Novel coupling of individual-based epidemiological and demographic models predicts realistic dynamics of tuberculosis in alien buffalo

Corey J.A. Bradshaw, Clive R. Mcmahon, Philip S. Miller, Robert C. Lacy, Michael J. Watts, Michelle L. Verant, John P. Pollak, Damien A. Fordham, Thomas A.A. Prowse, Barry W. Brook

    Research output: Contribution to journalArticleResearchpeer-review

    Abstract

    Increasing sophistication of population viability analysis has broadened our capacity to model population change while accounting for system complexity and uncertainty. However, many emergent properties of population dynamics, such as the coupling of demographic processes with transmission and spread of disease, are still poorly understood. We combined an individual-based demographic (Vortex) and epidemiological (Outbreak) model using a novel command-centre module (MetaModel Manager) to predict the progression of bovine tuberculosis in introduced swamp buffalo Bubalus bubalis in northern Australia and validated the model with data from a large-scale disease-monitoring and culling programme. We also assessed the capacity to detect disease based on incrementing sentinel (randomly sampled individuals) culling rates. We showed that even high monitoring effort (1000 culled sentinels) has a low (<10%) probability of detecting the disease, and current sampling is inadequate. Testing proportional and stepped culling rates revealed that up to 50% of animals must be killed each year to reduce disease prevalence to near-eradication levels. Sensitivity analysis indicated that prevalence depended mainly on population demography (e.g. female age at primiparity) and the additional mortality induced by disease, with only minor contributions from epidemiological characteristics such as probability of transmission and encounter rate. This is a useful finding because the disease parameters are the least well known. Synthesis and applications.Our models suggest that details of population demography should be incorporated into epidemiological models to avoid extensive bias in predictions of disease spread and effectiveness of control. Importantly, we demonstrate that low detection probabilities challenge the effectiveness of existing disease-monitoring protocols in northern Australia. The command-centre module we describe linking demographic and epidemiological models provides managers with the tools necessary to make informed decisions regarding disease management.

    Original languageEnglish
    Pages (from-to)268-277
    Number of pages10
    JournalJournal of Applied Ecology
    Volume49
    Issue number1
    DOIs
    Publication statusPublished - Feb 2012

    Fingerprint

    tuberculosis
    culling
    demography
    monitoring
    bovine tuberculosis
    population viability analysis
    disease spread
    disease prevalence
    encounter rate
    swamp
    vortex
    sensitivity analysis
    population dynamics
    mortality
    animal
    sampling
    prediction

    Cite this

    Bradshaw, Corey J.A. ; Mcmahon, Clive R. ; Miller, Philip S. ; Lacy, Robert C. ; Watts, Michael J. ; Verant, Michelle L. ; Pollak, John P. ; Fordham, Damien A. ; Prowse, Thomas A.A. ; Brook, Barry W. / Novel coupling of individual-based epidemiological and demographic models predicts realistic dynamics of tuberculosis in alien buffalo. In: Journal of Applied Ecology. 2012 ; Vol. 49, No. 1. pp. 268-277.
    @article{5e44426b0a1945ae89789adc26651b36,
    title = "Novel coupling of individual-based epidemiological and demographic models predicts realistic dynamics of tuberculosis in alien buffalo",
    abstract = "Increasing sophistication of population viability analysis has broadened our capacity to model population change while accounting for system complexity and uncertainty. However, many emergent properties of population dynamics, such as the coupling of demographic processes with transmission and spread of disease, are still poorly understood. We combined an individual-based demographic (Vortex) and epidemiological (Outbreak) model using a novel command-centre module (MetaModel Manager) to predict the progression of bovine tuberculosis in introduced swamp buffalo Bubalus bubalis in northern Australia and validated the model with data from a large-scale disease-monitoring and culling programme. We also assessed the capacity to detect disease based on incrementing sentinel (randomly sampled individuals) culling rates. We showed that even high monitoring effort (1000 culled sentinels) has a low (<10{\%}) probability of detecting the disease, and current sampling is inadequate. Testing proportional and stepped culling rates revealed that up to 50{\%} of animals must be killed each year to reduce disease prevalence to near-eradication levels. Sensitivity analysis indicated that prevalence depended mainly on population demography (e.g. female age at primiparity) and the additional mortality induced by disease, with only minor contributions from epidemiological characteristics such as probability of transmission and encounter rate. This is a useful finding because the disease parameters are the least well known. Synthesis and applications.Our models suggest that details of population demography should be incorporated into epidemiological models to avoid extensive bias in predictions of disease spread and effectiveness of control. Importantly, we demonstrate that low detection probabilities challenge the effectiveness of existing disease-monitoring protocols in northern Australia. The command-centre module we describe linking demographic and epidemiological models provides managers with the tools necessary to make informed decisions regarding disease management.",
    keywords = "Bubalus, Disease, Invasive species, MetaModel Manager, Outbreak, Population viability analysis, Vortex",
    author = "Bradshaw, {Corey J.A.} and Mcmahon, {Clive R.} and Miller, {Philip S.} and Lacy, {Robert C.} and Watts, {Michael J.} and Verant, {Michelle L.} and Pollak, {John P.} and Fordham, {Damien A.} and Prowse, {Thomas A.A.} and Brook, {Barry W.}",
    year = "2012",
    month = "2",
    doi = "10.1111/j.1365-2664.2011.02081.x",
    language = "English",
    volume = "49",
    pages = "268--277",
    journal = "Journal of Applied Ecology",
    issn = "0021-8901",
    publisher = "Wiley-Blackwell",
    number = "1",

    }

    Bradshaw, CJA, Mcmahon, CR, Miller, PS, Lacy, RC, Watts, MJ, Verant, ML, Pollak, JP, Fordham, DA, Prowse, TAA & Brook, BW 2012, 'Novel coupling of individual-based epidemiological and demographic models predicts realistic dynamics of tuberculosis in alien buffalo', Journal of Applied Ecology, vol. 49, no. 1, pp. 268-277. https://doi.org/10.1111/j.1365-2664.2011.02081.x

    Novel coupling of individual-based epidemiological and demographic models predicts realistic dynamics of tuberculosis in alien buffalo. / Bradshaw, Corey J.A.; Mcmahon, Clive R.; Miller, Philip S.; Lacy, Robert C.; Watts, Michael J.; Verant, Michelle L.; Pollak, John P.; Fordham, Damien A.; Prowse, Thomas A.A.; Brook, Barry W.

    In: Journal of Applied Ecology, Vol. 49, No. 1, 02.2012, p. 268-277.

    Research output: Contribution to journalArticleResearchpeer-review

    TY - JOUR

    T1 - Novel coupling of individual-based epidemiological and demographic models predicts realistic dynamics of tuberculosis in alien buffalo

    AU - Bradshaw, Corey J.A.

    AU - Mcmahon, Clive R.

    AU - Miller, Philip S.

    AU - Lacy, Robert C.

    AU - Watts, Michael J.

    AU - Verant, Michelle L.

    AU - Pollak, John P.

    AU - Fordham, Damien A.

    AU - Prowse, Thomas A.A.

    AU - Brook, Barry W.

    PY - 2012/2

    Y1 - 2012/2

    N2 - Increasing sophistication of population viability analysis has broadened our capacity to model population change while accounting for system complexity and uncertainty. However, many emergent properties of population dynamics, such as the coupling of demographic processes with transmission and spread of disease, are still poorly understood. We combined an individual-based demographic (Vortex) and epidemiological (Outbreak) model using a novel command-centre module (MetaModel Manager) to predict the progression of bovine tuberculosis in introduced swamp buffalo Bubalus bubalis in northern Australia and validated the model with data from a large-scale disease-monitoring and culling programme. We also assessed the capacity to detect disease based on incrementing sentinel (randomly sampled individuals) culling rates. We showed that even high monitoring effort (1000 culled sentinels) has a low (<10%) probability of detecting the disease, and current sampling is inadequate. Testing proportional and stepped culling rates revealed that up to 50% of animals must be killed each year to reduce disease prevalence to near-eradication levels. Sensitivity analysis indicated that prevalence depended mainly on population demography (e.g. female age at primiparity) and the additional mortality induced by disease, with only minor contributions from epidemiological characteristics such as probability of transmission and encounter rate. This is a useful finding because the disease parameters are the least well known. Synthesis and applications.Our models suggest that details of population demography should be incorporated into epidemiological models to avoid extensive bias in predictions of disease spread and effectiveness of control. Importantly, we demonstrate that low detection probabilities challenge the effectiveness of existing disease-monitoring protocols in northern Australia. The command-centre module we describe linking demographic and epidemiological models provides managers with the tools necessary to make informed decisions regarding disease management.

    AB - Increasing sophistication of population viability analysis has broadened our capacity to model population change while accounting for system complexity and uncertainty. However, many emergent properties of population dynamics, such as the coupling of demographic processes with transmission and spread of disease, are still poorly understood. We combined an individual-based demographic (Vortex) and epidemiological (Outbreak) model using a novel command-centre module (MetaModel Manager) to predict the progression of bovine tuberculosis in introduced swamp buffalo Bubalus bubalis in northern Australia and validated the model with data from a large-scale disease-monitoring and culling programme. We also assessed the capacity to detect disease based on incrementing sentinel (randomly sampled individuals) culling rates. We showed that even high monitoring effort (1000 culled sentinels) has a low (<10%) probability of detecting the disease, and current sampling is inadequate. Testing proportional and stepped culling rates revealed that up to 50% of animals must be killed each year to reduce disease prevalence to near-eradication levels. Sensitivity analysis indicated that prevalence depended mainly on population demography (e.g. female age at primiparity) and the additional mortality induced by disease, with only minor contributions from epidemiological characteristics such as probability of transmission and encounter rate. This is a useful finding because the disease parameters are the least well known. Synthesis and applications.Our models suggest that details of population demography should be incorporated into epidemiological models to avoid extensive bias in predictions of disease spread and effectiveness of control. Importantly, we demonstrate that low detection probabilities challenge the effectiveness of existing disease-monitoring protocols in northern Australia. The command-centre module we describe linking demographic and epidemiological models provides managers with the tools necessary to make informed decisions regarding disease management.

    KW - Bubalus

    KW - Disease

    KW - Invasive species

    KW - MetaModel Manager

    KW - Outbreak

    KW - Population viability analysis

    KW - Vortex

    UR - http://www.scopus.com/inward/record.url?scp=84855953849&partnerID=8YFLogxK

    U2 - 10.1111/j.1365-2664.2011.02081.x

    DO - 10.1111/j.1365-2664.2011.02081.x

    M3 - Article

    VL - 49

    SP - 268

    EP - 277

    JO - Journal of Applied Ecology

    JF - Journal of Applied Ecology

    SN - 0021-8901

    IS - 1

    ER -