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NCDMod: A Microsimulation Model Projecting Chronic Disease and Risk Factors for Australian Adults

Author

Listed:
  • Sharyn Lymer

    (Faculty of Pharmacy, Level 2 Charles Perkins Centre D17, University of Sydney, NSW 2006)

  • Deborah Schofield

    (Faculty of Pharmacy, Level 2 Charles Perkins Centre D17, University of Sydney, NSW 2006)

  • Crystal M Y Lee

    (The Boden Institute of Obesity, Nutrition, Exercise and Eating Disorders, level 2 Charles Perkins Centre D17, University of Sydney, NSW 2006)

  • Stephen Colagiuri

    (The Boden Institute of Obesity, Nutrition, Exercise and Eating Disorders, level 2 Charles Perkins Centre D17, University of Sydney, NSW 2006)

Abstract

Chronic disease and the associated risk factors are an ongoing public health concern. They represent a major burden of disease and result in significant health expenditure. The purpose of this paper is to describe the development and attributes of the microsimulation model NCDMod, an Australian, purpose-built model that simulates multiple chronic diseases and associated risk factors. The model offers flexibility in perspective and population of interest. The model projects out to 2025 in 5-year increments using a combination of static and dynamic methods. Transition equations are sourced from the literature and in-house analysis. NCDMod is able to capture the impacts of population ageing and shifts in incidence of specific chronic diseases and risk factors. Results from NCDMod will help to fill gaps in current Australian evidence on the population level impacts of interventions to prevent/delay chronic health conditions particularly diabetes, heart disease and obesity. Further, in combination with HealthWealthMod2030 this model will be able to offer evidence regarding the potential impact of health interventions on the long-term costs (both from an individual and government

Suggested Citation

  • Sharyn Lymer & Deborah Schofield & Crystal M Y Lee & Stephen Colagiuri, 2016. "NCDMod: A Microsimulation Model Projecting Chronic Disease and Risk Factors for Australian Adults," International Journal of Microsimulation, International Microsimulation Association, vol. 9(3), pages 103-139.
    • Handle: RePEc:ijm:journl:v:9:y:2016:i:3:p:103-139
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    References listed on IDEAS

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    1. Deborah Schofield & Rupendra Shrestha & Simon Kelly & Lennert Veerman & Robert Tanton & Megan Passey & Theo Vos & Michelle Cunich & Emily Callander, 2014. "Health&WealthMOD2030: A Microsimulation Model of the Long Term Economic Impacts of Disease Leading to Premature Retirements of Australians Aged 45-64 Years Old," International Journal of Microsimulation, International Microsimulation Association, vol. 7(2), pages 94-118.
    2. Agnes E. Walker & Stephen Colagiuri, 2011. "Cost-Benefit Model System of Chronic Diseases in Australia to Assess and Rank Prevention and Treatment Options," International Journal of Microsimulation, International Microsimulation Association, vol. 4(3), pages 57-70.
    3. Buchmueller, Thomas C. & Johar, Meliyanni, 2015. "Obesity and health expenditures: Evidence from Australia," Economics & Human Biology, Elsevier, vol. 17(C), pages 42-58.
    4. Alan D. Lopez & Colin D. Mathers & Majid Ezzati & Dean T. Jamison & Christopher J. L. Murray, 2006. "Global Burden of Disease and Risk Factors," World Bank Publications - Books, The World Bank Group, number 7039.
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    Cited by:

    1. Abbygail Jaccard & Lise Retat & Martin Brown & Laura Webber & Zaid Chalabi, 2018. "Global Sensitivity Analysis of a Model Simulating an Individual’s Health State through Their Lifetime," International Journal of Microsimulation, International Microsimulation Association, vol. 11(3), pages 100-121.
    2. Deborah J Schofield & Melanie J B Zeppel & Owen Tan & Sharyn Lymer & Michelle M Cunich & Rupendra N Shrestha, 2018. "A Brief, Global History of Microsimulation Models in Health: Past Applications, Lessons Learned and Future Directions," International Journal of Microsimulation, International Microsimulation Association, vol. 11(1), pages 97-142.
    3. Anne Mason & Idaira Rodriguez Santana & María José Aragón & Nigel Rice & Martin Chalkley & Raphael Wittenberg & Jose-Luis Fernandez, 2019. "Drivers of health care expenditure: Final report," Working Papers 169cherp, Centre for Health Economics, University of York.

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    More about this item

    Keywords

    Microsimulation; chronic disease; cardiovascular disease;
    All these keywords.

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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