease in common carp. Our main findings were as follows: (1) a seroprevalence survey showed that CyHV-3 infection occurred mostly in adult hosts, (2) a quantitative assay for CyHV-3 in a host population demonstrated that CyHV-3 was most abundant in the spring when host reproduction occurred and water temperature increased simultaneously and (3) an analysis of the dynamics of CyHV-3 in water revealed that CyHV-3 concentration increased markedly in breeding habitats during host group mating. These results indicate that breeding habitats can become hot spots for transmission of infectious diseases if hosts aggregate for mating and the activation of pathogens occurs during the host breeding season.     

Genetics of Crohn disease, an archetypal inflammatory barrier disease

Chronic inflammatory disorders such as Crohn disease, atopic eczema, asthma and psoriasis are triggered by hitherto unknown environmental factors that function on the background of some polygenic susceptibility. Recent technological advances have allowed us to unravel the genetic aetiology of these and other complex diseases. Using Crohn disease as an example, we show how the discovery of susceptibility genes furthers our understanding of the underlying disease mechanisms and how it will, ultimately, give rise to new therapeutic developments. The long-term goal of such endeavours is to develop targeted prophylactic strategies. These will probably target the molecular interaction on the mucosal surface between the products of the genome and the microbial metagenome of a patient.     

Landscape simplification shapes pathogen prevalence in plant‐pollinator networks

Species interaction networks, which play an important role in determining pathogen transmission and spread in ecological communities, can shift in response to agricultural landscape simplification. However, we know surprisingly little about how landscape simplification‐driven changes in network structure impact epidemiological patterns. Here, we combine mathematical modelling and data from eleven bipartite plant‐pollinator networks observed along a landscape simplification gradient to elucidate how changes in network structure shape disease dynamics. Our empirical data show that landscape simplification reduces pathogen prevalence in bee communities via increased diet breadth of the dominant species. Furthermore, our empirical data and theoretical model indicate that increased connectance reduces the likelihood of a disease outbreak and decreases variance in prevalence among bee species in the community, resulting in a dilution effect. Because infectious diseases are implicated in pollinator declines worldwide, a better understanding of how land use change impacts species interactions is therefore critical for conserving pollinator health.     

Evolution of virulence,environmental change,and the threat posed by emerging and chronic diseases

Assessments of future threats posed by infection have focused largely on zoonotic, acute disease, under the rubric “emerging diseases.” Evolutionary and epidemiological studies indicate, however, that particular aspects of infrastructure, such as protected water supplies, vector-proof housing, and health care facilities, protect against the emergence of zoonotic, acute infectious diseases. While attention in the global health community has focused on emerging diseases, there has been a concurrent, growing recognition that important chronic diseases, such as cancer, are often caused by infectious agents that are already widespread in human populations. For economically prosperous countries, the immediacy of this threat contrasts with their infrastructural protection from severe acute infectious disease. This reasoning leads to the conclusion that chronic infectious diseases pose a more significant threat to economically prosperous countries than zoonotic, acute infectious diseases. Research efforts directed at threats posed by infection may therefore be more effective overall if increased efforts are directed toward understanding and preventing infectious causes of chronic diseases across the spectrum of economic prosperity, as well as toward specific infrastructural improvements in less prosperous countries to protect against virulent, acute infectious diseases.     

Does life history mediate changing disease risk when communities disassemble?

Biodiversity loss sometimes increases disease risk or parasite transmission in humans, wildlife and plants. Some have suggested that this pattern can emerge when host species that persist throughout community disassembly show high host competence – the ability to acquire and transmit infections. Here, we briefly assess the current empirical evidence for covariance between host competence and extirpation risk, and evaluate the consequences for disease dynamics in host communities undergoing disassembly. We find evidence for such covariance, but the mechanisms for and variability around this relationship have received limited consideration. This deficit could lead to spurious assumptions about how and why disease dynamics respond to community disassembly. Using a stochastic simulation model, we demonstrate that weak covariance between competence and extirpation risk may account for inconsistent effects of host diversity on disease risk that have been observed empirically. This model highlights the predictive utility of understanding the degree to which host competence relates to extirpation risk, and the need for a better understanding of the mechanisms underlying such relationships.     

Gene analysis and its role in predicting susceptibility to disease

Recombinant DNA technology can now be applied to the analysis of complex human diseases such as polygenic disorders, where the inheritance of several unknown genes appears to be involved. We review here the progress in the analysis of genes which may be involved in the development of hyperlipidaemia, and show how the approach may be important in our understanding of the aetiology of coronary artery disease.     

New approaches in vaccine development for parasitic infections

Vaccines have had a tremendous impact on the control of infectious diseases. Not only are vaccines potentially the least expensive mechanism to combat infectious diseases, under optimal conditions, widespread vaccination can result in disease eradication - as in the case of smallpox. Despite this great potential, vaccines have had little impact on human parasitic infections. The reasons for this are many - these eukaryotic pathogens are genetically and biologically complex organisms, some with elaborate life cycles and well-honed immune evasion mechanisms. Additionally, our understanding of the mechanisms of immune control of many parasitic infections -- of what constitutes an effective immune response and of how to induce high-quality immunological memory -- is not fully developed. This review attempts to highlight recent advances that could impact vaccine discovery and development in parasitic infections and proposes areas where future studies may lead to breakthroughs in vaccines for the agents of parasitic diseases. There are several other recent reviews highlighting the results of vaccine trials, specifically in the malaria field.     

Local Scale Effects of Disease on Biodiversity

To date, ecologists and conservation biologists have focused much of their attention on the population and ecosystem effects of disease at regional scales and the role that diseases play in global species extinction. Far less research has been dedicated to identifying the effects that diseases can have on local scale species assemblages. We examined the role of infectious disease in structuring local biodiversity. Our intention was to illustrate how variable outcomes can occur by focusing on three case studies: the influence of chestnut blight on forest communities dominated by chestnut trees, the influence of red-spot disease on urchin barrens and kelp forests, and the influence of sylvatic plague on grassland communities inhabited by prairie dogs. Our findings reveal that at local scales infectious disease seems to play an important, though unpredictable, role in structuring species diversity. Through our case studies, we have shown that diseases can cause drastic population declines or local extirpations in keystone species, ecosystem engineers, and otherwise abundant species. These changes in local diversity may be very important, particularly when considered alongside potentially corresponding changes in community structure and function, and we believe that future efforts to understand the importance of disease to species diversity should have an increased focus on these local scales.     

Community structure in social networks: applications for epidemiological modelling

During an infectious disease outbreak people will often change their behaviour to reduce their risk of infection. Furthermore, in a given population, the level of perceived risk of infection will vary greatly amongst individuals. The difference in perception could be due to a variety of factors including varying levels of information regarding the pathogen, quality of local healthcare, availability of preventative measures, etc. In this work we argue that we can split a social network, representing a population, into interacting communities with varying levels of awareness of the disease. We construct a theoretical population and study which such communities suffer most of the burden of the disease and how their awareness affects the spread of infection. We aim to gain a better understanding of the effects that community-structured networks and variations in awareness, or risk perception, have on the disease dynamics and to promote more community-resolved modelling in epidemiology.     

Candida biofilms on implanted biomaterials: a clinically significant problem

In recent years there has been an increasing appreciation that microbial biofilms are ubiquitous, which has resulted in a number of studies on infectious diseases from a biofilm perspective. Biofilms are defined as structured microbial communities that are attached to a surface and encased in a matrix of exopolymeric material. A wide range of biomaterials used in clinical practice have been shown to support colonization and biofilm formation by Candida spp., and the increase in Candida infections in the last decades has almost paralleled the increase and widespread use of a broad range of medical implant devices, mainly in populations with impaired host defenses. Formation of Candida biofilms has important clinical repercussions because of their increased resistance to antifungal therapy and the ability of cells within biofilms to withstand host immune defenses. Further recognition and understanding of the role of Candida biofilms in human infection should help in the clinical management of these recalcitrant infections.     

A Novel Statistical Model to Estimate Host Genetic Effects Affecting Disease Transmission

There is increasing recognition that genetic diversity can affect the spread of diseases, potentially affecting plant and livestock disease control as well as the emergence of human disease outbreaks. Nevertheless, even though computational tools can guide the control of infectious diseases, few epidemiological models can simultaneously accommodate the inherent individual heterogeneity in multiple infectious disease traits influencing disease transmission, such as the frequently modeled propensity to become infected and infectivity, which describes the host ability to transmit the infection to susceptible individuals. Furthermore, current quantitative genetic models fail to fully capture the heritable variation in host infectivity, mainly because they cannot accommodate the nonlinear infection dynamics underlying epidemiological data. We present in this article a novel statistical model and an inference method to estimate genetic parameters associated with both host susceptibility and infectivity. Our methodology combines quantitative genetic models of social interactions with stochastic processes to model the random, nonlinear, and dynamic nature of infections and uses adaptive Bayesian computational techniques to estimate the model parameters. Results using simulated epidemic data show that our model can accurately estimate heritabilities and genetic risks not only of susceptibility but also of infectivity, therefore exploring a trait whose heritable variation is currently ignored in disease genetics and can greatly influence the spread of infectious diseases. Our proposed methodology offers potential impacts in areas such as livestock disease control through selective breeding and also in predicting and controlling the emergence of disease outbreaks in human populations.