A Role for Early-Phase Transmission in the Enzootic Maintenance of Plague.

Yersinia pestis, the bacterial agent of plague, is enzootic in many parts of the world within wild rodent populations and is transmitted by different flea vectors. The ecology of plague is complex, with rodent hosts exhibiting varying susceptibilities to overt disease and their fleas exhibiting varying levels of vector competence. A long-standing question in plague ecology concerns the conditions that lead to occasional epizootics among susceptible rodents. Many factors are involved, but a major one is the transmission efficiency of the flea vector. In this study, using Oropsylla montana (a ground squirrel flea that is a major plague vector in the western United States), we comparatively quantified the efficiency of the two basic modes of flea-borne transmission. Transmission efficiency by the early-phase mechanism was strongly affected by the host blood source. Subsequent biofilm-dependent transmission by blocked fleas was less influenced by host blood and was more efficient. Mathematical modeling predicted that early-phase transmission could drive an epizootic only among highly susceptible rodents with certain blood characteristics, but that transmission by blocked O. montana could do so in more resistant hosts irrespective of their blood characteristics. The models further suggested that for most wild rodents, exposure to sublethal doses of Y. pestis transmitted during the early phase may restrain rapid epizootic spread by increasing the number of immune, resistant individuals in the population.

Economical defence of resources structures territorial space use in a cooperative carnivore.

Ecologists have long sought to understand space use and mechanisms underlying patterns observed in nature. We developed an optimality landscape and mechanistic territory model to understand mechanisms driving space use and compared model predictions to empirical reality. We demonstrate our approach using grey wolves (Canis lupus). In the model, simulated animals selected territories to economically acquire resources by selecting patches with greatest value, accounting for benefits, costs and trade-offs of defending and using space on the optimality landscape. Our approach successfully predicted and explained first- and second-order space use of wolves, including the population's distribution, territories of individual packs, and influences of prey density, competitor density, human-caused mortality risk and seasonality. It accomplished this using simple behavioural rules and limited data to inform the optimality landscape. Results contribute evidence that economical territory selection is a mechanistic bridge between space use and animal distribution on the landscape. This approach and resulting gains in knowledge enable predicting effects of a wide range of environmental conditions, contributing to both basic ecological understanding of natural systems and conservation. We expect this approach will demonstrate applicability across diverse habitats and species, and that its foundation can help continue to advance understanding of spatial behaviour.

Physiological links with behavior and fitness: The acute adrenocortical response predicts trappability but not survival in male and female deermice.

The "Cort-Fitness" hypothesis predicts a negative relationship between baseline glucocorticoids (GCs) and fitness, although evidence for this hypothesis remains mixed. Such ambiguity could partially exist because blood GCs, typically used in field studies, can fluctuate too rapidly to measure accurately, while the relationship between GCs and trappability is often neglected. Here, by addressing these factors, we examined relationships between GC measures and survival of North American deermice (Peromyscus maniculatus; hereafter deermice) as a model system. To do this, we used more stable GC measures, including the integrated measures of baseline and stress response fecal corticosterone metabolites (FCMs), and downstream measures of neutrophil/lymphocyte ratio (N/L ratio), and body condition score (BCS), to characterize their relationships with survival and trappability. Over two years, deermice were live-trapped monthly, evaluated for BCS, and sampled for feces and blood. Stress response FCMs were evaluated only at first capture. Mark-recapture models, with GC measures as predictors of either survival or trappability, were compared to identify top models. We found that stress response FCMs negatively predicted trappability, and weaker evidence that BCS positively predicted survival. Although the latter provides some support for the "Cort-Fitness" hypothesis, there was no support when using integrated measures. Instead, our findings suggest that deermice with a lower adrenocortical response (i.e. stress response FCMs) were more likely to be captured. Therefore, GC-trappability relationships must be investigated in field studies to avoid linking the wrong GC profile to fitness, and physiological measures other than blood GCs may be useful for detecting GC-fitness patterns.

Species diversity concurrently dilutes and amplifies transmission in a zoonotic host-pathogen system through competing mechanisms.

In this era of unprecedented biodiversity loss and increased zoonotic disease emergence, it is imperative to understand the effects of biodiversity on zoonotic pathogen dynamics in wildlife. Whether increasing biodiversity should lead to a decrease or increase in infection prevalence, termed the dilution and amplification effects, respectively, has been hotly debated in disease ecology. Sin Nombre hantavirus, which has an ∼35% mortality rate when it spills over into humans, occurs at a lower prevalence in the reservoir host, the North American deermouse, in areas with higher small mammal diversity-a dilution effect. However, the mechanism driving this relationship is not understood. Using a mechanistic mathematical model of infection dynamics and a unique long-term, high-resolution, multisite dataset, it appears that the observed dilution effect is a result of increasing small-mammal diversity leading to decreased deermouse population density and, subsequently, prevalence (a result of density-dependent transmission). However, once density is taken into account, there is an increase in the transmission rate at sites with higher diversity-a component amplification effect. Therefore, dilution and amplification are occurring at the same time in the same host-pathogen system; there is a component amplification effect (increase in transmission rate), but overall a net dilution because the effect of diversity on reservoir host population density is stronger. These results suggest we should focus on how biodiversity affects individual mechanisms that drive prevalence and their relative strengths if we want to make generalizable predictions across host-pathogen systems.

Network analysis of host-virus communities in bats and rodents reveals determinants of cross-species transmission.

Bats are natural reservoirs of several important emerging viruses. Cross-species transmission appears to be quite common among bats, which may contribute to their unique reservoir potential. Therefore, understanding the importance of bats as reservoirs requires examining them in a community context rather than concentrating on individual species. Here, we use a network approach to identify ecological and biological correlates of cross-species virus transmission in bats and rodents, another important host group. We show that given our current knowledge the bat viral sharing network is more connected than the rodent network, suggesting viruses may pass more easily between bat species. We identify host traits associated with important reservoir species: gregarious bats are more likely to share more viruses and bats which migrate regionally are important for spreading viruses through the network. We identify multiple communities of viral sharing within bats and rodents and highlight potential species traits that can help guide studies of novel pathogen emergence.

Toward a Mechanistic Understanding of Environmentally Forced Zoonotic Disease Emergence: Sin Nombre Hantavirus.

Understanding the environmental drivers of zoonotic reservoir and human interactions is crucial to understanding disease risk, but these drivers are poorly predicted. We propose a mechanistic understanding of human-reservoir interactions, using hantavirus pulmonary syndrome as a case study. Crucial processes underpinning the disease's incidence remain poorly studied, including the connectivity among natural and peridomestic deer mouse host activity, virus transmission, and human exposure. We found that disease cases were greatest in arid states and declined exponentially with increasing precipitation. Within arid environments, relatively rare climatic conditions (e.g., El Niño) are associated with increased rainfall and reservoir abundance, producing more frequent virus transmission and host dispersal. We suggest that deer mice increase their occupancy of peridomestic structures during spring-summer, amplifying intraspecific transmission and human infection risk. Disease incidence in arid states may increase with predicted climatic changes. Mechanistic approaches incorporating reservoir behavior, reservoir-human interactions, and pathogen spillover could enhance our understanding of global hantavirus ecology, with applications to other directly transmitted zoonoses.

Bat flight and zoonotic viruses.

Bats are sources of high viral diversity and high-profile zoonotic viruses worldwide. Although apparently not pathogenic in their reservoir hosts, some viruses from bats severely affect other mammals, including humans. Examples include severe acute respiratory syndrome coronaviruses, Ebola and Marburg viruses, and Nipah and Hendra viruses. Factors underlying high viral diversity in bats are the subject of speculation. We hypothesize that flight, a factor common to all bats but to no other mammals, provides an intensive selective force for coexistence with viral parasites through a daily cycle that elevates metabolism and body temperature analogous to the febrile response in other mammals. On an evolutionary scale, this host-virus interaction might have resulted in the large diversity of zoonotic viruses in bats, possibly through bat viruses adapting to be more tolerant of the fever response and less virulent to their natural hosts.

A comparison of bats and rodents as reservoirs of zoonotic viruses: are bats special?

Bats are the natural reservoirs of a number of high-impact viral zoonoses. We present a quantitative analysis to address the hypothesis that bats are unique in their propensity to host zoonotic viruses based on a comparison with rodents, another important host order. We found that bats indeed host more zoonotic viruses per species than rodents, and we identified life-history and ecological factors that promote zoonotic viral richness. More zoonotic viruses are hosted by species whose distributions overlap with a greater number of other species in the same taxonomic order (sympatry). Specifically in bats, there was evidence for increased zoonotic viral richness in species with smaller litters (one young), greater longevity and more litters per year. Furthermore, our results point to a new hypothesis to explain in part why bats host more zoonotic viruses per species: the stronger effect of sympatry in bats and more viruses shared between bat species suggests that interspecific transmission is more prevalent among bats than among rodents. Although bats host more zoonotic viruses per species, the total number of zoonotic viruses identified in bats (61) was lower than in rodents (68), a result of there being approximately twice the number of rodent species as bat species. Therefore, rodents should still be a serious concern as reservoirs of emerging viruses. These findings shed light on disease emergence and perpetuation mechanisms and may help lead to a predictive framework for identifying future emerging infectious virus reservoirs.

Food availability leads to more connected contact networks among peridomestic zoonotic reservoir hosts.

The North American deermouse (Peromyscus maniculatus) is a reservoir host for many zoonotic pathogens. Deermice have been well studied, but few studies have attempted to understand social interactions within the species despite these interactions being key to understanding disease transmission. We performed an experiment to determine if supplemental food or nesting material affected social interactions of deermice and tested if interactions increased with increasing population density. We constructed three simulated buildings that received one of three treatments: food, nesting material, or control. Mice were tagged with passive integrated transponder (PIT) tags, and their movement in and out of buildings was monitored with PIT tag readers. PIT tag readings were used to create contact networks, assuming a contact if two deermice were in the same building at the same time. We found that buildings with food led to contact networks that were approximately 10 times more connected than buildings with nesting material or control buildings. We also saw a significant effect of population density on the average number of contacts per individual. These results suggest that food supplementation which is common in peridomestic settings, can significantly increase contacts between reservoir hosts, potentially leading to increased transmission of zoonotic viruses within the reservoir host and from reservoir hosts to humans.

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.

Sin Nombre hantavirus decreases survival of male deer mice.

How pathogens affect their hosts is a key question in infectious disease ecology, and it can have important influences on the spread and persistence of the pathogen. Sin Nombre virus (SNV) is the etiological agent of hantavirus pulmonary syndrome (HPS) in humans. A better understanding of SNV in its reservoir host, the deer mouse, could lead to improved predictions of the circulation and persistence of the virus in the mouse reservoir, and could help identify the factors that lead to increased human risk of HPS. Using mark-recapture statistical modeling on longitudinal data collected over 15 years, we found a 13.4% decrease in the survival of male deer mice with antibodies to SNV compared to uninfected mice (both male and female). There was also an additive effect of breeding condition, with a 21.3% decrease in survival for infected mice in breeding condition compared to uninfected, non-breeding mice. The data identified that transmission was consistent with density-dependent transmission, implying that there may be a critical host density below which SNV cannot persist. The notion of a critical host density coupled with the previously overlooked disease-induced mortality reported here contribute to a better understanding of why SNV often goes extinct locally and only seems to persist at the metapopulation scale, and why human spillover is episodic and hard to predict.

Nitrogen and phosphorus fertilization consistently favor pathogenic over mutualistic fungi in grassland soils.

Ecosystems across the globe receive elevated inputs of nutrients, but the consequences of this for soil fungal guilds that mediate key ecosystem functions remain unclear. We find that nitrogen and phosphorus addition to 25 grasslands distributed across four continents promotes the relative abundance of fungal pathogens, suppresses mutualists, but does not affect saprotrophs. Structural equation models suggest that responses are often indirect and primarily mediated by nutrient-induced shifts in plant communities. Nutrient addition also reduces co-occurrences within and among fungal guilds, which could have important consequences for belowground interactions. Focusing only on plots that received no nutrient addition, soil properties influence pathogen abundance globally, whereas plant community characteristics influence mutualists, and climate influence saprotrophs. We show consistent, guild-level responses that enhance our ability to predict shifts in soil function related to anthropogenic eutrophication, which can have longer-term consequences for plant communities.

The effect of seasonality, density and climate on the population dynamics of Montana deer mice, important reservoir hosts for Sin Nombre hantavirus.

1. Since Sin Nombre virus was discovered in the U.S. in 1993, longitudinal studies of the rodent reservoir host, the deer mouse (Peromyscus maniculatus) have demonstrated a qualitative correlation among mouse population dynamics and risk of hantavirus pulmonary syndrome (HPS) in humans, indicating the importance of understanding deer mouse population dynamics for evaluating risk of HPS. 2. Using capture-mark-recapture statistical methods on a 15-year data set from Montana, we estimated deer mouse survival, maturation and recruitment rates and tested the relative importance of seasonality, population density and local climate in explaining temporal variation in deer mouse demography. 3. From these estimates, we designed a population model to simulate deer mouse population dynamics given climatic variables and compared the model to observed patterns. 4. Month, precipitation 5 months previously, temperature 5 months previously and to a lesser extent precipitation and temperature in the current month, were important in determining deer mouse survival. Month, the sum of precipitation over the last 4 months, and the sum of the temperature over the last 4 months were important in determining recruitment rates. Survival was more important in determining the growth rate of the population than recruitment. 5. While climatic drivers appear to have a complex influence on dynamics, our forecasts were good. Our quantitative model may allow public health officials to better predict increased human risk from basic climatic data.

Leukocyte Evaluation of the Free-Ranging Deermouse (Peromyscus maniculatus) from Montana, USA.

We generated reference ranges for seasonal leukocyte differential counts of the free-ranging deermouse (Peromyscus maniculatus) from Montana, US. Blood was collected from the retro-orbital capillary sinus of deermice after topical anesthesia with proparacaine. Although season influenced lymphocyte, neutrophil, and monocyte absolute counts, sex and reproductive status did not.

Nonlinear population dynamics are ubiquitous in animals.

Nonlinear dynamics, where a change in the input is not proportional to a change in the output, are often found throughout nature, for example in biochemical kinetics. Because of the complex suite of interacting abiotic and biotic variables present in ecosystems, animal population dynamics are often thought to be driven in a nonlinear, state-dependent fashion. However, so far these have only been identified in model organisms and some natural systems. Here we show that nonlinear population dynamics are ubiquitous in nature. We use nonlinear forecasting to analyse 747 datasets of 228 species to find that insect population trends were highly nonlinear (74%), followed by mammals (58%), bony fish (49%) and birds (35%). This indicates that linear, equilibrium-based model assumptions may fail at predicting population dynamics across a wide range of animal taxa. We show that faster-reproducing animals are more likely to have nonlinear and high-dimensional dynamics, supporting past ecological theory. Lastly, only a third of time series were predictable beyond two years; therefore, the ability to predict animal population trends using these methods may be limited. Our results suggest that the complex dynamics necessary to cause regime shifts and other transitions may be inherent in a wide variety of animals.

Maternal antibody and the maintenance of a lyssavirus in populations of seasonally breeding African bats.

Pathogens causing acute disease and death or lasting immunity require specific spatial or temporal processes to persist in populations. Host traits, such as maternally-derived antibody (MDA) and seasonal birthing affect infection maintenance within populations. Our study objective is to understand how viral and host traits lead to population level infection persistence when the infection can be fatal. We collected data on African fruit bats and a rabies-related virus, Lagos bat virus (LBV), including through captive studies. We incorporate these data into a mechanistic model of LBV transmission to determine how host traits, including MDA and seasonal birthing, and viral traits, such as incubation periods, interact to allow fatal viruses to persist within bat populations. Captive bat studies supported MDA presence estimated from field data. Captive bat infection-derived antibody decayed more slowly than MDA, and while faster than estimates from the field, supports field data that suggest antibody persistence may be lifelong. Unobserved parameters were estimated by particle filtering and suggest only a small proportion of bats die of disease. Pathogen persistence in the population is sensitive to this proportion, along with MDA duration and incubation period. Our analyses suggest MDA produced bats and prolonged virus incubation periods allow viral maintenance in adverse conditions, such as a lethal pathogen or strongly seasonal resource availability for the pathogen in the form of seasonally pulsed birthing.

Mapping U.S. cattle shipment networks: Spatial and temporal patterns of trade communities from 2009 to 2011.

The application of network analysis to cattle shipments broadens our understanding of shipment patterns beyond pairwise interactions to the network as a whole. Such a quantitative description of cattle shipments in the U.S. can identify trade communities, describe temporal shipment patterns, and inform the design of disease surveillance and control strategies. Here, we analyze a longitudinal dataset of beef and dairy cattle shipments from 2009 to 2011 in the United States to characterize communities within the broader cattle shipment network, which are groups of counties that ship mostly to each other. Because shipments occur over time, we aggregate the data at various temporal scales to examine the consistency of network and community structure over time. Our results identified nine large (>50 counties) communities based on shipments of beef cattle in 2009 aggregated into an annual network and nine large communities based on shipments of dairy cattle. The size and connectance of the shipment network was highly dynamic; monthly networks were smaller than yearly networks and revealed seasonal shipment patterns consistent across years. Comparison of the shipment network over time showed largely consistent shipping patterns, such that communities identified on annual networks of beef and diary shipments from 2009 still represented 41-95% of shipments in monthly networks from 2009 and 41-66% of shipments from networks in 2010 and 2011. The temporal aspects of cattle shipments suggest that future applications of the U.S. cattle shipment network should consider seasonal shipment patterns. However, the consistent within-community shipping patterns indicate that yearly communities could provide a reasonable way to group regions for management.

Utility of mosquito surveillance data for spatial prioritization of vector control against dengue viruses in three Brazilian cities.

BACKGROUND: Vector control remains the primary defense against dengue fever. Its success relies on the assumption that vector density is related to disease transmission. Two operational issues include the amount by which mosquito density should be reduced to minimize transmission and the spatio-temporal allotment of resources needed to reduce mosquito density in a cost-effective manner. Recently, a novel technology, MI-Dengue, was implemented city-wide in several Brazilian cities to provide real-time mosquito surveillance data for spatial prioritization of vector control resources. We sought to understand the role of city-wide mosquito density data in predicting disease incidence in order to provide guidance for prioritization of vector control work. METHODS: We used hierarchical Bayesian regression modeling to examine the role of city-wide vector surveillance data in predicting human cases of dengue fever in space and time. We used four years of weekly surveillance data from Vitoria city, Brazil, to identify the best model structure. We tested effects of vector density, lagged case data and spatial connectivity. We investigated the generality of the best model using an additional year of data from Vitoria and two years of data from other Brazilian cities: Governador Valadares and Sete Lagoas. RESULTS: We found that city-wide, neighborhood-level averages of household vector density were a poor predictor of dengue-fever cases in the absence of accounting for interactions with human cases. Effects of city-wide spatial patterns were stronger than within-neighborhood or nearest-neighborhood effects. Readily available proxies of spatial relationships between human cases, such as economic status, population density or between-neighborhood roadway distance, did not explain spatial patterns in cases better than unweighted global effects. CONCLUSIONS: For spatial prioritization of vector controls, city-wide spatial effects should be given more weight than within-neighborhood or nearest-neighborhood connections, in order to minimize city-wide cases of dengue fever. More research is needed to determine which data could best inform city-wide connectivity. Once these data become available, MI-dengue may be even more effective if vector control is spatially prioritized by considering city-wide connectivity between cases together with information on the location of mosquito density and infected mosquitos.

Changes in rodent abundance and weather conditions potentially drive hemorrhagic fever with renal syndrome outbreaks in Xi'an, China, 2005-2012.

BACKGROUND: Increased risks for hemorrhagic fever with renal syndrome (HFRS) caused by Hantaan virus have been observed since 2005, in Xi'an, China. Despite increased vigilance and preparedness, HFRS outbreaks in 2010, 2011, and 2012 were larger than ever, with a total of 3,938 confirmed HFRS cases and 88 deaths in 2010 and 2011. METHODS AND FINDINGS: Data on HFRS cases and weather were collected monthly from 2005 to 2012, along with active rodent monitoring. Wavelet analyses were performed to assess the temporal relationship between HFRS incidence, rodent density and climatic factors over the study period. Results showed that HFRS cases correlated to rodent density, rainfall, and temperature with 2, 3 and 4-month lags, respectively. Using a Bayesian time-series Poisson adjusted model, we fitted the HFRS outbreaks among humans for risk assessment in Xi'an. The best models included seasonality, autocorrelation, rodent density 2 months previously, and rainfall 2 to 3 months previously. Our models well reflected the epidemic characteristics by one step ahead prediction, out-of-sample. CONCLUSIONS: In addition to a strong seasonal pattern, HFRS incidence was correlated with rodent density and rainfall, indicating that they potentially drive the HFRS outbreaks. Future work should aim to determine the mechanism underlying the seasonal pattern and autocorrelation. However, this model can be useful in risk management to provide early warning of potential outbreaks of this disease.

Rhesus macaque MHC class I molecules present HLA-B-like peptides.

SIV-infected Indian rhesus macaques (Macaca mulatta) are an important animal model for humans infected with HIV. Understanding macaque (M. mulatta class I (Mamu)) MHC class I-peptide binding facilitates the comparison of SIV- and HIV-specific cellular immune responses. In this study, we characterized the endogenous peptide-binding properties of three Mamu-A (A*02, A*08, A*11) and three Mamu-B (B*01, B*03, B*12) class I molecules. Motif comparisons revealed that five of the six macaque class I molecules (A*02, A*08, A*11, B*01, and B*03) have peptide-binding motifs similar to those of human class I molecules. Of the 65 macaque endogenous peptide ligands that we sequenced by tandem mass spectroscopy, 5 were previously eluted from HLA class I molecules. Nonamers predominated among the individual ligands, and both the motifs and the individual ligands indicated P2, P9, and various ancillary anchors. Interestingly, peptide binding of the Mamu-A and Mamu-B molecules exhibited cross-species peptide-presentation overlap primarily with HLA-B molecules. Indeed, all of the macaque class I molecules appeared HLA-B-like in peptide presentation. Remarkably, the overlap in macaque- and HLA-peptide presentation occurred despite divergent class I peptide-binding grooves. Macaque and human class I differing by up to 42 aa (13-23%) within the alpha-1 and alpha-2 domains, including substantial divergence within specificity pockets A-F, bound the same endogenous peptide. Therefore, endogenous peptide characterization indicates that macaque class I molecules may be the functional equivalents of HLA-B molecules.