scholarly journals A mechanistic, stigmergy model of territory formation in asocial animals: Territorial behavior can dampen disease prevalence but increase persistence

2019 ◽  
Author(s):  
Lauren A. White ◽  
Sue VandeWoude ◽  
Meggan E. Craft

AbstractMechanistic portrayals of how animals form and maintain territories remain rare, and as a discipline, collective movement ecology has tended to focus on synergistic (e.g., migration, shoaling) rather than agonistic or territorial interactions. Here we ask how dynamic territory formation and maintenance might contribute to disease dynamics in an asocial territorial animal for an indirectly transmitted pathogen. We developed a mechanistic individual-based model where stigmergy—the deposition of signals into the environment (e.g., scent marking, scraping)—dictates not only local movement choices and long-term territory formation, but also the risk of pathogen transmission. Based on a variable importance analysis, the length of the infectious period was the single most important variable in predicting outbreak success, maximum prevalence, and outbreak duration. Population size and rate of pathogen decay were also key predictors. We found that territoriality best reduced maximum prevalence in conditions where we would otherwise expect outbreaks to be most successful: slower recovery rates (i.e., longer infectious periods) and higher conspecific densities. However, at high enough densities, outbreak duration became considerably more variable. Our findings therefore support a limited version of the “territoriality benefits” hypothesis—where reduced home range overlap leads to reduced opportunities for pathogen transmission, but with the caveat that reduction in outbreak severity may increase the likelihood of pathogen persistence. For longer infectious periods and higher host densities, key trade-offs emerged between the strength of pathogen load, strength of the stigmergy cue, and the rate at which those two quantities decayed; this finding raises interesting questions about the evolutionary nature of these competing processes and the role of possible feedbacks between parasitism and territoriality. This work also highlights the importance of considering social cues as part of the movement landscape in order to improve our understanding of the consequences of individual behaviors on population level outcomes.Author summaryMaking decisions about conservation and disease management relies on our understanding of what allows animal populations to be successful. However, movement ecology, as a field, tends to focus on how animals respond to their abiotic environment. Similarly, disease ecology often focuses on the social behavior of animals without accounting for their individual movement patterns. We developed a simulation model that bridges these two fields by allowing hosts to inform their movement based on the past trajectories of other hosts. As hosts navigate their environment, they leave behind a scent trail while avoiding the scent trails of other individuals. We wanted to know if this means of territory formation could heighten or dampen disease spread when infectious hosts leave pathogens in their wake. We found that territoriality could inhibit disease spread under conditions that we would normally expect pathogens to be most successful: where there are many hosts on the landscape and hosts stay infectious for longer. This work points to how incorporating movement behavior into disease models can provide improved understanding of how diseases spread in wildlife populations; such understanding is particularly important in the face of combatting ongoing and emerging infectious diseases.

2005 ◽  
Vol 134 (1) ◽  
pp. 31-40 ◽  
Author(s):  
C. R. WEBB

SUMMARYThe rate at which infectious diseases spread through farm animal populations depends both on individual disease characteristics and the opportunity for transmission via close contact. Data on the relationships affecting the contact structure of farm animal populations are, therefore, required to improve mathematical models for the spatial spread of farm animal diseases. This paper presents data on the contact network for agricultural shows in Great Britain, whereby a link between two shows occurs if they share common competitors in the sheep class. Using the network, the potential for disease spread through agricultural shows is investigated varying both the initial show infected and the infectious period of the disease. The analysis reveals a highly connected network such that diseases introduced early in the show season could present a risk to sheep at the majority of subsequent shows. This data emphasizes the importance of maintaining rigorous showground and farm-level bio-security.


Author(s):  
Yun Tao ◽  
Jessica L. Hite ◽  
Kevin D. Lafferty ◽  
David J. D. Earn ◽  
Nita Bharti

AbstractAnalyses of transient dynamics are critical to understanding infectious disease transmission and persistence. Identifying and predicting transients across scales, from within-host to community-level patterns, plays an important role in combating ongoing epidemics and mitigating the risk of future outbreaks. Moreover, greater emphases on non-asymptotic processes will enable timely evaluations of wildlife and human diseases and lead to improved surveillance efforts, preventive responses, and intervention strategies. Here, we explore the contributions of transient analyses in recent models spanning the fields of epidemiology, movement ecology, and parasitology. In addition to their roles in predicting epidemic patterns and endemic outbreaks, we explore transients in the contexts of pathogen transmission, resistance, and avoidance at various scales of the ecological hierarchy. Examples illustrate how (i) transient movement dynamics at the individual host level can modify opportunities for transmission events over time; (ii) within-host energetic processes often lead to transient dynamics in immunity, pathogen load, and transmission potential; (iii) transient connectivity between discrete populations in response to environmental factors and outbreak dynamics can affect disease spread across spatial networks; and (iv) increasing species richness in a community can provide transient protection to individuals against infection. Ultimately, we suggest that transient analyses offer deeper insights and raise new, interdisciplinary questions for disease research, consequently broadening the applications of dynamical models for outbreak preparedness and management.


2019 ◽  
Vol 59 (5) ◽  
pp. 1220-1230 ◽  
Author(s):  
Amberleigh E Henschen ◽  
James S Adelman

Abstract Host competence, or how well an individual transmits pathogens, varies substantially within and among animal populations. As this variation can alter the course of epidemics and epizootics, revealing its underlying causes will help predict and control the spread of disease. One host trait that could drive heterogeneity in competence is host tolerance, which minimizes fitness losses during infection without decreasing pathogen load. In many cases, tolerance should increase competence by extending infectious periods and enabling behaviors that facilitate contact among hosts. However, we argue that the links between tolerance and competence are more varied. Specifically, the different physiological and behavioral mechanisms by which hosts achieve tolerance should have a range of effects on competence, enhancing the ability to transmit pathogens in some circumstances and impeding it in others. Because tissue-based pathology (damage) that reduces host fitness is often critical for pathogen transmission, we focus on two mechanisms that can underlie tolerance at the tissue level: damage-avoidance and damage-repair. As damage-avoidance reduces transmission-enhancing pathology, this mechanism is likely to decrease host competence and pathogen transmission. In contrast, damage-repair does not prevent transmission-relevant pathology from occurring. Rather, damage-repair provides new, healthy tissues that pathogens can exploit, likely extending the infectious period and increasing host competence. We explore these concepts through graphical models and present three disease systems in which damage-avoidance and damage-repair alter host competence in the predicted directions. Finally, we suggest that by incorporating these links, future theoretical studies could provide new insights into infectious disease dynamics and host–pathogen coevolution.


2018 ◽  
Vol 5 (4) ◽  
pp. 92 ◽  
Author(s):  
Kathryn Huyvaert ◽  
Robin Russell ◽  
Kelly Patyk ◽  
Meggan Craft ◽  
Paul Cross ◽  
...  

Diseases that affect both wild and domestic animals can be particularly difficult to prevent, predict, mitigate, and control. Such multi-host diseases can have devastating economic impacts on domestic animal producers and can present significant challenges to wildlife populations, particularly for populations of conservation concern. Few mathematical models exist that capture the complexities of these multi-host pathogens, yet the development of such models would allow us to estimate and compare the potential effectiveness of management actions for mitigating or suppressing disease in wildlife and/or livestock host populations. We conducted a workshop in March 2014 to identify the challenges associated with developing models of pathogen transmission across the wildlife-livestock interface. The development of mathematical models of pathogen transmission at this interface is hampered by the difficulties associated with describing the host-pathogen systems, including: (1) the identity of wildlife hosts, their distributions, and movement patterns; (2) the pathogen transmission pathways between wildlife and domestic animals; (3) the effects of the disease and concomitant mitigation efforts on wild and domestic animal populations; and (4) barriers to communication between sectors. To promote the development of mathematical models of transmission at this interface, we recommend further integration of modern quantitative techniques and improvement of communication among wildlife biologists, mathematical modelers, veterinary medicine professionals, producers, and other stakeholders concerned with the consequences of pathogen transmission at this important, yet poorly understood, interface.


2018 ◽  
Vol 5 (5) ◽  
pp. 180041 ◽  
Author(s):  
Muriel Dietrich ◽  
Teresa Kearney ◽  
Ernest C. J. Seamark ◽  
Janusz T. Paweska ◽  
Wanda Markotter

Seasonal reproduction is a period of extreme physiological and behavioural changes, yet we know little about how it may affect host microbial communities (i.e. microbiota) and pathogen transmission. Here, we investigated shifts of the bacterial microbiota in saliva, urine and faeces during the seasonal reproduction of bats in South Africa, and test for an interaction in shedding patterns of both bacterial ( Leptospira ) and viral (adeno- and herpesviruses) agents. Based on a comparative approach in two cave-dwelling bat species and high-throughput sequencing of the 16S rRNA gene, we demonstrated a clear signature in microbiota changes over the reproduction season, consistent across the multiple body habitats investigated, and associated with the sex, age and reproductive condition of bats. We observed in parallel highly dynamic shedding patterns for both bacteria and viruses, but did not find a significant association between viral shedding and bacterial microbiota composition. Indeed, only Leptospira shedding was associated with alterations in both the diversity and composition of the urinary microbiota. These results illustrate how seasonal reproduction in bats substantially affects microbiota composition and infection dynamics, and have broad implications for the understanding of disease ecology in important reservoir hosts, such as bats.


Behaviour ◽  
2018 ◽  
Vol 155 (7-9) ◽  
pp. 759-791 ◽  
Author(s):  
Marie L.J. Gilbertson ◽  
Nicholas M. Fountain-Jones ◽  
Meggan E. Craft

Abstract Utilization of contact networks has provided opportunities for assessing the dynamic interplay between pathogen transmission and host behaviour. Genomic techniques have, in their own right, provided new insight into complex questions in disease ecology, and the increasing accessibility of genomic approaches means more researchers may seek out these tools. The integration of network and genomic approaches provides opportunities to examine the interaction between behaviour and pathogen transmission in new ways and with greater resolution. While a number of studies have begun to incorporate both contact network and genomic approaches, a great deal of work has yet to be done to better integrate these techniques. In this review, we give a broad overview of how network and genomic approaches have each been used to address questions regarding the interaction of social behaviour and infectious disease, and then discuss current work and future horizons for the merging of these techniques.


2017 ◽  
Vol 372 (1722) ◽  
pp. 20160131 ◽  
Author(s):  
A. Marm Kilpatrick ◽  
Daniel J. Salkeld ◽  
Georgia Titcomb ◽  
Micah B. Hahn

The Earth's ecosystems have been altered by anthropogenic processes, including land use, harvesting populations, species introductions and climate change. These anthropogenic processes greatly alter plant and animal communities, thereby changing transmission of the zoonotic pathogens they carry. Biodiversity conservation may be a potential win–win strategy for maintaining ecosystem health and protecting public health, yet the causal evidence to support this strategy is limited. Evaluating conservation as a viable public health intervention requires answering four questions: (i) Is there a general and causal relationship between biodiversity and pathogen transmission, and if so, which direction is it in? (ii) Does increased pathogen diversity with increased host biodiversity result in an increase in total disease burden? (iii) Do the net benefits of biodiversity conservation to human well-being outweigh the benefits that biodiversity-degrading activities, such as agriculture and resource utilization, provide? (iv) Are biodiversity conservation interventions cost-effective when compared to other options employed in standard public health approaches? Here, we summarize current knowledge on biodiversity–zoonotic disease relationships and outline a research plan to address the gaps in our understanding for each of these four questions. Developing practical and self-sustaining biodiversity conservation interventions will require significant investment in disease ecology research to determine when and where they will be effective. This article is part of the themed issue ‘Conservation, biodiversity and infectious disease: scientific evidence and policy implications’.


2018 ◽  
Vol 115 (28) ◽  
pp. 7374-7379 ◽  
Author(s):  
Lauren A. White ◽  
James D. Forester ◽  
Meggan E. Craft

Disease models have provided conflicting evidence as to whether spatial heterogeneity promotes or impedes pathogen persistence. Moreover, there has been limited theoretical investigation into how animal movement behavior interacts with the spatial organization of resources (e.g., clustered, random, uniform) across a landscape to affect infectious disease dynamics. Importantly, spatial heterogeneity of resources can sometimes lead to nonlinear or counterintuitive outcomes depending on the host and pathogen system. There is a clear need to develop a general theoretical framework that could be used to create testable predictions for specific host–pathogen systems. Here, we develop an individual-based model integrated with movement ecology approaches to investigate how host movement behaviors interact with landscape heterogeneity (in the form of various levels of resource abundance and clustering) to affect pathogen dynamics. For most of the parameter space, our results support the counterintuitive idea that fragmentation promotes pathogen persistence, but this finding was largely dependent on perceptual range of the host, conspecific density, and recovery rate. For simulations with high conspecific density, slower recovery rates, and larger perceptual ranges, more complex disease dynamics emerged, and the most fragmented landscapes were not necessarily the most conducive to outbreaks or pathogen persistence. These results point to the importance of interactions between landscape structure, individual movement behavior, and pathogen transmission for predicting and understanding disease dynamics.


Author(s):  
Razvan G. Romanescu ◽  
Rob Deardon

Abstract Properties of statistical alarms have been well studied for simple disease surveillance models, such as normally distributed incidence rates with a sudden or gradual shift in mean at the start of an outbreak. It is known, however, that outbreak dynamics in human populations depend significantly on the heterogeneity of the underlying contact network. The rate of change in incidence for a disease such as influenza peaks early on during the outbreak, when the most highly connected individuals get infected, and declines as the average number of connections in the remaining susceptible population drops. Alarm systems currently in use for detecting the start of influenza seasons generally ignore this mechanism of disease spread, and, as a result, will miss out on some early warning signals. We investigate the performance of various alarms on epidemics simulated from an undirected network model with a power law degree distribution for a pathogen with a relatively short infectious period. We propose simple custom alarms for the disease system considered, and show that they can detect a change in the process sooner than some traditional alarms. Finally, we test our methods on observed rates of influenza-like illness from two sentinel providers (one French, one Spanish) to illustrate their use in the early detection of the flu season.


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