Distribution of the disease pathogen Batrachochytrium dendrobatidis in non‐epidemic amphibian communities of western Canada

Chytridiomycosis is an emerging infectious disease of amphibians caused by the waterborne pathogen Batrachochytrium dendrobatidis (Bd) and is responsible for the recent decline of species worldwide. Elucidating patterns in disease prevalence has proved challenging, as small‐scale studies to date have provided conflicting results. We present data on the prevalence of Bd (the proportion of individuals with Bd) collected from amphibians sampled throughout British Columbia. We had two different datasets: our original dataset includes 1129 individuals sampled in 103 sites representing 14 species. A second dataset has 839 individuals sampled in 19 sites representing 10 species. We use a Bayesian state‐space occupancy modelling approach to estimate the probability that an individual is Bd+ as a function of individual and site characteristics. Cross‐validation techniques and the original dataset were used to find the best model: this model includes species, life stage, and geographic location. Our results suggest that Bd prevalence is not strongly related to seasonality, latitude or site type. Within a species, Bd prevalence depended on life stage; the watershed in which a site occurs may also usefully predict prevalence. Overall observed infection prevalence was ～16%. Our best model accurately assigns Bd status to an individual ～ 42% of the time. Taking advantage of the Bayesian framework, we ran an analysis with the second dataset using estimates from the original model as prior values. We present posterior density distributions for those sites and species with narrow credible intervals, and show that sites tend to be either highly likely or highly unlikely to have individuals with Bd, while individuals of some stages of some species have an intermediate likelihood of being Bd‐positive. The Bayesian model using informed priors had increased accuracy rates in assigning Bd status to both individuals and groups of individuals.     

Estimation of the Exposure of the UK Population to the Bovine Spongiform Encephalopathy Agent through Dietary Intake During the Period 1980 to 1996

Although the incidence of variant Creutzfeldt-Jakob disease (vCJD) has declined to 1 since 2012 in the UK, uncertainty remains regarding possible future cases and the size of the subclinical population that may cause secondary transmission of the disease through blood transfusion. Estimating the number of individuals who were exposed to the bovine spongiform encephalopathy (BSE) infectious agent and may be susceptible to vCJD will help to clarify related public health concerns and plan strategies. In this paper, we explore this estimate by describing the probability of potential exposure due to dietary intake throughout the BSE epidemic period from 1980 to 1996 as a stochastic Poisson process. We estimate the age- and gender-specific exposure intensities in food categories of beef and beef-containing dishes, burgers and kebabs, pies, and sausages, separating the two periods of 1980–1989 and 1990–1996 due to the specified bovine offal legislation of 1989. The estimated total number of (living) exposed individuals during each period is 5,089,027 (95% confidence interval [CI] 4,514,963–6,410,317), which was obtained by multiplying the population size of different birth cohorts by the probability of exposure via dietary intake and the probability of survival until the end of 2013. The estimated number is approximately doubled, assuming a contamination rate of . Among those individuals estimated, 31,855 (95% CI 26,849–42,541) are susceptible to infection. We also examined the threshold hypothesis by fitting an extreme-value distribution to the estimated infectious dose of the exposed individuals and obtained a threshold estimate of 13.7 bID₅₀ (95% CI 6.6–26.2 bID₅₀) (Weibull). The results provide useful information on potential carriers of prion disease who may pose a threat of infection via blood transfusion and thus provide insight into the likelihood of new incidents of vCJD occurring in the future.     

Parameterizing Spatial Models of Infectious Disease Transmission that Incorporate Infection Time Uncertainty Using Sampling-Based Likelihood Approximations

A class of discrete-time models of infectious disease spread, referred to as individual-level models (ILMs), are typically fitted in a Bayesian Markov chain Monte Carlo (MCMC) framework. These models quantify probabilistic outcomes regarding the risk of infection of susceptible individuals due to various susceptibility and transmissibility factors, including their spatial distance from infectious individuals. The infectious pressure from infected individuals exerted on susceptible individuals is intrinsic to these ILMs. Unfortunately, quantifying this infectious pressure for data sets containing many individuals can be computationally burdensome, leading to a time-consuming likelihood calculation and, thus, computationally prohibitive MCMC-based analysis. This problem worsens when using data augmentation to allow for uncertainty in infection times. In this paper, we develop sampling methods that can be used to calculate a fast, approximate likelihood when fitting such disease models. A simple random sampling approach is initially considered followed by various spatially-stratified schemes. We test and compare the performance of our methods with both simulated data and data from the 2001 foot-and-mouth disease (FMD) epidemic in the U.K. Our results indicate that substantial computation savings can be obtained—albeit, of course, with some information loss—suggesting that such techniques may be of use in the analysis of very large epidemic data sets.     

Diseases and causes of death in European bats: dynamics in disease susceptibility and infection rates

Background

Bats receive increasing attention in infectious disease studies, because of their well recognized status as reservoir species for various infectious agents. This is even more important, as bats with their capability of long distance dispersal and complex social structures are unique in the way microbes could be spread by these mammalian species. Nevertheless, infection studies in bats are predominantly limited to the identification of specific pathogens presenting a potential health threat to humans. But the impact of infectious agents on the individual host and their importance on bat mortality is largely unknown and has been neglected in most studies published to date.

Methodology/Principal Findings

Between 2002 and 2009, 486 deceased bats of 19 European species (family Vespertilionidae) were collected in different geographic regions in Germany. Most animals represented individual cases that have been incidentally found close to roosting sites or near human habitation in urban and urban-like environments. The bat carcasses were subjected to a post-mortem examination and investigated histo-pathologically, bacteriologically and virologically. Trauma and disease represented the most important causes of death in these bats. Comparative analysis of pathological findings and microbiological results show that microbial agents indeed have an impact on bats succumbing to infectious diseases, with fatal bacterial, viral and parasitic infections found in at least 12% of the bats investigated.

Conclusions/Significance

Our data demonstrate the importance of diseases and infectious agents as cause of death in European bat species. The clear seasonal and individual variations in disease prevalence and infection rates indicate that maternity colonies are more susceptible to infectious agents, underlining the possible important role of host physiology, immunity and roosting behavior as risk factors for infection of bats.     

Public avoidance and epidemics: insights from an economic model

In this paper, we present a mathematical model of infectious disease transmission in which people can engage in public avoidance behavior to minimize the likelihood of acquiring an infection. The framework employs the economist's theory of utility maximization to model people's decision regarding their level of public avoidance. We derive the reproductive number of a disease which determines whether an endemic equilibrium exists or not. We show that when the contact function exhibits saturation, an endemic equilibrium must be unique. Otherwise, multiple endemic equilibria that differ in disease prevalence can coexist, and which one the population gets to depends on initial conditions. Even when a unique endemic equilibrium exists, people's preferences and the initial conditions may determine whether the disease will eventually die out or become endemic. Public health policies that increase the recovery rate or encourage self-quarantine by infected people can be beneficial to the community by lowering disease prevalence. However, it is also possible for these policies to worsen the situation and cause prevalence to rise since these measures give people less incentive to engage in public avoidance behavior. We also show that implementing policies that result in a higher level of public avoidance behavior in equilibrium does not necessarily lower prevalence and can result in more infections.     

Economic Incentives in the Socially Optimal Management of Infectious Disease: When $$ R_{0} $$ is Not Enough

Does society benefit from encouraging or discouraging private infectious disease-risk mitigation? Private individuals routinely mitigate infectious disease risks through the adoption of a range of precautions, from vaccination to changes in their contact with others. Such precautions have epidemiological consequences. Private disease-risk mitigation generally reduces both peak prevalence of symptomatic infection and the number of people who fall ill. At the same time, however, it can prolong an epidemic. A reduction in prevalence is socially beneficial. Prolongation of an epidemic is not. We find that for a large class of infectious diseases, private risk mitigation is socially suboptimal—either too low or too high. The social optimum requires either more or less private mitigation. Since private mitigation effort depends on the cost of mitigation and the cost of illness, interventions that change either of these costs may be used to alter mitigation decisions. We model the potential for instruments that affect the cost of illness to yield net social benefits. We find that where a disease is not very infectious or the duration of illness is short, it may be socially optimal to promote private mitigation effort by increasing the cost of illness. By contrast, where a disease is highly infectious or long lasting, it may be optimal to discourage private mitigation by reducing the cost of disease. Society would prefer a shorter, more intense, epidemic to a longer, less intense epidemic. There is, however, a region in parameter space where the relationship is more complicated. For moderately infectious diseases with medium infectious periods, the social optimum depends on interactions between prevalence and duration. Basic reproduction numbers are not sufficient to predict the social optimum.     

Current Status and Challenge of Pseudorabies Virus Infection in China

Pseudorabies(PR), also called Aujeszky's disease, is a highly infectious disease caused by pseudorabies virus(PRV).Without specific host tropism, PRV can infect a wide variety of mammals, including pig, sheep, cattle, etc., thereby causing severe clinical symptoms and acute death. PRV was firstly reported in China in 1950 s, while outbreaks of emerging PRV variants have been documented in partial regions since 2011, leading to significant economic losses in swine industry.Although scientists have been devoting to the design of diagnostic approaches and the development of vaccines during the past years, PR remains a vital infectious disease widely prevalent in Chinese pig industry. Especially, its potential threat to human health has also attracted the worldwide attention. In this review, we will provide a summary of current understanding of PRV in China, mainly focusing on PRV history, the existing diagnosis methods, PRV prevalence in pig population and other susceptible mammals, molecular characteristics, and the available vaccines against its infection.Additionally, promising agents including traditional Chinese herbal medicines and novel inhibitors that may be employed to treat this viral infection, are also discussed.     

Effects of low-density feeding on elk–fetus contact rates on Wyoming feedgrounds

High seroprevalance for Brucella abortus among elk on Wyoming feedgrounds suggests that supplemental feeding may influence parasite transmission and disease dynamics by altering the rate at which elk contact infectious materials in their environment. We used proximity loggers and video cameras to estimate rates of elk-to-fetus contact (the primary source of brucellosis transmission) during winter supplemental feeding. We compared contact rates during high-density and low-density (LD) feeding treatments that provided the same total amount of food distributed over different areas. Low-density feeding led to >70% reductions in total number of contacts and number of individuals contacting a fetus. Proximity loggers and video cameras provided similar estimates of elk–fetus contact rates. Elk contacted fetuses and random control points equally, suggesting that elk were not attracted to fetuses but encountered them incidentally while feeding. The modeled relationship between contact rate and disease prevalence is nonlinear and LD feeding may result in large reductions in brucellosis prevalence, but this depends on the amount of transmission that occurs on and off feedgrounds. © 2012 The Wildlife Society.     

A Few Bad Apples: A Model of Disease Influenced Agent Behaviour in a Heterogeneous Contact Environment

For diseases that infect humans or livestock, transmission dynamics are at least partially dependent on human activity and therefore human behaviour. However, the impact of human behaviour on disease transmission is relatively understudied, especially in the context of heterogeneous contact structures such as described by a social network. Here, we use a strategic game, coupled with a simple disease model, to investigate how strategic agent choices impact the spread of disease over a contact network. Using beliefs that are based on disease status and that build up over time, agents choose actions that stochastically determine disease spread on the network. An agent’s disease status is therefore a function of both his own and his neighbours actions. The effect of disease on agents is modelled by a heterogeneous payoff structure. We find that the combination of network shape and distribution of payoffs has a non-trivial impact on disease prevalence, even if the mean payoff remains the same. An important scenario occurs when a small percentage (called noncooperators) have little incentive to avoid disease. For diseases that are easily acquired when taking a risk, then even when good behavior can lead to disease eradication, a small increase in the percentage of noncooperators (less than 5%) can yield a large (up to 25%) increase in prevalence.     

A stochastic SIR model with contact-tracing: large population limits and statistical inference

This paper is devoted to the presentation and study of a specific stochastic epidemic model accounting for the effect of contact-tracing on the spread of an infectious disease. Precisely, one considers here the situation in which individuals identified as infected by the public health detection system may contribute to detecting other infectious individuals by providing information related to persons with whom they have had possibly infectious contacts. The control strategy, which consists of examining each individual who has been able to be identified on the basis of the information collected within a certain time period, is expected to efficiently reinforce the standard random-screening-based detection and considerably ease the epidemic. In the novel modelling of the spread of a communicable infectious disease considered here, the population of interest evolves through demographic, infection and detection processes, in a way that its temporal evolution is described by a stochastic Markov process, of which the component accounting for the contact-tracing feature is assumed to be valued in a space of point measures. For adequate scalings of the demographic, infection and detection rates, it is shown to converge to the weak deterministic solution of a PDE system, as a parameter n, interpreted as the population size, roughly speaking, becomes larger. From the perspective of the analysis of infectious disease data, this approximation result may serve as a key tool for exploring the asymptotic properties of standard inference methods such as maximum likelihood estimation. We state preliminary statistical results in this context. Eventually, relations of the model with the available data of the HIV epidemic in Cuba, in which country a contact-tracing detection system has been set up since 1986, is investigated and numerical applications are carried out.     

Influence of age on the haemoglobin concentration of malaria-infected patients in a reference centre in the Brazilian Amazon

Anaemia is amongst the major complications of malaria, a major public health problem in the Amazon Region in Latin America. We examined the haemoglobin (Hb) concentrations of malaria-infected patients and compared it to that of malaria-negative febrile patients and afebrile controls. The haematological parameters of febrile patients who had a thick-blood-smear performed at an infectious diseases reference centre of the Brazilian Amazon between December 2009-January 2012 were retrieved together with clinical data. An afebrile community control group was composed from a survey performed in a malaria-endemic area. Hb concentrations and anaemia prevalence were analysed according to clinical-epidemiological status and demographic characteristics. In total, 7,831 observations were included. Patients with Plasmodium falciparum infection had lower mean Hb concentrations (10.5 g/dL) followed by P. vivax-infected individuals (12.4 g/dL), community controls (12.8 g/dL) and malaria-negative febrile patients (13.1 g/dL) (p < 0.001). Age, gender and clinical-epidemiological status were strong independent predictors for both outcomes. Amongst malaria-infected individuals, women in the reproductive age had considerably lower Hb concentrations. In this moderate transmission intensity setting, both vivax and falciparum malaria are associated with reduced Hb concentrations and risk of anaemia throughout a wide age range.     

Prevalence of antibodies to selected viral pathogens in wild boars (Sus scrofa) in Croatia in 2005-06 and 2009-10

We determined prevalence of antibody to selected viral pathogens important for domestic pigs and livestock in 556 wild boar (Sus scrofa) sera collected during 2005-06 and 2009-10 in four counties in Croatia. These counties account for an important part of the Croatian commercial pig production and have a high density of wild boars. Samples were tested for antibodies to porcine parvovirus (PPV), Aujeszky's disease virus (ADV), porcine circovirus type 2 (PCV2), swine influenza virus, porcine respiratory and reproductive syndrome virus (PRRSV), porcine respiratory coronavirus (PRCV), transmissible gastroenteritis virus, and swine vesicular disease virus (SVDV). Antibodies to all of the infectious pathogens except SVDV were detected. There was a statistically significant difference in prevalence between the two periods for PPV, ADV, PCV2, PRRSV, and PRCV, with a higher prevalence of PPV and ADV in the 2009-10 period (P<0.05). During the same period, the prevalence of PCV2, PRRSV, and PRCV was lower (P<0.05). Our results provide information on the current disease exposure and health status of wild boars in Croatia and suggest that wild boars may act as a reservoir for several pathogens and a source of infection for domestic pigs and other livestock as well as humans, especially for ADV.     

Hantavirus infections in fluctuating host populations: the role of maternal antibodies

Infected females may transfer maternal antibodies (MatAbs) to their offspring, which may then be transiently protected against infections the mother has encountered. However, the role of maternal protection in infectious disease dynamics in wildlife has largely been neglected. Here, we investigate the effects of Puumala hantavirus (PUUV)-specific MatAbs on PUUV dynamics, using 7 years'' data from a cyclic bank vole population in Finland. For the first time to our knowledge, we partition seropositivity data from a natural population into separate dynamic patterns for MatAbs and infection. The likelihood of young of the year carrying PUUV-specific MatAbs during the breeding season correlated positively with infection prevalence in the overwintered parent population in the preceding spring. The probability of PUUV infection varied between seasons (highest in spring, lowest in late summer) and depended on population structure, but was also, in late autumn, notably, negatively related to summer MatAb prevalence, as well as to infection prevalence earlier in the breeding season. Hence, our results suggest that high infection prevalence in the early breeding season leads to a high proportion of transiently immune young individuals, which causes delays in transmission. This suggests, in turn, that MatAb protection has the potential to affect infection dynamics in natural populations.     

A stochastic SIR model with contact-tracing: large population limits and statistical inference

This paper is devoted to the presentation and study of a specific stochastic epidemic model accounting for the effect of contact-tracing on the spread of an infectious disease. Precisely, one considers here the situation in which individuals identified as infected by the public health detection system may contribute to detecting other infectious individuals by providing information related to persons with whom they have had possibly infectious contacts. The control strategy, which consists of examining each individual who has been able to be identified on the basis of the information collected within a certain time period, is expected to efficiently reinforce the standard random-screening-based detection and considerably ease the epidemic. In the novel modelling of the spread of a communicable infectious disease considered here, the population of interest evolves through demographic, infection and detection processes, in a way that its temporal evolution is described by a stochastic Markov process, of which the component accounting for the contact-tracing feature is assumed to be valued in a space of point measures. For adequate scalings of the demographic, infection and detection rates, it is shown to converge to the weak deterministic solution of a PDE system, as a parameter n, interpreted as the population size, roughly speaking, becomes larger. From the perspective of the analysis of infectious disease data, this approximation result may serve as a key tool for exploring the asymptotic properties of standard inference methods such as maximum likelihood estimation. We state preliminary statistical results in this context. Eventually, relations of the model with the available data of the HIV epidemic in Cuba, in which country a contact-tracing detection system has been set up since 1986, is investigated and numerical applications are carried out.     

Detecting Presymptomatic Infection Is Necessary to Forecast Major Epidemics in the Earliest Stages of Infectious Disease Outbreaks

We assess how presymptomatic infection affects predictability of infectious disease epidemics. We focus on whether or not a major outbreak (i.e. an epidemic that will go on to infect a large number of individuals) can be predicted reliably soon after initial cases of disease have appeared within a population. For emerging epidemics, significant time and effort is spent recording symptomatic cases. Scientific attention has often focused on improving statistical methodologies to estimate disease transmission parameters from these data. Here we show that, even if symptomatic cases are recorded perfectly, and disease spread parameters are estimated exactly, it is impossible to estimate the probability of a major outbreak without ambiguity. Our results therefore provide an upper bound on the accuracy of forecasts of major outbreaks that are constructed using data on symptomatic cases alone. Accurate prediction of whether or not an epidemic will occur requires records of symptomatic individuals to be supplemented with data concerning the true infection status of apparently uninfected individuals. To forecast likely future behavior in the earliest stages of an emerging outbreak, it is therefore vital to develop and deploy accurate diagnostic tests that can determine whether asymptomatic individuals are actually uninfected, or instead are infected but just do not yet show detectable symptoms.     

Decentralized Opportunistic Spectrum Resources Access Model and Algorithm toward Cooperative Ad-Hoc Networks

Limited communication resources have gradually become a critical factor toward efficiency of decentralized large scale multi-agent coordination when both system scales up and tasks become more complex. In current researches, due to the agent’s limited communication and observational capability, an agent in a decentralized setting can only choose a part of channels to access, but cannot perceive or share global information. Each agent’s cooperative decision is based on the partial observation of the system state, and as such, uncertainty in the communication network is unavoidable. In this situation, it is a major challenge working out cooperative decision-making under uncertainty with only a partial observation of the environment. In this paper, we propose a decentralized approach that allows agents cooperatively search and independently choose channels. The key to our design is to build an up-to-date observation for each agent’s view so that a local decision model is achievable in a large scale team coordination. We simplify the Dec-POMDP model problem, and each agent can jointly work out its communication policy in order to improve its local decision utilities for the choice of communication resources. Finally, we discuss an implicate resource competition game, and show that, there exists an approximate resources access tradeoff balance between agents. Based on this discovery, the tradeoff between real-time decision-making and the efficiency of cooperation using these channels can be well improved.     

A General HIV Incidence Inference Scheme Based on Likelihood of Individual Level Data and a Population Renewal Equation

We derive a new method to estimate the age specific incidence of an infection with a differential mortality, using individual level infection status data from successive surveys. The method consists of a) an SI-type model to express the incidence rate in terms of the prevalence and its derivatives as well as the difference in mortality rate, and b) a maximum likelihood approach to estimate the prevalence and its derivatives. Estimates can in principle be obtained for any chosen age and time, and no particular assumptions are made about the epidemiological or demographic context. This is in contrast with earlier methods for estimating incidence from prevalence data, which work with aggregated data, and the aggregated effect of demographic and epidemiological rates over the time interval between prevalence surveys. Numerical simulation of HIV epidemics, under the presumption of known excess mortality due to infection, shows improved control of bias and variance, compared to previous methods. Our analysis motivates for a) effort to be applied to obtain accurate estimates of excess mortality rates as a function of age and time among HIV infected individuals and b) use of individual level rather than aggregated data in order to estimate HIV incidence rates at times between two prevalence surveys.     

Why genetic selection to reduce the prevalence of infectious diseases is way more promising than currently believed

Genetic selection for improved disease resistance is an important part of strategies to combat infectious diseases in agriculture. Quantitative genetic analyses of binary disease status, however, indicate low heritability for most diseases, which restricts the rate of genetic reduction in disease prevalence. Moreover, the common liability threshold model suggests that eradication of an infectious disease via genetic selection is impossible because the observed-scale heritability goes to zero when the prevalence approaches zero. From infectious disease epidemiology, however, we know that eradication of infectious diseases is possible, both in theory and practice, because of positive feedback mechanisms leading to the phenomenon known as herd immunity. The common quantitative genetic models, however, ignore these feedback mechanisms. Here, we integrate quantitative genetic analysis of binary disease status with epidemiological models of transmission, aiming to identify the potential response to selection for reducing the prevalence of endemic infectious diseases. The results show that typical heritability values of binary disease status correspond to a very substantial genetic variation in disease susceptibility among individuals. Moreover, our results show that eradication of infectious diseases by genetic selection is possible in principle. These findings strongly disagree with predictions based on common quantitative genetic models, which ignore the positive feedback effects that occur when reducing the transmission of infectious diseases. Those feedback effects are a specific kind of Indirect Genetic Effects; they contribute substantially to the response to selection and the development of herd immunity (i.e., an effective reproduction ratio less than one).     

Epizootiology of Brucella infection in Australian fur seals

Novel members of the bacterial genus Brucella have recently emerged as pathogens of various marine mammal species and as potential zoonotic agents. We investigated the epizootiology of Brucella infection in Australian fur seals (Arctocephalus pusillus doriferus) by establishing demographic and temporal variations in antibody prevalence, attempting isolation of the causative agent, and determining whether this potential pathogen is involved in frequent abortions observed in this pinniped species. Two competitive enzyme-linked immunosorbent assays (cELISAs), an indirect ELISA, and a fluorescence polarization assay (FPA) were used to test sera for Brucella antibodies. The FPA and cELISA proved suitable for use in this species. Significant differences in antibody prevalence were found between age classes of seals sampled between 2007 and 2009 at one colony. Pups sampled at this site (n=134) were negative for Brucella antibodies by all serologic tests but 17 of 45 (38%) of juveniles were antibody-positive. Antibody prevalence in adult females was significantly higher than in juveniles (P=0.044). Antibody prevalence for adult females between 2003 and 2009 varied significantly over time (P=0.011), and for individuals sampled between 2003 and 2005, the likelihood of pregnancy was greater in individuals positive for Brucella antibodies (P=0.034). Inflammatory lesions suggestive of infectious agents were found in 14 of 39 aborted Australian fur seal pups, but pathologic changes were not uniformly consistent for Brucella infection. Culture and PCR investigations on fetal tissues were negative for Brucella. Culture and PCR on selected fresh or frozen tissues from 36 juvenile and adult animals were also negative. We suspect that the prevalence of active infection with Brucella in Australian fur seals is low relative to antibody prevalence.