Role of environmental persistence in pathogen transmission: a mathematical modeling approach

Multiple endemic equilibria in an environmentally-transmitted disease with three disease stages

We construct, analyze and interpret a mathematical model for an environmental transmitted disease characterized for the existence of three disease stages: acute, severe and asymptomatic. Besides, we consider that severe and asymptomatic cases may present relapse between them. Transmission dynamics driven by the contact rates only occurs when a parameter R∗>1, as normally occur in directly-transmitted or vector-transmitted diseases, but it will not adequately correspond to a basic reproductive number as it depends on environmental parameters. In this case, the forward transcritical bifurcation that exists for R∗<1, becomes a backward bifurcation, producing multiple steady-states, a hysteresis effect and dependence on initial conditions. A threshold parameter for an epidemic outbreak, independent of R∗ is only the ratio of the external contamination inflow shedding rate to the environmental clearance rate. R∗ describes the strength of the transmission to infectious classes other than the I-(acute) type infections. The epidemic outbreak conditions and the structure of R∗ appearing in this model are both responsible for the existence of endemic states.

Modelling of tuberculosis dynamics incorporating indirect transmission of contaminated environment and infectivity of smear-negative individuals: A case study for Xinjiang, China

Xinjiang has been one of the high incidence areas of pulmonary tuberculosis (PTB) in China. Besides being infected by direct contacting with active PTB individuals (direct infection), the susceptible would be infected because of the exposure to the environment contaminated by Mycobacterium tuberculosis (indirect infection). Active PTB individuals include not only the smear-positive PTB (PTB+) but also the smear-negative PTB (PTB-) who are infectious due to their ability to release tiny Mycobacterium tuberculosis particles even in the absence of visible Mycobacterium tuberculosis in sputum. By taking account of direct/indirect infection and the difference between PTB+ and PTB- individuals in transmission capability, a periodic dynamical PTB transmission model is proposed. The model is fitted to the newly monthly PTB+ and PTB- cases in Xinjiang from 2008 to 2017 by Markov Chain Monte Carlo algorithm. Moreover, global sensitivity analysis is constructed to address the uncertainty of some key parameters by using Latin hypercube sampling and partial rank correlation coefficient methods. Basic reproduction number R0 for PTB transmission in Xinjiang is estimated to be 2.447 (95% CrI:(1.203, 3.844)), indicating that PTB has been prevalent in Xinjiang over the study period. Our results suggest that reducing the direct/indirect transmission rates, early screening, isolating and treating the latent, PTB+ and PTB- individuals, and enhancing the clearance of Mycobacterium tuberculosis in the environment could more effectively control PTB transmission in Xinjiang. The model fits the reported PTB data well and achieves acceptable prediction accuracy. We believe that our model can provide heuristic support for controlling PTB transmission in Xinjiang.

A novel method to jointly estimate transmission rate and decay rate parameters in environmental transmission models

In environmental transmission, pathogens transfer from one individual to another via the environment. It is a common transmission mechanism in a wide range of host-pathogen systems. Incorporating environmental transmission in dynamic transmission models is crucial for gauging the effect of interventions, as extrapolating model results to new situations is only valid when the mechanisms are modelled correctly. The challenge in environmental transmission models lies in not jointly identifiable parameters for pathogen shedding, decay, and transmission dynamics. To solve this unidentifiability issue, we present a stochastic environmental transmission model with a novel scaling method for shedding rate parameter and a novel estimation method that distinguishes transmission rate and decay rate parameters. The core of our scaling and estimation method is calculating exposure and relating exposure to infection risks. By scaling shedding rate parameter, we standardize exposure to pathogens contributed by one infectious individual present during one time interval to one. The standardized exposure leads to a standard definition of transmission rate parameter applicable to scenarios with different decay rate parameters. Hence, we unify direct transmission (large decay rate) and environmental transmission in a continuous manner. More importantly, our exposure-based estimation method can correctly estimate back the transmission rate and the decay rate parameters, while the commonly used trajectory-based method failed. The reason is that exposure-based method gives the correct weight to infection data from previous observation periods. The correct estimation from exposure-based method will lead to more reliable predictions of intervention impact. Using the effect of disinfection as an example, we show how incorrectly estimated parameters may lead to incorrect conclusions about the effectiveness of interventions. This illustrates the importance of correct estimation of transmission rate and decay rate parameters for extrapolating environmental transmission models and predicting intervention effects.

The transmission mechanism theory of disease dynamics: Its aims, assumptions and limitations

Most of the progress in the development of single scale mathematical and computational models for the study of infectious disease dynamics which now span over a century is build on a body of knowledge that has been developed to address particular single scale descriptions of infectious disease dynamics based on understanding disease transmission process. Although this single scale understanding of infectious disease dynamics is now founded on a body of knowledge with a long history, dating back to over a century now, that knowledge has not yet been formalized into a scientific theory. In this article, we formalize this accumulated body of knowledge into a scientific theory called the transmission mechanism theory of disease dynamics which states that at every scale of organization of an infectious disease system, disease dynamics is determined by transmission as the main dynamic disease process. Therefore, the transmission mechanism theory of disease dynamics can be seen as formalizing knowledge that has been inherent in the study of infectious disease dynamics using single scale mathematical and computational models for over a century now. The objective of this article is to summarize this existing knowledge about single scale modelling of infectious dynamics by means of a scientific theory called the transmission mechanism theory of disease dynamics and highlight its aims, assumptions and limitations.

Dilution of Epidemic Potential of Environmentally Transmitted Infectious Diseases for Species with Partially Overlapping Habitats

AbstractSpecies diversity may play an important role in the modulation of pathogen transmission through the dilution effect. Infectious disease models can help elucidate mechanisms that may underlie this effect. While many modeling studies have assumed direct host-to-host transmission, many pathogens are transmitted through the environment. We present a mathematical modeling analysis exploring conditions under which we observe the dilution effect in systems with environmental transmission where host species interact through fully or partially overlapping habitats. We measure the strength of the dilution effect by the relative decrease in the basic reproduction number of two-species assemblages compared with that of a focal host species. We find that a dilution effect is most likely when the pathogen is environmentally persistent (frequency-dependent-like transmission). The magnitude of this effect is strongest when the species with the greater epidemic potential is relatively slow to pick up pathogens in the environment (density-dependent transmission) and the species with the lesser epidemic potential is efficient at picking up pathogens (frequency-dependent transmission). These findings suggest that measurable factors, including pathogen persistence and the host's relative efficiency of pathogen pickup, can guide predictions of when biodiversity might lead to a dilution effect and may thus give concrete direction to future ecological work.

Environmental suitability of bare-nosed wombat burrows for Sarcoptes scabiei

Some of the most important pathogens affecting wildlife are transmitted indirectly via the environment. Yet the environmental stages of pathogens are often poorly understood, relative to infection in the host, making this an important research frontier. Sarcoptic mange is a globally widespread disease caused by the parasitic mite Sarcoptes scabiei. The bare-nosed wombat (Vombatus ursinus) is particularly susceptible, and their solitary nature and overlapping use of burrows strongly indicate the importance of environmental transmission. However, due to the challenge of accessing and monitoring within wombat burrows, there has been limited research into their suitability for off-host mite survival and environmental transmission (i.e., to serve as a fomite). We created a model using published laboratory data to predict mite survival times based on temperature and humidity. We then implemented innovative technologies (ground-penetrating radar and a tele-operated robotic vehicle) to map and access wombat burrows to record temperature and relative humidity. We found that the stable conditions within burrows were conducive for off-host survival of S. scabiei, particularly in winter (estimated mite survival of 16.41 ± 0.34 days) and less so in warmer and drier months (summer estimated survival of 5.96 ± 0.37 days). We also compared two areas with higher and lower average mange prevalence in wombats (13.35% and 4.65%, respectively), finding estimated mite survival was slightly higher in the low prevalence area (10.10 and 12.12 days, respectively), contrary to our expectations, suggesting other factors are also important for population prevalence. Our study is the first to demonstrate the suitability of the bare-nosed wombat burrow for off-host mite survival and environmental transmission. Our findings have implications for understanding observed patterns of mange, disease dynamics and disease management for not only bare-nosed wombats, but also other burrow or den-obligate species exposed to S. scabiei via environmental transmission.

•

Wombat burrows are a source of environmental transmission of Sarcoptes scabiei.

•

We used ground-penetrating radar and a robotic vehicle to measure burrow conditions.

•

We estimate S. scabiei can survive 5.96–16.41 days within burrows depending on season.

•

Seasonal variation in environmental survival may influence disease dynamics in wombats.

Inferring environmental transmission using phylodynamics: a case-study using simulated evolution of an enteric pathogen

Indirect (environmental) and direct (host-host) transmission pathways cannot easily be distinguished when they co-occur in epidemics, particularly when they occur on similar time scales. Phylodynamic reconstruction is a potential approach to this problem that combines epidemiological information (temporal, spatial information) with pathogen whole-genome sequencing data to infer transmission trees of epidemics. However, factors such as differences in mutation and transmission rates between host and non-host environments may obscure phylogenetic inference from these methods. In this study, we used a network-based transmission model that explicitly models pathogen evolution to simulate epidemics with both direct and indirect transmission. Epidemics were simulated according to factorial combinations of direct/indirect transmission proportions, host mutation rates and conditions of environmental pathogen growth. Transmission trees were then reconstructed using the phylodynamic approach SCOTTI (structured coalescent transmission tree inference) and evaluated. We found that although insufficient diversity sets a lower bound on when accurate phylodynamic inferences can be made, transmission routes and assumed pathogen lifestyle affected pathogen population structure and subsequently influenced both reconstruction success and the likelihood of direct versus indirect pathways being reconstructed. We conclude that prior knowledge of the likely ecology and population structure of pathogens in host and non-host environments is critical to fully using phylodynamic techniques.

Soil Reservoir Dynamics of Ophidiomyces ophidiicola, the Causative Agent of Snake Fungal Disease

Wildlife diseases pose an ever-growing threat to global biodiversity. Understanding how wildlife pathogens are distributed in the environment and the ability of pathogens to form environmental reservoirs is critical to understanding and predicting disease dynamics within host populations. Snake fungal disease (SFD) is an emerging conservation threat to North American snake populations. The causative agent, Ophidiomyces ophidiicola (Oo), is detectable in environmentally derived soils. However, little is known about the distribution of Oo in the environment and the persistence and growth of Oo in soils. Here, we use quantitative PCR to detect Oo in soil samples collected from five snake dens. We compare the detection rates between soils collected from within underground snake hibernacula and associated, adjacent topsoil samples. Additionally, we used microcosm growth assays to assess the growth of Oo in soils and investigate whether the detection and growth of Oo are related to abiotic parameters and microbial communities of soil samples. We found that Oo is significantly more likely to be detected in hibernaculum soils compared to topsoils. We also found that Oo was capable of growth in sterile soil, but no growth occurred in soils with an active microbial community. A number of fungal genera were more abundant in soils that did not permit growth of Oo, versus those that did. Our results suggest that soils may display a high degree of both general and specific suppression of Oo in the environment. Harnessing environmental suppression presents opportunities to mitigate the impacts of SFD in wild snake populations.

The roles of environmental variation and parasite survival in virulence-transmission relationships

Disease outbreaks are a consequence of interactions among the three components of a host-parasite system: the infectious agent, the host and the environment. While virulence and transmission are widely investigated, most studies of parasite life-history trade-offs are conducted with theoretical models or tractable experimental systems where transmission is standardized and the environment controlled. Yet, biotic and abiotic environmental factors can strongly affect disease dynamics, and ultimately, host-parasite coevolution. Here, we review research on how environmental context alters virulence-transmission relationships, focusing on the off-host portion of the parasite life cycle, and how variation in parasite survival affects the evolution of virulence and transmission. We review three inter-related 'approaches' that have dominated the study of the evolution of virulence and transmission for different host-parasite systems: (i) evolutionary trade-off theory, (ii) parasite local adaptation and (iii) parasite phylodynamics. These approaches consider the role of the environment in virulence and transmission evolution from different angles, which entail different advantages and potential biases. We suggest improvements to how to investigate virulence-transmission relationships, through conceptual and methodological developments and taking environmental context into consideration. By combining developments in life-history evolution, phylogenetics, adaptive dynamics and comparative genomics, we can improve our understanding of virulence-transmission relationships across a diversity of host-parasite systems that have eluded experimental study of parasite life history.

Variation in microparasite free-living survival and indirect transmission can modulate the intensity of emerging outbreaks

Variation in free-living microparasite survival can have a meaningful impact on the ecological dynamics of established and emerging infectious diseases. Nevertheless, resolving the importance of indirect and environmental transmission in the ecology of epidemics remains a persistent challenge. It requires accurately measuring the free-living survival of pathogens across reservoirs of various kinds and quantifying the extent to which interaction between hosts and reservoirs generates new infections. These questions are especially salient for emerging pathogens, where sparse and noisy data can obfuscate the relative contribution of different infection routes. In this study, we develop a mechanistic, mathematical model that permits both direct (host-to-host) and indirect (environmental) transmission and then fit this model to empirical data from 17 countries affected by an emerging virus (SARS-CoV-2). From an ecological perspective, our model highlights the potential for environmental transmission to drive complex, nonlinear dynamics during infectious disease outbreaks. Summarizing, we propose that fitting alternative models with indirect transmission to real outbreak data from SARS-CoV-2 can be useful, as it highlights that indirect mechanisms may play an underappreciated role in the dynamics of infectious diseases, with implications for public health.

Variation in SARS-CoV-2 free-living survival and environmental transmission can modulate the intensity of emerging outbreaks

Variation in free-living, microparasite survival can have a meaningful impact on the ecological dynamics of established and emerging infectious diseases. Nevertheless, resolving the importance of environmental transmission in the ecology of epidemics remains a persistent challenge, requires accurate measuring the free-living survival of pathogens across reservoirs of various kinds, and quantifying the extent to which interaction between hosts and reservoirs generates new infections. These questions are especially salient for emerging pathogens, where sparse and noisy data can obfuscate the relative contribution of different infection routes. In this study, we develop a mechanistic, mathematical model that permits both direct (host-to-host) and indirect (environmental) transmission and then fit this model to empirical data from 17 countries affected by an emerging virus (SARS-CoV-2). From an ecological perspective, our model highlights the potential for environmental transmission to drive complex, non-linear dynamics during infectious disease outbreaks. Summarizing, we propose that fitting such models with environmental transmission to real outbreak data from SARS-CoV-2 transmission highlights that variation in environmental transmission is an underappreciated aspect of the ecology of infectious disease, and an incomplete understanding of its role has consequences for public health interventions.

Ecological drivers of African swine fever virus persistence in wild boar populations: Insight for control

Environmental sources of infection can play a primary role in shaping epidemiological dynamics; however, the relative impact of environmental transmission on host-pathogen systems is rarely estimated. We developed and fit a spatially explicit model of African swine fever virus (ASFV) in wild boar to estimate what proportion of carcass-based transmission is contributing to the low-level persistence of ASFV in Eastern European wild boar. Our model was developed based on ecological insight and data from field studies of ASFV and wild boar in Eastern Poland. We predicted that carcass-based transmission would play a substantial role in persistence, especially in low-density host populations where contact rates are low. By fitting the model to outbreak data using approximate Bayesian computation, we inferred that between 53% and 66% of transmission events were carcass-based that is, transmitted through contact of a live host with a contaminated carcass. Model fitting and sensitivity analyses showed that the frequency of carcass-based transmission increased with decreasing host density, suggesting that management policies should emphasize the removal of carcasses and consider how reductions in host densities may drive carcass-based transmission. Sensitivity analyses also demonstrated that carcass-based transmission is necessary for the autonomous persistence of ASFV under realistic parameters. Autonomous persistence through direct transmission alone required high host densities; otherwise re-introduction of virus periodically was required for persistence when direct transmission probabilities were moderately high. We quantify the relative role of different persistence mechanisms for a low-prevalence disease using readily collected ecological data and viral surveillance data. Understanding how the frequency of different transmission mechanisms vary across host densities can help identify optimal management strategies across changing ecological conditions.

On modelling environmentally transmitted pathogens

Many pathogens are able to replicate or survive in abiotic environments. Disease transmission models that include environmental reservoirs and environment-to-host transmission have used a variety of functional forms and modelling frameworks without a clear connection to pathogen ecology or space and time scales. We present a conceptual framework to organize microparasites based on the role that abiotic environments play in their lifecycle. Mean-field and individual-based models for environmental transmission are analysed and compared. We show considerable divergence between both modelling approaches when conditions do not facilitate well mixing and for pathogens with fast dynamics in the environment. We conclude with recommendations for modelling environmentally transmitted pathogens based on the pathogen lifecycle and time and spatial scales of the host-pathogen system under consideration.

A general method for multiscale modelling of vector-borne disease systems

The inability to develop multiscale models which can describe vector-borne disease systems in terms of the complete pathogen life cycle which represents multiple targets for control has hindered progress in our efforts to control, eliminate and even eradicate these multi-host infections. This is because it is currently not easy to determine precisely where and how in the life cycles of vector-borne disease systems the key constrains which are regarded as crucial in regulating pathogen population dynamics in both the vertebrate host and vector host operate. In this article, we present a general method for development of multiscale models of vector-borne disease systems which integrate the within-host and between-host scales for the two hosts (a vertebrate host and a vector host) that are implicated in vector-borne disease dynamics. The general multiscale modelling method is an extension of our previous work on multiscale models of infectious disease systems which established a basic science and accompanying theory of how pathogen population dynamics at within-host scale scales up to between-host scale and in turn how it scales down from between-host scale to within-host scale. Further, the general method is applied to multiscale modelling of human onchocerciasis-a vector-borne disease system which is sometimes called river blindness as a case study.

The Replication-Transmission Relativity Theory for Multiscale Modelling of Infectious Disease Systems

It is our contention that for multiscale modelling of infectious disease systems to evolve and expand in scope, it needs to be founded on a theory. Such a theory would improve our ability to describe infectious disease systems in terms of their scales and levels of organization, and their inter-relationships. In this article we present a relativistic theory for multiscale modelling of infectious disease systems, that can be considered as an extension of the relativity principle in physics, called the replication-transmission relativity theory. This replication-transmission relativity theory states that at any level of organization of an infectious disease system there is no privileged/absolute scale which would determine, disease dynamics, only interactions between the microscale and macroscale. Such a relativistic theory provides a scientific basis for a systems level description of infectious disease systems using multiscale modelling methods. The central idea of this relativistic theory is that at every level of organization of an infectious disease system, the reciprocal influence between the microscale and the macroscale establishes a pathogen replication-transmission multiscale cycle. We distinguish two kinds of reciprocal influence between the microscale and the macroscale based on systematic differences in their conditions of relevancy. Evidence for the validity of the replication-transmission relativity theory is presented using a multiscale model of hookworm infection that is developed at host level when the relationship between the microscale and the macroscale is described by one of the forms of reciprocal influence.

Hepatitis C virus modelled as an indirectly transmitted infection highlights the centrality of injection drug equipment in disease dynamics

The hepatitis C virus (HCV) epidemic often occurs through the persistence of injection drug use. Mathematical models have been useful in understanding various aspects of the HCV epidemic, and especially, the importance of new treatment measures. Until now, however, few models have attempted to understand HCV in terms of an interaction between the various actors in an HCV outbreak-hosts, viruses and the needle injection equipment. In this study, we apply perspectives from the ecology of infectious diseases to model the transmission of HCV among a population of injection drug users. The products of our model suggest that modelling HCV as an indirectly transmitted infection-where the injection equipment serves as an environmental reservoir for infection-facilitates a more nuanced understanding of disease dynamics, by animating the underappreciated actors and interactions that frame disease. This lens may allow us to understand how certain public health interventions (e.g. needle exchange programmes) influence HCV epidemics. Lastly, we argue that this model is of particular importance in the light of the modern opioid epidemic, which has already been associated with outbreaks of viral diseases.

Metapopulation Model from Pathogen's Perspective: A Versatile Framework to Quantify Pathogen Transfer and Circulation between Environment and Hosts

Metapopulation models have been primarily explored in infectious disease epidemiology to study host subpopulation movements and between-host contact structures. They also have the potential to investigate environmental pathogen transferring. In this study, we demonstrate that metapopulation models serve as an ideal modeling framework to characterize and quantify pathogen transfer between environment and hosts. It therefore unifies host, pathogen, and environment, collectively known as the epidemiological triad, a fundamental concept in epidemiology. We develop a customizable and generalized pathogen-transferring model where pathogens dwell in and transferring (via contact) between environment and hosts. We analyze three specific case studies: pure pathogen transferring without pathogen demography, source-sink dynamics, and pathogen control via external disinfection. We demonstrate how pathogens circulate in the system between environment and hosts, as well as evaluate different controlling efforts for healthcare-associated infections (HAIs). For pure pathogen transferring, system equilibria can be derived analytically to explicitly quantify long-term pathogen distribution in the system. For source-sink dynamics and pathogen control via disinfection, we demonstrate that complete eradication of pathogens can be achieved, but the rates of converging to system equilibria differ based on specific model parameterization. Direct host-host pathogen transferring and within-host dynamics can be future directions of this modeling framework by adding specific modules.

Microbial Exchange via Fomites and Implications for Human Health

PURPOSE OF REVIEW

Fomites are inanimate objects that become colonized with microbes and serve as potential intermediaries for transmission to/from humans. This review summarizes recent literature on fomite contamination and microbial survival in the built environment, transmission between fomites and humans, and implications for human health.

RECENT FINDINGS

Applications of molecular sequencing techniques to analyze microbial samples have increased our understanding of the microbial diversity that exists in the built environment. This growing body of research has established that microbial communities on surfaces include substantial diversity, with considerable dynamics. While many microbial taxa likely die or lay dormant, some organisms survive, including those that are potentially beneficial, benign, or pathogenic. Surface characteristics also influence microbial survival and rates of transfer to and from humans. Recent research has combined experimental data, mechanistic modeling, and epidemiological approaches to shed light on the likely contributors to microbial exchange between fomites and humans and their contributions to adverse (and even potentially beneficial) human health outcomes.

SUMMARY

In addition to concerns for fomite transmission of potential pathogens, new analytical tools have uncovered other microbial matters that can be transmitted indirectly via fomites, including entire microbial communities and antibiotic-resistant bacteria. Mathematical models and epidemiological approaches can provide insight on human health implications. However, both are subject to limitations associated with study design, and there is a need to better understand appropriate input model parameters. Fomites remain an important mechanism of transmission of many microbes, along with direct contact and short- and long-range aerosols.

Pathogen transfer through environment-host contact: an agent-based queueing theoretic framework

Queueing theory studies the properties of waiting queues and has been applied to investigate direct host-to-host transmitted disease dynamics, but its potential in modelling environmentally transmitted pathogens has not been fully explored. In this study, we provide a flexible and customizable queueing theory modelling framework with three major subroutines to study the in-hospital contact processes between environments and hosts and potential nosocomial pathogen transfer, where environments are servers and hosts are customers. Two types of servers with different parameters but the same utilization are investigated. We consider various forms of transfer functions that map contact duration to the amount of pathogen transfer based on existing literature. We propose a case study of simulated in-hospital contact processes and apply stochastic queues to analyse the amount of pathogen transfer under different transfer functions, and assume that pathogen amount decreases during the inter-arrival time. Different host behaviour (feedback and non-feedback) as well as initial pathogen distribution (whether in environment and/or in hosts) are also considered and simulated. We assess pathogen transfer and circulation under these various conditions and highlight the importance of the nonlinear interactions among contact processes, transfer functions and pathogen demography during the contact process. Our modelling framework can be readily extended to more complicated queueing networks to simulate more realistic situations by adjusting parameters such as the number and type of servers and customers, and adding extra subroutines.

Experimental evidence of a pathogen invasion threshold

Host density thresholds to pathogen invasion separate regions of parameter space corresponding to endemic and disease-free states. The host density threshold is a central concept in theoretical epidemiology and a common target of human and wildlife disease control programmes, but there is mixed evidence supporting the existence of thresholds, especially in wildlife populations or for pathogens with complex transmission modes (e.g. environmental transmission). Here, we demonstrate the existence of a host density threshold for an environmentally transmitted pathogen by combining an epidemiological model with a microcosm experiment. Experimental epidemics consisted of replicate populations of naive crustacean zooplankton (Daphnia dentifera) hosts across a range of host densities (20-640 hosts l-1) that were exposed to an environmentally transmitted fungal pathogen (Metschnikowia bicuspidata). Epidemiological model simulations, parametrized independently of the experiment, qualitatively predicted experimental pathogen invasion thresholds. Variability in parameter estimates did not strongly influence outcomes, though systematic changes to key parameters have the potential to shift pathogen invasion thresholds. In summary, we provide one of the first clear experimental demonstrations of pathogen invasion thresholds in a replicated experimental system, and provide evidence that such thresholds may be predictable using independently constructed epidemiological models.

Bacterial Lipopolysaccharide Destabilizes Influenza Viruses

Depending on the specific viral pathogen, commensal bacteria can promote or reduce the severity of viral infection and disease progression in their hosts. Influenza A virus (IAV) has a broad host range, comprises many subtypes, and utilizes different routes of transmission, including the fecal-oral route in wild birds. It has been previously demonstrated that commensal bacteria can interact with the host's immune system to protect against IAV pathogenesis. However, it is unclear whether bacteria and their products may be interacting directly with IAV to impact virion stability. Herein we show that gastrointestinal (GI) tract bacterial isolates in an in vitro system significantly reduce the stability of IAV. Moreover, bacterial lipopolysaccharide (LPS), found on the exterior surfaces of bacteria, was sufficient to significantly decrease the stability of both human and avian viral strains in a temperature-dependent manner, including at the relevant temperatures of their respective hosts and the external aquatic habitat. The subtype and host origin of the viruses were shown to affect the extent to which IAV was susceptible to LPS. Furthermore, using a receptor binding assay and transmission electron microscopy, we observed that LPS binds to and alters the morphology of influenza virions, suggesting that direct interaction with the viral surface contributes to the observed antiviral effect of LPS on influenza. IMPORTANCE Influenza A virus (IAV), transmitted primarily via the fecal-oral route in wild birds, encounters high concentrations of bacteria and their products. Understanding the extent to which bacteria affect the infectivity of IAV will lead to a broader understanding of viral ecology in reservoir hosts and may lead to insights for the development of therapeutics in respiratory infection. Herein we show that bacteria and lipopolysaccharide (LPS) interact with and destabilize influenza virions. Moreover, we show that LPS reduces the long-term persistence and freeze-thaw stability of IAV, which is important information for modeling the movement and emergence of novel strains from animal hosts. Our results, demonstrating that the subtype and host origin of a virus also influence its susceptibility to LPS, raise key questions about the fitness of viruses in reservoir hosts, their potential to transmit to humans, and the importance of bacterial-viral interactions in viral ecology.

Modeling environmental transmission of MAP infection in dairy cows

Johne's disease is caused by Mycobacterium avium subspecies paratuberculosis(MAP). It is a chronic, progressive, and inflammatory disease which has a long incubation period. One main problem with the disease is the reduction of milk production in infected dairy cows. In our study we develop a system of ordinary differential equations to describe the dynamics of MAP infection in a dairy farm. This model includes the progression of the disease and the age structure of the cows. To investigate the effect of persistence of this bacteria on the farm on transmission in our model, we include environmental compartments, representing the pathogen input in an explicit way. The effect of indirect transmission from the bacteria in the environment and the culling of high-shedding adults can be seen in the numerical simulations. Since culling usually only happens once a year, we include a novel feature in the simulations with a discrete action of removing high-shedding adults once a year. We conclude that with culling of high shedders even at a high rate, the infection will persist in the modeled farm setting.

The Use of Chemoprophylaxis after Floods to Reduce the Occurrence and Impact of Leptospirosis Outbreaks

Record-breaking and devastating rainfall events have occurred in the past decade. Rain and floods are considered the main risk factors for leptospirosis and several outbreaks have been reported following extreme weather events. In such situations, one possible intervention to prevent leptospirosis cases in high-risk groups is the use of chemoprophylaxis. However, not enough evidence of its effect is available. The objectives of this study were to review the literature on the current practices of chemoprophylaxis for leptospirosis and to explore, using a mathematical model, how various chemoprophylaxis scenarios may affect the progression of a leptospirosis outbreak. Twenty-six peer-reviewed publications were selected (10 quantitative studies, two systematic reviews and 14 articles of other types). Oral doxycycline was the most used antibiotic for chemoprophylaxis of leptospirosis. Post-exposure prophylaxis was assessed in four studies following a natural disaster. Although evidence of the effectiveness of post-exposure prophylaxis is inconsistent, the direction of association supported a protective effect for morbidity and mortality. The theoretical model showed how the assumed benefit of chemoprophylaxis was influenced by the time and rate of administration. Future models should consider the heterogeneity of affected communities, improved estimates of the effect of chemoprophylaxis on leptospirosis infection and disease, as well as potential detrimental impacts. Additional research is critical to provide clear evidence-based recommendations for leptospirosis control during an outbreak. The results of this study suggest that chemoprophylaxis may provide some protection in reducing the number of leptospirosis cases after a high-risk exposure; however, the effective benefit may depend on a variety of factors such as the timing and coverage of prophylaxis. The information summarized can be used to support decision-making during a high-risk event.

Dose-response relationships for environmentally mediated infectious disease transmission models

Environmentally mediated infectious disease transmission models provide a mechanistic approach to examining environmental interventions for outbreaks, such as water treatment or surface decontamination. The shift from the classical SIR framework to one incorporating the environment requires codifying the relationship between exposure to environmental pathogens and infection, i.e. the dose-response relationship. Much of the work characterizing the functional forms of dose-response relationships has used statistical fit to experimental data. However, there has been little research examining the consequences of the choice of functional form in the context of transmission dynamics. To this end, we identify four properties of dose-response functions that should be considered when selecting a functional form: low-dose linearity, scalability, concavity, and whether it is a single-hit model. We find that i) middle- and high-dose data do not constrain the low-dose response, and different dose-response forms that are equally plausible given the data can lead to significant differences in simulated outbreak dynamics; ii) the choice of how to aggregate continuous exposure into discrete doses can impact the modeled force of infection; iii) low-dose linear, concave functions allow the basic reproduction number to control global dynamics; and iv) identifiability analysis offers a way to manage multiple sources of uncertainty and leverage environmental monitoring to make inference about infectivity. By applying an environmentally mediated infectious disease model to the 1993 Milwaukee Cryptosporidium outbreak, we demonstrate that environmental monitoring allows for inference regarding the infectivity of the pathogen and thus improves our ability to identify outbreak characteristics such as pathogen strain.

Environmental Persistence Influences Infection Dynamics for a Butterfly Pathogen

Many pathogens, including those infecting insects, are transmitted via dormant stages shed into the environment, where they must persist until encountering a susceptible host. Understanding how abiotic conditions influence environmental persistence and how these factors influence pathogen spread are crucial for predicting patterns of infection risk. Here, we explored the consequences of environmental transmission for infection dynamics of a debilitating protozoan parasite (Ophryocystis elektroscirrha) that infects monarch butterflies (Danaus plexippus). We first conducted an experiment to observe the persistence of protozoan spores exposed to natural conditions. Experimental results showed that, contrary to our expectations, pathogen doses maintained high infectivity even after 16 days in the environment, although pathogens did yield infections with lower parasite loads after environmental exposure. Because pathogen longevity exceeded the time span of our experiment, we developed a mechanistic model to better explore environmental persistence for this host-pathogen system. Model analysis showed that, in general, longer spore persistence led to higher infection prevalence and slightly smaller monarch population sizes. The model indicated that typical parasite doses shed onto milkweed plants must remain viable for a minimum of 3 weeks for prevalence to increase during the summer-breeding season, and for 11 weeks or longer to match levels of infection commonly reported from the wild, assuming moderate values for parasite shedding rate. Our findings showed that transmission stages of this butterfly pathogen are long-lived and indicated that this is a necessary condition for the protozoan to persist in local monarch populations. This study provides a modeling framework for future work examining the dynamics of an ecologically important pathogen in an iconic insect.

Relevance of Indirect Transmission for Wildlife Disease Surveillance

Epidemiological models of infectious diseases are essential tools in support of risk assessment, surveillance design, and contingency planning in public and animal health. Direct pathogen transmission from host to host is an essential process of each host–pathogen system and respective epidemiological modeling concepts. It is widely accepted that numerous diseases involve indirect transmission (IT) through pathogens shed by infectious hosts to their environment. However, epidemiological models largely do not represent pathogen persistence outside the host explicitly. We hypothesize that this simplification might bias management-related model predictions for disease agents that can persist outside their host for a certain time span. We adapted an individual-based, spatially explicit epidemiological model that can mimic both transmission processes. One version explicitly simulated indirect pathogen transmission through a contaminated environment. The second version simulated direct host-to-host transmission only. We aligned the model variants by the transmission potential per infectious host (i.e., basic reproductive number R₀) and the spatial transmission kernel of the infection to allow unbiased comparison of predictions. The quantitative model results are provided for the example of surveillance plans for early detection of foot-and-mouth disease in wild boar, a social host. We applied systematic sampling strategies on the serological status of randomly selected host individuals in both models. We compared between the model variants the time to detection and the area affected prior to detection, measures that strongly influence mitigation costs. Moreover, the ideal sampling strategy to detect the infection in a given time frame was compared between both models. We found the simplified, direct transmission model to underestimate necessary sample size by up to one order of magnitude but to overestimate the area put under control measures. Thus, the model predictions underestimated surveillance efforts but overestimated mitigation costs. We discuss parameterization of IT models and related knowledge gaps. We conclude that the explicit incorporation of IT mechanisms in epidemiological modeling may reward by adapting surveillance and mitigation efforts.

Impact of the shedding level on transmission of persistent infections in Mycobacterium avium subspecies paratuberculosis (MAP)

Super-shedders are infectious individuals that contribute a disproportionate amount of infectious pathogen load to the environment. A super-shedder host may produce up to 10,000 times more pathogens than other infectious hosts. Super-shedders have been reported for multiple human and animal diseases. If their contribution to infection dynamics was linear to the pathogen load, they would dominate infection dynamics. We here focus on quantifying the effect of super-shedders on the spread of infection in natural environments to test if such an effect actually occurs in Mycobacterium avium subspecies paratuberculosis (MAP). We study a case where the infection dynamics and the bacterial load shed by each host at every point in time are known. Using a maximum likelihood approach, we estimate the parameters of a model with multiple transmission routes, including direct contact, indirect contact and a background infection risk. We use longitudinal data from persistent infections (MAP), where infectious individuals have a wide distribution of infectious loads, ranging upward of three orders of magnitude. We show based on these parameters that the effect of super-shedders for MAP is limited and that the effect of the individual bacterial load is limited and the relationship between bacterial load and the infectiousness is highly concave. A 1000-fold increase in the bacterial contribution is equivalent to up to a 2-3 fold increase in infectiousness.

Aggregation and environmental transmission in Chronic Wasting Disease

Disease transmission depends on the interplay between the infectious agent and the behavior of the host. Some diseases, such as Chronic Wasting Disease, can be transmitted directly between hosts as well as indirectly via the environment. The social behavior of hosts affects both of these pathways, and a successful intervention requires knowledge of the relative influence of the different etiological and behavioral aspects of the disease. We develop a strategic differential equation model for Chronic Wasting Disease and include direct and indirect transmission as well as host aggregation into our model. We calculate the basic reproduction number and perform a sensitivity analysis based on Latin hypercube sampling from published parameter values. We find conditions for the existence of an endemic equilibrium, and show that, under a certain mild assumption on parameters, the model does not exhibit a backward bifurcation or bistability. Hence, the basic reproduction number constitutes the disease elimination threshold. We find that the prevalence of the disease decreases with host aggregation and increases with the lifespan of the infectious agent in the environment.

Household Transmission of Vibrio cholerae in Bangladesh

Background

Vibrio cholerae infections cluster in households. This study's objective was to quantify the relative contribution of direct, within-household exposure (for example, via contamination of household food, water, or surfaces) to endemic cholera transmission. Quantifying the relative contribution of direct exposure is important for planning effective prevention and control measures.

Methodology/Principal Findings

Symptom histories and multiple blood and fecal specimens were prospectively collected from household members of hospital-ascertained cholera cases in Bangladesh from 2001–2006. We estimated the probabilities of cholera transmission through 1) direct exposure within the household and 2) contact with community-based sources of infection. The natural history of cholera infection and covariate effects on transmission were considered. Significant direct transmission (p-value<0.0001) occurred among 1414 members of 364 households. Fecal shedding of O1 El Tor Ogawa was associated with a 4.9% (95% confidence interval: 0.9%–22.8%) risk of infection among household contacts through direct exposure during an 11-day infectious period (mean length). The estimated 11-day risk of O1 El Tor Ogawa infection through exposure to community-based sources was 2.5% (0.8%–8.0%). The corresponding estimated risks for O1 El Tor Inaba and O139 infection were 3.7% (0.7%–16.6%) and 8.2% (2.1%–27.1%) through direct exposure, and 3.4% (1.7%–6.7%) and 2.0% (0.5%–7.3%) through community-based exposure. Children under 5 years-old were at elevated risk of infection. Limitations of the study may have led to an underestimation of the true risk of cholera infection. For instance, available covariate data may have incompletely characterized levels of pre-existing immunity to cholera infection. Transmission via direct exposure occurring outside of the household was not considered.

Conclusions

Direct exposure contributes substantially to endemic transmission of symptomatic cholera in an urban setting. We provide the first estimate of the transmissibility of endemic cholera within prospectively-followed members of households. The role of direct transmission must be considered when planning cholera control activities.

Since John Snow's ground-breaking investigations of the devastating outbreaks in 19^th-century London, cholera has been considered the quintessential waterborne human infection, transmitting via fecal contamination of environmental water sources. Recently, renewed interest has been paid to the potential importance of transmission through direct exposure within close-contact groups, such as, via fecal contamination of surfaces, food, or drinking water within households. Significant direct transmission of cholera within close contact groups would represent a new target for innovative prevention and control strategies. We estimated the probability of transmission 1) via direct contact within 364 urban households located in an endemic cholera setting (Dhaka, Bangladesh) and 2) via exposure to sources located outside of these households. In this setting we estimated a 4 to 8 percent probability of becoming infected with cholera via direct exposure within households in this setting versus a 2 to 3 percent likelihood of infection due to exposure to external sources over a comparable time period. Our results demonstrate that direct (within-household) transmission is a significant component of endemic cholera transmission, suggesting that biomedical and behavioral-modification interventions specifically targeting this mode of transmission could substantially reduce the cholera burden in this type of setting.

From the bench to modeling--R0 at the interface between empirical and theoretical approaches in epidemiology of environmentally transmitted infectious diseases

For environmentally transmitted infectious diseases (ETIDs), which spread through the contaminated environment (such as foods, surfaces and fomites), there is a lack of consensus about the mathematical approach to derive R0, leading to inconsistent predictions about the spread and control of these infections in their host populations. The objective of this study was to explain three current, though conflicting, approaches to derive a theoretical expression for R0 for ETIDs and assess their validity through comparison with available empirical data. Salmonella Typhimurium in laboratory mice was used as a theoretical and empirical model system. The three conflicting theoretical expressions for R0 were derived using the next generation matrix approach according to three unverified hypotheses about the role of the environmental phase in the transmission of ETIDs. The hypotheses assume that the environment contaminated with a pathogen is: (H1) an extension of the host's infectious period, (H2) a reservoir for the infectious agent, or (H3) has both of these characteristics. For the parameter values describing the empirical model system, the theoretical values of R0 corresponding to the hypotheses H2 and H3 were very similar (1.38 and 1.62, respectively) and their values were approximately half of the value of R0 for hypothesis H1 (2.94). The theoretical R0 values were compared with an empirical R0 (1.58, 95% confidence interval: 1.14, 2.02) estimated using a Martingale method from published experimental data on Salmonella Typhimurium transmission in mice. The results of the comparison suggested that hypothesis H1 is unlikely to hold true but it could not be rejected with confidence because of uncertainty in the value of the pathogen growth rate in the environment. The hypotheses H2 and H3 were both equally strongly supported with the empirical data suggesting that either of them could be valid. A sensitivity analysis identified critical information gaps about the indirect transmission rate of infection and the pathogen growth rate in the environment. Moreover, we identified experimental conditions for which the theoretical R0 predictions based on the hypotheses H2 and H3 differ greatly, which would assist their discrimination and conclusive validation against future empirical studies. Once a valid theoretical R0 is identified for Salmonella Typhimurium in mice, its generalizability to other host-pathogen-environment systems should be tested. The present study may serve as a template for integrated empirical and theoretical research of R0 in the epidemiology of ETIDs.

Complex system modelling for veterinary epidemiology

The use of mathematical models has a long tradition in infectious disease epidemiology. The nonlinear dynamics and complexity of pathogen transmission pose challenges in understanding its key determinants, in identifying critical points, and designing effective mitigation strategies. Mathematical modelling provides tools to explicitly represent the variability, interconnectedness, and complexity of systems, and has contributed to numerous insights and theoretical advances in disease transmission, as well as to changes in public policy, health practice, and management. In recent years, our modelling toolbox has considerably expanded due to the advancements in computing power and the need to model novel data generated by technologies such as proximity loggers and global positioning systems. In this review, we discuss the principles, advantages, and challenges associated with the most recent modelling approaches used in systems science, the interdisciplinary study of complex systems, including agent-based, network and compartmental modelling. Agent-based modelling is a powerful simulation technique that considers the individual behaviours of system components by defining a set of rules that govern how individuals ("agents") within given populations interact with one another and the environment. Agent-based models have become a recent popular choice in epidemiology to model hierarchical systems and address complex spatio-temporal dynamics because of their ability to integrate multiple scales and datasets.

Persistence of an amphibian ranavirus in aquatic communities

Host-parasite dynamics can be strongly influenced by interactions with other members of the biotic community, particularly when the parasite spends some fraction of its life in the environment unprotected by its host. Ranaviruses-often lethal viruses of cold-blooded vertebrate hosts transmitted by direct contact, and via water and fomites-offer an interesting system for understanding these community influences. Previous laboratory studies have shown that ranaviruses can persist for anywhere from days to years, depending on the conditions, with much longer times under sterile conditions. To address the role of the biotic community and particulate matter on ranavirus persistence, we experimentally inoculated filter-sterilized, UV-treated, and unmanipulated pond water with a Frog virus 3 (FV3)-like Ranavirus and took samples over 78 d, quantifying viral titers with real-time quantitative PCR and plaque assays. Viral counts dropped quickly in all treatments, by an order of magnitude in under a day in unmanipulated pond water and in 8 d in filter-sterilized pond water. In a second experiment, we measured viral titers over 24 h in virus-spiked spring water with Daphnia pulex. Presence of D. pulex reduced the concentration of infectious ranavirus, but not viral DNA, by an order of magnitude in 24 h. D. pulex themselves did not accumulate the virus. We conclude that both microbial and zooplanktonic communities can play an important role in ranavirus epidemiology, rapidly inactivating ranavirus in the water and thereby minimizing environmental transmission. We suspect that interactions with the biotic community will be important for most pathogens with environmental resting or transmission stages.

Transmission of ranavirus between ectothermic vertebrate hosts

Transmission is an essential process that contributes to the survival of pathogens. Ranaviruses are known to infect different classes of lower vertebrates including amphibians, fishes and reptiles. Differences in the likelihood of infection among ectothermic vertebrate hosts could explain the successful yearlong persistence of ranaviruses in aquatic environments. The goal of this study was to determine if transmission of a Frog Virus 3 (FV3)-like ranavirus was possible among three species from different ectothermic vertebrate classes: Cope’s gray treefrog (Hyla chrysoscelis) larvae, mosquito fish (Gambusia affinis), and red-eared slider (Trachemys scripta elegans). We housed individuals previously exposed to the FV3-like ranavirus with naïve (unexposed) individuals in containers divided by plastic mesh screen to permit water flow between subjects. Our results showed that infected gray treefrog larvae were capable of transmitting ranavirus to naïve larval conspecifics and turtles (60% and 30% infection, respectively), but not to fish. Also, infected turtles and fish transmitted ranavirus to 50% and 10% of the naïve gray treefrog larvae, respectively. Nearly all infected amphibians experienced mortality, whereas infected turtles and fish did not die. Our results demonstrate that ranavirus can be transmitted through water among ectothermic vertebrate classes, which has not been reported previously. Moreover, fish and reptiles might serve as reservoirs for ranavirus given their ability to live with subclinical infections. Subclinical infections of ranavirus in fish and aquatic turtles could contribute to the pathogen’s persistence, especially when highly susceptible hosts like amphibians are absent as a result of seasonal fluctuations in relative abundance.

Temporal-spatial heterogeneity in animal-environment contact: implications for the exposure and transmission of pathogens

Contact structure, a critical driver of infectious disease transmission, is not completely understood and characterized for environmentally transmitted pathogens. In this study, we assessed the effects of temporal and spatial heterogeneity in animal contact structures on the dynamics of environmentally transmitted pathogens. We used real-time animal position data to describe contact between animals and specific environmental areas used for feeding and watering calves. The generated contact structure varied across days and among animals. We integrated animal and environmental heterogeneity into an agent-based simulation model for Escherichia coli O157 environmental transmission in cattle to simulate four different scenarios with different environmental bacteria concentrations at different areas. The simulation results suggest heterogeneity in environmental contact structure among cattle influences pathogen prevalence and exposure associated with each environment. Our findings suggest that interventions that target environmental areas, even relatively small areas, with high bacterial concentration can result in effective mitigation of environmentally transmitted pathogens.

Modeling seasonal behavior changes and disease transmission with application to chronic wasting disease

Behavior and habitat of wildlife animals change seasonally according to environmental conditions. Mathematical models need to represent this seasonality to be able to make realistic predictions about the future of a population and the effectiveness of human interventions. Managing and modeling disease in wild animal populations requires particular care in that disease transmission dynamics is a critical consideration in the etiology of both human and animal diseases, with different transmission paradigms requiring different disease risk management strategies. Since transmission of infectious diseases among wildlife depends strongly on social behavior, mechanisms of disease transmission could also change seasonally. A specific consideration in this regard confronted by modellers is whether the contact rate between individuals is density-dependent or frequency-dependent. We argue that seasonal behavior changes could lead to a seasonal shift between density and frequency dependence. This hypothesis is explored in the case of chronic wasting disease (CWD), a fatal disease that affects deer, elk and moose in many areas of North America. Specifically, we introduce a strategic CWD risk model based on direct disease transmission that accounts for the seasonal change in the transmission dynamics and habitats occupied, guided by information derived from cervid ecology. The model is composed of summer and winter susceptible-infected (SI) equations, with frequency-dependent and density-dependent transmission dynamics, respectively. The model includes impulsive birth events with density-dependent birth rate. We determine the basic reproduction number as a weighted average of two seasonal reproduction numbers. We parameterize the model from data derived from the scientific literature on CWD and deer ecology, and conduct global and local sensitivity analyses of the basic reproduction number. We explore the effectiveness of different culling strategies for the management of CWD: although summer culling seems to be an effective disease eradication strategy, the total culling rate is limited by the requirement to preserve the herd.

A construction method to study the role of incidence in the adaptive dynamics of pathogens with direct and environmental transmission

We study the adaptive dynamics of virulence of a pathogen transmitted both via direct contacts between hosts and via free pathogens that survive in the environment. The model is very flexible with a number of trade-off functions linking virulence to other pathogen-related parameters and with two incidence functions that describe the contact rates between hosts and between a host and free pathogens. Instead of making a priori particular assumptions about the shapes of these functions, we introduce a construction method to create specific pairs of incidence functions such that the model becomes an optimization model. Unfolding the optimization model leads to coexistence of pathogen strains and evolutionary branching of virulence. The construction method is applicable to a wide range of eco-evolutionary models.