An immuno-eco-epidemiological model of competition

Bhattacharya, Souvik; Martcheva, Maia

doi:10.1080/17513758.2016.1186291

Cited by 7 publications

(8 citation statements)

References 45 publications

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“…We did this in order to examine how epidemiological parameters interact with within-host processes, showing that population epidemics are determined by the level of toxicant exposure, which can be divided into five such phases. Few studies examine the interaction between toxicant stress and within-host processes, and even fewer then relate this to the population scale (Lundin et al 2015, Bhattacharya andMartcheva 2016). The novelty therefore in this paper is the consideration of both within-and betweenhost scales, as opposed to the singular scale examined in Booton et al (2018).…”

Section: Discussionmentioning

confidence: 99%

“…To date, little work addresses the interface between population epidemiology and toxicant stress (Lundin et al 2015, Bhattacharya andMartcheva 2016). In this study, we examine how toxicants impact the spread of disease within populations, and how the subsequent epidemiology is formed from their respective within-and between-host processes.…”

Section: Introductionmentioning

confidence: 97%

“…This approach is particularly useful when the effects of within-host processes on determining population epidemiology are unknown (Mideo et al 2008), and as such, parameter relationships can be determined from the subsequent analysis of the nested model, providing important biological mechanistic predictions (Gilchrist and Sasaki 2002, Alizon and van Baalen 2005, Gilchrist and Coombs 2006, Feng et al 2012. For example, the model by Bhattacharya and Martcheva (2016) relates the immune response of a species infected by a pathogen to population epidemiological parameters, using a nested within-and between-host approach. This study however focusses on ecological competition between species, rather than additional sources of stressors such as toxicants.…”

Section: Introductionmentioning

confidence: 99%

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How do toxicants affect epidemiological dynamics?

Booton

Iwasa

Childs

2018

Oikos

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Populations are formed of their constituent interacting individuals, each with their own respective within‐host biological processes. Infection not only spreads within the host organism but also spreads between individuals. Here we propose and study a multilevel model which links the within‐host statuses of immunity and parasite density to population epidemiology under sublethal and lethal toxicant exposure. We analyse this nested model in order to better understand how toxicants impact the spread of disease within populations. We demonstrate that outbreak of infection within a population is completely determined by the level of toxicant exposure, and that it is maximised by intermediate toxicant dosage. We classify the population epidemiology into five phases of increasing toxicant exposure and calculate the conditions under which disease will spread, showing that there exists a threshold toxicant level under which epidemics will not occur. In general, higher toxicant load results in either extinction of the population or outbreak of infection. The within‐host statuses of the individual host also determine the outcome of the epidemic at the population level. We discuss applications of our model in the context of environmental epidemiology, predicting that increased exposure to toxicants could result in greater risk of epidemics within ecological systems. We predict that reducing sublethal toxicant exposure below our predicted safe threshold could contribute to controlling population level disease and infection.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 97%

Section: Introductionmentioning

confidence: 99%

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How do toxicants affect epidemiological dynamics?

Booton

Iwasa

Childs

2018

Oikos

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“…Since complex interactions and feedbacks are likely when certain traits are correlated with competitive ability in a community, the ability to intuit the resulting effects of these correlations on community dynamics may break down. Fortunately, the diverse theoretical work that has investigated the effects of parasites in communities (Begon et al, 1992;Bhattacharya & Martcheva, 2016;Bowers & Turner, 1997;Fenton & Brockhurst, 2008;Fenton, Streicker, Petchey, & Pederson, 2015;Holt & Pickering, 1985;Joseph et al, 2013;Mihaljevic, Joseph, Orlofske, & Paull, 2014;O'Regan et al, 2015;Strauss et al, 2015) provides an excellent framework to approach these complex questions.…”

Section: Introductionmentioning

confidence: 99%

Host traits and competitive ability jointly structure disease dynamics and community assembly

Kirk

Shea

Start

2019

Journal of Animal Ecology

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Parasitism and competition are both ubiquitous interactions in ecological communities. The ability of host species to interact directly via competition and indirectly through shared parasites suggests that host traits related to competition and parasitism are likely important in structuring communities and disease dynamics. Specifically, those host traits affecting competition and those mediating parasitism are often correlated either because of trade‐offs (in resource acquisition or resource allocation) or condition dependence, yet the consequences of these trait relationships for community and epidemiological dynamics are poorly understood. We conducted a literature review of parasite‐related host traits–competitive ability relationships. We found that transmission–competitive ability relationships were most often reported, and that superior competitors exhibited elevated transmission relative to their less‐competitive counterparts in nearly 80% of the cases. We also found a significant number of virulence–competitive ability and parasite shedding–competitive ability relationships. We investigated these links by altering the relationship between host competitive ability and three parasite‐related traits (transmission, virulence and parasite shedding rates) in a simple model, incorporating competitive asymmetries in a multi‐host community. We show that these relationships can lead to a range of different communities. For example, depending on the strength and direction of these distinct trait relationships, we observed communities with anywhere from high parasite prevalence to complete parasite extinction, and either one, two or the maximum of three host species coexisting. Our results suggest that parasite–competitive ability relationships may be common in nature, that further integration of these relationships can produce novel and unexpected community and disease dynamics, and that generalizations may allow for the prediction of how parasitism and competition jointly structure disease and diversity in natural communities.

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“…The dependence of the within-host system on a between-host variable makes the nested model bidirectionally linked, although our linking mechanism is different from the one used in environmentally driven diseases. This type of interaction and bidirectional linkage was first examined in [2]. Here we generalize the model and examine more complex properties of the model than considered in [2].…”

Section: Introductionmentioning

confidence: 99%

Backward bifurcation and oscillations in a nested immuno-eco-epidemiological model

Barfield

Martcheva

Tuncer

et al. 2017

Journal of Biological Dynamics

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This paper introduces a novel partial differential equation immuno-eco-epidemiological model of competition in which one species is affected by a disease while another can compete with it directly and by lowering the first species' immune response to the infection, a mode of competition termed stress-induced competition. When the disease is chronic, and the within-host dynamics are rapid, we reduce the partial differential equation model (PDE) to a three-dimensional ordinary differential equation (ODE) model. The ODE model exhibits backward bifurcation and sustained oscillations caused by the stress-induced competition. Furthermore, the ODE model, although not a special case of the PDE model, is useful for detecting backward bifurcation and oscillations in the PDE model. Backward bifurcation related to stress-induced competition allows the second species to persist for values of its invasion number below one. Furthermore, stress-induced competition leads to destabilization of the coexistence equilibrium and sustained oscillations in the PDE model. We suggest that complex systems such as this one may be studied by appropriately designed simple ODE models.

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An immuno-eco-epidemiological model of competition

Cited by 7 publications

References 45 publications

How do toxicants affect epidemiological dynamics?

How do toxicants affect epidemiological dynamics?

Host traits and competitive ability jointly structure disease dynamics and community assembly

Backward bifurcation and oscillations in a nested immuno-eco-epidemiological model

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