A simulation model to estimate the risk of transfusion-transmitted arboviral infection

Guifang Shang, Brad Biggerstaff, Alice RICHARDSON, Michelle GAHAN, Brett Lidbury

    Research output: Contribution to journalArticle

    2 Citations (Scopus)

    Abstract

    Background The arboviruses West Nile virus (WNV), dengue virus (DENV) and Ross River virus (RRV) have been demonstrated to be blood transfusion-transmissible. A model to estimate the risk of WNV to the blood supply using a Monte Carlo approach has been developed and also applied to Chikungunya virus. Also, a probabilistic model was developed to assess the risk of DENV to blood safety, which was later adapted to RRV. To address efficacy and limitations within each model we present a hybrid model that promises improved accuracy, and is broadly applicable to assess the risk of arboviral transmission by blood transfusion. Material and methods Data were drawn from the Cairns Public Health Unit (Australia) and published literature. Based on the published models and using R code, a novel ‘combined’ model was developed and validated against the BP model using sensitivity testing. Results The mean risk per 10,000 of the combined model is 0.98 with a range from 0.79 to 1.25, while the maximum risk was 4.45 ranging from 2.62 to 7.67 respectively. These parameters for the BP model were 1.20 ranging from 0.84 to 1.55, and 2.86 ranging from 1.33 to 5.23 respectively. Conclusion The combined simulation model is simple and robust. We propose it can be applied as a ‘generic’ arbovirus model to assess the risk from known or novel arboviral threats to the blood supply.
    Original languageEnglish
    Pages (from-to)233-239
    Number of pages7
    JournalTransfusion and Apheresis Science
    Volume55
    Issue number2
    DOIs
    Publication statusPublished - Oct 2016

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    Ross River virus
    Infection
    Arboviruses
    West Nile virus
    Dengue Virus
    Blood Transfusion
    Chikungunya virus
    Blood Safety
    Statistical Models
    Public Health

    Cite this

    Shang, Guifang ; Biggerstaff, Brad ; RICHARDSON, Alice ; GAHAN, Michelle ; Lidbury, Brett. / A simulation model to estimate the risk of transfusion-transmitted arboviral infection. In: Transfusion and Apheresis Science. 2016 ; Vol. 55, No. 2. pp. 233-239.
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    abstract = "Background The arboviruses West Nile virus (WNV), dengue virus (DENV) and Ross River virus (RRV) have been demonstrated to be blood transfusion-transmissible. A model to estimate the risk of WNV to the blood supply using a Monte Carlo approach has been developed and also applied to Chikungunya virus. Also, a probabilistic model was developed to assess the risk of DENV to blood safety, which was later adapted to RRV. To address efficacy and limitations within each model we present a hybrid model that promises improved accuracy, and is broadly applicable to assess the risk of arboviral transmission by blood transfusion. Material and methods Data were drawn from the Cairns Public Health Unit (Australia) and published literature. Based on the published models and using R code, a novel ‘combined’ model was developed and validated against the BP model using sensitivity testing. Results The mean risk per 10,000 of the combined model is 0.98 with a range from 0.79 to 1.25, while the maximum risk was 4.45 ranging from 2.62 to 7.67 respectively. These parameters for the BP model were 1.20 ranging from 0.84 to 1.55, and 2.86 ranging from 1.33 to 5.23 respectively. Conclusion The combined simulation model is simple and robust. We propose it can be applied as a ‘generic’ arbovirus model to assess the risk from known or novel arboviral threats to the blood supply.",
    keywords = "Arboviruses, Blood transfusion, Public health, Risk estimation model",
    author = "Guifang Shang and Brad Biggerstaff and Alice RICHARDSON and Michelle GAHAN and Brett Lidbury",
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    A simulation model to estimate the risk of transfusion-transmitted arboviral infection. / Shang, Guifang; Biggerstaff, Brad; RICHARDSON, Alice; GAHAN, Michelle; Lidbury, Brett.

    In: Transfusion and Apheresis Science, Vol. 55, No. 2, 10.2016, p. 233-239.

    Research output: Contribution to journalArticle

    TY - JOUR

    T1 - A simulation model to estimate the risk of transfusion-transmitted arboviral infection

    AU - Shang, Guifang

    AU - Biggerstaff, Brad

    AU - RICHARDSON, Alice

    AU - GAHAN, Michelle

    AU - Lidbury, Brett

    PY - 2016/10

    Y1 - 2016/10

    N2 - Background The arboviruses West Nile virus (WNV), dengue virus (DENV) and Ross River virus (RRV) have been demonstrated to be blood transfusion-transmissible. A model to estimate the risk of WNV to the blood supply using a Monte Carlo approach has been developed and also applied to Chikungunya virus. Also, a probabilistic model was developed to assess the risk of DENV to blood safety, which was later adapted to RRV. To address efficacy and limitations within each model we present a hybrid model that promises improved accuracy, and is broadly applicable to assess the risk of arboviral transmission by blood transfusion. Material and methods Data were drawn from the Cairns Public Health Unit (Australia) and published literature. Based on the published models and using R code, a novel ‘combined’ model was developed and validated against the BP model using sensitivity testing. Results The mean risk per 10,000 of the combined model is 0.98 with a range from 0.79 to 1.25, while the maximum risk was 4.45 ranging from 2.62 to 7.67 respectively. These parameters for the BP model were 1.20 ranging from 0.84 to 1.55, and 2.86 ranging from 1.33 to 5.23 respectively. Conclusion The combined simulation model is simple and robust. We propose it can be applied as a ‘generic’ arbovirus model to assess the risk from known or novel arboviral threats to the blood supply.

    AB - Background The arboviruses West Nile virus (WNV), dengue virus (DENV) and Ross River virus (RRV) have been demonstrated to be blood transfusion-transmissible. A model to estimate the risk of WNV to the blood supply using a Monte Carlo approach has been developed and also applied to Chikungunya virus. Also, a probabilistic model was developed to assess the risk of DENV to blood safety, which was later adapted to RRV. To address efficacy and limitations within each model we present a hybrid model that promises improved accuracy, and is broadly applicable to assess the risk of arboviral transmission by blood transfusion. Material and methods Data were drawn from the Cairns Public Health Unit (Australia) and published literature. Based on the published models and using R code, a novel ‘combined’ model was developed and validated against the BP model using sensitivity testing. Results The mean risk per 10,000 of the combined model is 0.98 with a range from 0.79 to 1.25, while the maximum risk was 4.45 ranging from 2.62 to 7.67 respectively. These parameters for the BP model were 1.20 ranging from 0.84 to 1.55, and 2.86 ranging from 1.33 to 5.23 respectively. Conclusion The combined simulation model is simple and robust. We propose it can be applied as a ‘generic’ arbovirus model to assess the risk from known or novel arboviral threats to the blood supply.

    KW - Arboviruses

    KW - Blood transfusion

    KW - Public health

    KW - Risk estimation model

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