PCR to predict risk of airborne disease

Plant, animal and human diseases spread by microscopic airborne particles have had major economic and social impacts during history. Special air-sampling devices have been used to collect such particles since the 19th century but it has often been impossible to identify them accurately. Exciting new opportunities to combine air sampling with quantitative PCR to identify and count these particles are reviewed, using crop pathogen examples. These methods can be used to predict the risk of unexpected outbreaks of airborne diseases by identifying increases in pathogen inoculum or genetic changes in pathogen populations that render control ineffective. The predictions can provide guidance to policymakers, health professionals or the agricultural industry for the development of strategies to minimise the risk of severe pandemics.     

Transmission of Plodia interpunctella granulosis virus does not conform to the mass action model

1. Transmission of insect pathogens is traditionally described by a term which states that transmission is proportional to the densities of the susceptible hosts and the infectious units, multiplied by a constant, the transmission coefficient. Theoretical studies suggest that deviations from this can be important in host–pathogen population dynamics, but little is known of how commonly pathogen transmission conforms to the conventional model.
2. We describe a test of the traditional assumption for the Indian meal moth, Plodia interpunctella (Lepidoptera: Pyralidae) (Hübner) and its granulosis virus using a modification of the previous methods, which allows for unpredictable declines in the amount of infectious material present.
3. The estimated transmission coefficient increased with the density of susceptible hosts and showed a marked decline with density of infectious cadavers. This suggests that the usual assumption does not adequately describe transmission in this system.
4. The reasons for this deviation from the usual assumption are likely to be a combination of behavioural and physiological changes at high host density, and differential susceptibility to the pathogen leading to an effect analogous to pseudo-interference in parasitoids.     

Applying population-genetic models in theoretical evolutionary epidemiology

Much of the existing theory for the evolutionary biology of infectious diseases uses an invasion analysis approach. In this Ideas and Perspectives article, we suggest that techniques from theoretical population genetics can also be profitably used to study the evolutionary epidemiology of infectious diseases. We highlight four ways in which population-genetic models provide benefits beyond those provided by most invasion analyses: (i) they can make predictions about the rate of pathogen evolution; (ii) they explicitly draw out the mechanistic way in which the epidemiological dynamics feed into evolutionary change, and thereby provide new insights into pathogen evolution; (iii) they can make predictions about the evolutionary consequences of non-equilibrium epidemiological dynamics; (iv) they can readily incorporate the effects of multiple host dynamics, and thereby account for phenomena such as immunological history and/or host co-evolution.     

What limits the evolutionary emergence of pathogens?

The ability of a pathogen to cause an epidemic when introduced in a new host population often relies on its ability to adapt to this new environment. Here, we give a brief overview of recent theoretical and empirical studies of such evolutionary emergence of pathogens. We discuss the effects of several ecological and genetic factors that may affect the likelihood of emergence: migration, life history of the infectious agent, host heterogeneity, and the rate and effects of mutations. We contrast different modelling approaches and indicate how details in the way we model each step of a life cycle can have important consequences on the predicted probability of evolutionary emergence. These different theoretical perspectives yield important insights into optimal surveillance and intervention strategies, which should aim for a reduction in the emergence (and re-emergence) of infectious diseases.     

A Quantitative Prioritisation of Human and Domestic Animal Pathogens in Europe

Disease or pathogen risk prioritisations aid understanding of infectious agent impact within surveillance or mitigation and biosecurity work, but take significant development. Previous work has shown the H-(Hirsch-)index as an alternative proxy. We present a weighted risk analysis describing infectious pathogen impact for human health (human pathogens) and well-being (domestic animal pathogens) using an objective, evidence-based, repeatable approach; the H-index. This study established the highest H-index European pathogens. Commonalities amongst pathogens not included in previous surveillance or risk analyses were examined. Differences between host types (humans/animals/zoonotic) in pathogen H-indices were explored as a One Health impact indicator. Finally, the acceptability of the H-index proxy for animal pathogen impact was examined by comparison with other measures. 57 pathogens appeared solely in the top 100 highest H-indices (1) human or (2) animal pathogens list, and 43 occurred in both. Of human pathogens, 66 were zoonotic and 67 were emerging, compared to 67 and 57 for animals. There were statistically significant differences between H-indices for host types (humans, animal, zoonotic), and there was limited evidence that H-indices are a reasonable proxy for animal pathogen impact. This work addresses measures outlined by the European Commission to strengthen climate change resilience and biosecurity for infectious diseases. The results include a quantitative evaluation of infectious pathogen impact, and suggest greater impacts of human-only compared to zoonotic pathogens or scientific under-representation of zoonoses. The outputs separate high and low impact pathogens, and should be combined with other risk assessment methods relying on expert opinion or qualitative data for priority setting, or could be used to prioritise diseases for which formal risk assessments are not possible because of data gaps.     

Populations and infectious diseases: Dynamics and evolution

The host-parasite or host-pathogen system was analyzed from dynamical and evolutionary viewpoints using simple mathematical models incorporating vertical transmission, immunity and its loss. We first analyzed a model without density regulation of host population. In the analysis on dynamics, the condition for the pathogen to work as a density regulating factor was obtained. In the analysis on evolution, criteria for the evolution of host and pathogen were proposed. These criteria implies that the evolution of hosts should result in an increase in infected host density, whereas the evolution of pathogens a decrease in susceptible host density. The direction of evolution at some parameters of host and that of pathogen were examined when the parameters were independently and freely changeable. Among the parameters, only reduction in additional mortality due to infection was the evolutionary trend common to both host and pathogen. In all the other parameters examined, trend of evolution predicted in host is reversed in pathogen. We then analyzed whether the obtained criteria still hold in models with density regulation of hosts. Using randomly generated parameter sets, we obtained the result that the criteria should hold very likely though they do not always hold. We discussed evolution of virulence when there is a constraint between the traits.     

New insights into virulence evolution in multigroup hosts

Many of the standard predictions in evolutionary epidemiology result from models in which all hosts are equally susceptible to acquiring an infection and equally capable of resisting pathogens once an infection has been established. This contrasts with the empirical reality that natural host populations are typically composed of individuals with various susceptibilities and vulnerabilities to pathogen exploitation that can influence all aspects of a given pathogen's transmission-virulence phenotype. In these structured host settings, host-dependent variation in the virulence-transmission trade-off plays an important role in determining pathogen evolution. By deriving some game-theoretic equilibrium expressions that describe pathogen evolution in heterogeneous host populations, the contribution of host heterogeneity to the direction of evolution in host exploitation is made explicit. Within this framework, qualitative departures from predictions derived from theory utilizing a homogeneous host assumption can be seen as a manifestation of Simpson's paradox in an evolutionary setting. By reconsidering some predictions from homogeneous host theory through the lens of this new perspective, it can be seen that many standard predictions are actually special cases that result when homogeneity in immunity parameters is imposed on host populations.     

Directly transmitted viral diseases: modeling the dynamics of transmission

A key hurdle in understanding the spread and control of infectious diseases is to capture appropriately the dynamics of pathogen transmission. As people and goods travel increasingly rapidly around the world, so do pathogens; we must be prepared to understand their spread, in terms of the contact network between hosts, viral life history and within-host dynamics. This will require collaborative work that takes into account viral life history, strategy and evolution, and host genetics, demographics and immunodynamics. Mathematical models are a useful tool for integrating the data and analyses from diverse fields that contribute to our understanding of viral transmission dynamics in heterogeneous host populations.     

Epidemiology and disease control in everyday beef practice

It is important for food animal veterinarians to understand the interaction among animals, pathogens, and the environment, in order to implement herd-specific biosecurity plans. Animal factors such as the number of immunologically protected individuals influence the number of individuals that a potential pathogen is able to infect, as well as the speed of spread through a population. Pathogens differ in their virulence and contagiousness. In addition, pathogens have various methods of transmission that impact how they interact with a host population. A cattle population's environment includes its housing type, animal density, air quality, and exposure to mud or dust and other health antagonists such as parasites and stress; these environmental factors influence the innate immunity of a herd by their impact on immunosuppression. In addition, a herd's environment also dictates the "animal flow" or contact and mixing patterns of potentially infectious and susceptible animals. Biosecurity is the attempt to keep infectious agents away from a herd, state, or country, and to control the spread of infectious agents within a herd. Infectious agents (bacteria, viruses, or parasites) alone are seldom able to cause disease in cattle without contributing factors from other infectious agents and/or the cattle's environment. Therefore to develop biosecurity plans for infectious disease in cattle, veterinarians must consider the pathogen, as well as environmental and animal factors.     

Phylogenetic determinants of potential host shifts in fungal pathogens

Understanding what determines the host range of pathogens and the potential for host shifts is of critical importance to controlling their introductions into new environments. The phylogeny of the hosts has been shown to be important: pathogens are more likely to be infectious on hosts closely related to their host‐of‐origin because of the similar host environments that is shared by descent. The importance of pathogen phylogenies for predicting host range has never been investigated, although a pathogen should also be able to exploit a new host that its close relative can infect. We performed cross‐inoculations using a plant–fungal association and showed that both host and pathogen phylogenies were significant predictors of host range, with at least partly independent effects. Furthermore, we showed that some pathogens were better at infecting novel hosts. Our results should have implications in the context of biological invasions and emergences of new diseases due to globalization.     

The Application of Genomics to Emerging Zoonotic Viral Diseases

Interspecies transmission of pathogens may result in the emergence of new infectious diseases in humans as well as in domestic and wild animals. Genomics tools such as high-throughput sequencing, mRNA expression profiling, and microarray-based analysis of single nucleotide polymorphisms are providing unprecedented ways to analyze the diversity of the genomes of emerging pathogens as well as the molecular basis of the host response to them. By comparing and contrasting the outcomes of an emerging infection with those of closely related pathogens in different but related host species, we can further delineate the various host pathways determining the outcome of zoonotic transmission and adaptation to the newly invaded species. The ultimate challenge is to link pathogen and host genomics data with biological outcomes of zoonotic transmission and to translate the integrated data into novel intervention strategies that eventually will allow the effective control of newly emerging infectious diseases.     

Ecosystem dynamics, biological diversity and emerging infectious diseases

In this article, we summarize the major scientific developments of the last decade on the transmission of infectious agents in multi-host systems. Almost sixty percent of the pathogens that have emerged in humans during the last 30-40 years are of animal origin and about sixty percent of them show an important variety of host species besides humans (3 or more possible host species). In this review, we focus on zoonotic infections with vector-borne transmission and dissect the contrasting effects that a multiplicity of host reservoirs and vectors can have on their disease dynamics. We discuss the effects exerted by host and vector species richness and composition on pathogen prevalence (i.e., reduction, including the dilution effect, or amplification). We emphasize that, in multiple host systems and for vector-borne zoonotic pathogens, host reservoir species and vector species can exert contrasting effect locally. The outcome on disease dynamics (reduced pathogen prevalence in vectors when the host reservoir species is rich and increased pathogen prevalence when the vector species richness increases) may be highly heterogeneous in both space and time. We then ask briefly how a shift towards a more systemic perspective in the study of emerging infectious diseases, which are driven by a multiplicity of hosts, may stimulate further research developments. Finally, we propose some research avenues that take better into account the multi-host species reality in the transmission of the most important emerging infectious diseases, and, particularly, suggest, as a possible orientation, the careful assessment of the life-history characteristics of hosts and vectors in a community ecology-based perspective.     

Biological control of fungal plant diseases

Research has demonstrated the agricultural potential of biological control. For airborne pathogens as well as for soilborne pathogens similar strategies based on different targets in the life cycle of the pathogen can be distinguished, viz. (1) microbial protection of the host against infection, (2) microbial reduction of pathogen sporulation and (3) microbial interference with pathogen survival. Some successes and failures with respect to these targets will be discussed and include (1) biocontrol of seedling diseases, root pathogens, and post-harvest diseases (2) biocontrol of powdery mildew and Botrytis cinerea (3) biocontrol of sclerotial pathogens. Despite of a lot of research on biological control of plant diseases, the number of products available is limited and their market size is marginal. The market for biological control products is not only determined by agricultural aspects such as the number of diseases controlled by one biocontrol product in different crops but also by economic aspects as cost-effective mass production, easy registration and the availability of competing means of control including fungicides. The future development of low-chemical input sustainable agriculture and organic farming will determine the eventual role of biological control in agriculture.     

Local adaptation in the Linum marginale-Melampsora lini host-pathogen interaction

The potential for local adaptation between pathogens and their hosts has generated strong theoretical and empirical interest with evidence both for and against local adaptation reported for a range of systems. We use the Linum marginale-Melampsora lini plant-pathogen system and a hierarchical spatial structure to investigate patterns of local adaptation within a metapopulation characterised by epidemic dynamics and frequent extinction of pathogen populations. Based on large sample sizes and comprehensive cross-inoculation trials, our analyses demonstrate strong local adaptation by Melampsora to its host populations, with this effect being greatest at regional scales, as predicted from the broader spatial scales at which M. lini disperses relative to L. marginale. However, there was no consistent trend for more distant pathogen populations to perform more poorly. Our results further show how the coevolutionary interaction between hosts and pathogens can be influenced by local structure such that resistant hosts select for generally virulent pathogens, while susceptible hosts select for more avirulent pathogens. Empirically, local adaptation has generally been tested in two contrasting ways: (1) pathogen performance on sympatric versus allopatric hosts; and (2) sympatric versus allopatric pathogens on a given host population. In situations where no host population is more resistant or susceptible than others when averaged across pathogen populations (and likewise, no pathogen population is more virulent or avirulent than others), results from these tests should generally be congruent. We argue that this is unlikely to be the case in the metapopulation situations that predominate in natural host-pathogen interactions, thus requiring tests that control simultaneously for variation in plant and pathogen populations.     

Spatiotemporal Model of Barley and Cereal Yellow Dwarf Virus Transmission Dynamics with Seasonality and Plant Competition

Many generalist pathogens are influenced by the spatial distributions and relative abundances of susceptible host species. The spatial structure of host populations can influence patterns of infection incidence (or disease outbreaks), and the effects of a generalist pathogen on host community dynamics in a spatially heterogeneous community may differ from predictions derived via simple models. In this paper, we model the transmission of a generalist pathogen within a patch framework that incorporates the movement of vectors between discrete host patches to investigate the effects of local host community composition and vector movement rates on disease dynamics.     

THE ORIGIN OF SPECIFICITY BY MEANS OF NATURAL SELECTION: EVOLVED AND NONHOST RESISTANCE IN HOST–PATHOGEN INTERACTIONS

Most species seem to be completely resistant to most pathogens and parasites. This resistance has been called “nonhost resistance” because it is exhibited by species that are considered not to be part of the normal host range of the pathogen. A conceptual model is presented suggesting that failure of infection on nonhosts may be an incidental by‐product of pathogen evolution leading to specialization on their source hosts. This model is contrasted with resistance that results from hosts evolving to resist challenge by their pathogens, either as a result of coevolution with a persistent pathogen or as the result of one‐sided evolution by the host against pathogens that are not self‐sustaining on those hosts. Distinguishing evolved from nonevolved resistance leads to contrasting predictions regarding the relationship between resistance and genetic distance. An analysis of cross‐inoculation experiments suggests that the resistance is often the product of pathogen specialization. Understanding the contrasting evolutionary origins of resistance is critical for studies on the genetics and evolution of host–pathogen interactions in human, agricultural, and natural populations. Research on human infectious disease using animal models may often study resistances that have quite contrasting evolutionary origins, and therefore very different underlying genetic mechanisms.     

Organ-on-a-chip models for elucidating the cellular biology of infectious diseases

Infectious diseases are caused by the invasion of pathogens into a host. To explore the mechanisms of pathogen infections and cellular responses, human models that can accurately recapitulate human pathophysiology are needed. Organ-on-a-chip is a type of advanced in vitro model system that cultures cells in microfluidic devices to replicate physiologically relevant microenvironments such as 3D structures, shear stress, and mechanical stimulation. Recently, organ-on-a-chips have been widely adopted to examine the pathophysiology of infectious diseases in detail. Here, we will summarize recent advances in infectious disease research of visceral organs such as the lung, intestine, liver, and kidneys, using organ-on-a-chips.     

A field test of the dilution effect hypothesis in four avian multi-host pathogens

The Dilution Effect Hypothesis (DEH) argues that greater biodiversity lowers the risk of disease and reduces the rates of pathogen transmission since more diverse communities harbour fewer competent hosts for any given pathogen, thereby reducing host exposure to the pathogen. DEH is expected to operate most intensely in vector-borne pathogens and when species-rich communities are not associated with increased host density. Overall, dilution will occur if greater species diversity leads to a lower contact rate between infected vectors and susceptible hosts, and between infected hosts and susceptible vectors. Field-based tests simultaneously analysing the prevalence of several multi-host pathogens in relation to host and vector diversity are required to validate DEH. We tested the relationship between the prevalence in house sparrows (Passer domesticus) of four vector-borne pathogens–three avian haemosporidians (including the avian malaria parasite Plasmodium and the malaria-like parasites Haemoproteus and Leucocytozoon) and West Nile virus (WNV)–and vertebrate diversity. Birds were sampled at 45 localities in SW Spain for which extensive data on vector (mosquitoes) and vertebrate communities exist. Vertebrate censuses were conducted to quantify avian and mammal density, species richness and evenness. Contrary to the predictions of DEH, WNV seroprevalence and haemosporidian prevalence were not negatively associated with either vertebrate species richness or evenness. Indeed, the opposite pattern was found, with positive relationships between avian species richness and WNV seroprevalence, and Leucocytozoon prevalence being detected. When vector (mosquito) richness and evenness were incorporated into the models, all the previous associations between WNV prevalence and the vertebrate community variables remained unchanged. No significant association was found for Plasmodium prevalence and vertebrate community variables in any of the models tested. Despite the studied system having several characteristics that should favour the dilution effect (i.e., vector-borne pathogens, an area where vector and host densities are unrelated, and where host richness is not associated with an increase in host density), none of the relationships between host species diversity and species richness, and pathogen prevalence supported DEH and, in fact, amplification was found for three of the four pathogens tested. Consequently, the range of pathogens and communities studied needs to be broadened if we are to understand the ecological factors that favour dilution and how often these conditions occur in nature.