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Chung Yin Kong - One of the best experts on this subject based on the ideXlab platform.
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population impact of lung cancer screening in the united states projections from a Microsimulation Model
PLOS Medicine, 2018Co-Authors: Steven D Criss, Deirdre F Sheehan, Lauren Palazzo, Chung Yin KongAbstract:Background Previous simulation studies estimating the impacts of lung cancer screening have ignored the changes in smoking prevalence over time in the United States. Our primary rationale was to perform, to our knowledge, the first simulation study that estimates the health outcomes of lung cancer screening with explicit Modeling of smoking trends for the whole US population. Methods/Findings Utilizing a well-validated Microsimulation Model, we estimated the benefits and harms of an annual low-dose computed tomography screening scenario with a realistic screening adherence rate versus a no-screening scenario for the US population from 2016–2030. The Centers for Medicare and Medicaid Services (CMS) eligibility criteria were applied: age 55–77 years at time of screening, history of at least 30 pack-years of smoking, and current smoker or former smoker with fewer than 15 years since quitting. In the screened population, cumulative mortality reduction was projected to reach 16.98% (95% CI 16.90%–17.07%). Cumulative mortality reduction was estimated to be 3.52% (95% CI 3.50%–3.53%) for the overall study population, with annual mortality reduction peaking at 4.38% (95% CI 4.36%–4.41%) in 2021 and falling to 3.53% (95% CI 3.50%–3.56%) by 2030. Lung cancer screening would save a projected 148,484 life-years (95% CI 147,429–149,540) across the total population through 2030. There were estimated to be 9,054 (95% CI 9,011–9,098) overdiagnosed cases among the 252,429 (95% CI 251,208–253,649) screen-detected lung cancer diagnoses, yielding an overdiagnosis rate of 3.59%. The limitations of our study are that we do not explicitly Model race or socioeconomic status and our Model was calibrated to data from studies performed in academic centers, both of which may impact the generalizability of our results. We also exclusively Model the effects of the CMS guidelines for lung cancer screening and not any other screening strategies. Conclusions The mortality reduction and life-years gained estimated by this study are lower than those of single birth cohort studies. Single cohort studies neglect the changing dynamics of smoking behavior across generations, whereas this study reflects the trend of decreasing smoking prevalence since the 1960s. Maximum benefit could be derived from lung cancer screening through 2021; in later years, mortality reduction due to screening will decline. If a comprehensive screening program is not implemented in the near future, the opportunity to achieve these benefits will have passed.
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Microsimulation Model predicts survival benefit of radiofrequency ablation and stereotactic body radiotherapy versus radiotherapy for treating inoperable stage i non small cell lung cancer
American Journal of Roentgenology, 2013Co-Authors: Angela C Tramontano, Lauren E Cipriano, Chung Yin Kong, Joanne O Shepard, Michael Lanuti, Scott G Gazelle, Pamela M McmahonAbstract:OBJECTIVE. A subset of patients with stage IA and IB non–small cell lung cancer (NSCLC) is ineligible for surgical resection and undergoes radiation therapy. Radiofrequency ablation (RFA) and stereotactic body radiotherapy are newer potentially attractive alternative therapies. MATERIALS AND METHODS. We added RFA and stereotactic body radiotherapy treatment modules to a Microsimulation Model that simulates lung cancer's natural history, detection, and treatment. Natural history parameters were previously estimated via calibration against tumor registry data and cohort studies; the Model was validated with screening study and cohort data. RFA Model parameters were calibrated against 2-year survival from the Radiofrequency Ablation of Pulmonary Tumor Response Evaluation (RAPTURE) study, and stereotactic body radiotherapy Model parameters were calibrated against 3-year survival from a phase 2 prospective trial. We simulated lifetime histories of identical patients with early-stage NSCLC who were ineligible f...
Deborah Schofield - One of the best experts on this subject based on the ideXlab platform.
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the indirect costs of ischemic heart disease through lost productive life years for australia from 2015 to 2030 results from a Microsimulation Model
BMC Public Health, 2019Co-Authors: Deborah Schofield, Lennert Veerman, Robert Tanton, Megan Passey, Rupendra N Shrestha, Michelle Cunich, Simon KellyAbstract:Most studies measure the impact of ischemic heart disease (IHD) on individuals using quality of life metrics such as disability-adjusted life-years (DALYs); however, IHD also has an enormous impact on productive life years (PLYs). The objective of this study was to project the indirect costs of IHD resulting from lost PLYs to older Australian workers (45–64 years), government, and society 2015–2030. Nationally representative data from the Surveys of Disability, Ageing and Carers (2003, 2009) were used to develop the base population in the Microsimulation Model (HealthW and lost income tax revenue increased from AU$74 (US$71) million in 2015 to AU$117 (US$113) million in 2030 (58% increase). A loss of AU$785 (US$755) million in GDP was projected for 2015, increasing to AU$1125 (US$1082) million in 2030. Significant costs of IHD through lost productivity are incurred by individuals, the government, and society. The benefits of IHD interventions include not only improved health but also potentially economic benefits as workforce capacity.
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the long term economic impacts of arthritis through lost productive life years results from an australian Microsimulation Model
BMC Public Health, 2018Co-Authors: Deborah Schofield, Lennert Veerman, Robert Tanton, Simon Kelly, Rupendra N Shrestha, Michelle Cunich, Megan PasseyAbstract:While the direct (medical) costs of arthritis are regularly reported in cost of illness studies, the 'true' cost to indivdiuals and goverment requires the calculation of the indirect costs as well including lost productivity due to ill-health. Respondents aged 45-64 in the ABS Survey of Disability, Ageing and Carers 2003, 2009 formed the base population. We projected the indirect costs of arthritis using Health&WealthMOD2030 – Australia’s first Microsimulation Model on the long-term impacts of ill-health in older workers – which incorporated outputs from established Microsimulation Models (STINMOD and APPSIM), population and labour force projections from Treasury, and chronic conditions trends for Australia. All costs of arthritis were expressed in real 2013 Australian dollars, adjusted for inflation over time. We estimated there are 54,000 people aged 45-64 with lost PLYs due to arthritis in 2015, increasing to 61,000 in 2030 (13% increase). In 2015, people with lost PLYs are estimated to receive AU$706.12 less in total income and AU$311.67 more in welfare payments per week than full-time workers without arthritis, and pay no income tax on average. National costs include an estimated loss of AU$1.5 billion in annual income in 2015, increasing to AU$2.4 billion in 2030 (59% increase). Lost annual taxation revenue was projected to increase from AU$0.4 billion in 2015 to $0.5 billion in 2030 (56% increase). We projected a loss in GDP of AU$6.2 billion in 2015, increasing to AU$8.2 billion in 2030. Significant costs of arthritis through lost PLYs are incurred by individuals and government. The effectiveness of arthritis interventions should be judged not only on healthcare use but quality of life and economic wellbeing.
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the productivity costs of premature mortality due to cancer in australia evidence from a Microsimulation Model
PLOS ONE, 2016Co-Authors: Hannah E Carter, Deborah Schofield, Rupendra N ShresthaAbstract:AIM: To estimate the productivity costs of premature mortality due to cancer in Australia, in aggregate and for the 26 most prevalent cancer sites. METHODS: A human capital approach was adopted to estimate the long term impacts of Australian cancer deaths in 2003. Using population mortality data, the labour force participation and the present value of lifetime income (PVLI) forgone due to premature mortality was estimated based on individual characteristics at the time of death including age, sex and socioeconomic status. Outcomes were Modelled to the year 2030 using economic data from a national Microsimulation Model. A discount rate of 3% was applied and costs were reported in 2016 Australian dollars. RESULTS: Premature deaths from cancer in 2003 resulted in 88,000 working years lost and a cost of $4.2 billion in the PVLI forgone. Costs were close to three times higher in males than females due to the higher number of premature deaths in men, combined with higher levels of workforce participation and income. Lung, colorectal and brain cancers accounted for the highest proportion of costs, while testicular cancer was the most costly cancer site per death. CONCLUSIONS: The productivity costs of premature mortality due to cancer are significant. These results provide an economic measure of the cancer burden which may assist decision makers in allocating scare resources amongst competing priorities.
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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, 2014Co-Authors: Deborah Schofield, Rupendra Shrestha, Lennert Veerman, Robert Tanton, Simon Kelly, Megan PasseyAbstract:Policymakers in Australia, like in most OECD countries, have recognised the importance of early retirement due to ill health on individuals and families, as well as on the budget balance when planning for the health needs of an ageing population. In order to understand these effects, a unique Microsimulation Model, called HealthWealthMOD2030, was built to estimate the impacts of early retirement due to ill health on labour force participation, personal and household income, economic hardship (poverty), and government taxation revenue, spending and GDP in the years 2010, 2015, 2020, 2025 and 2030. This paper describes the construction of HealthWealthMOD2030. The Model captures the long term projections of demographic change, changing labour force participation patterns, real wages growth and trends in major illnesses affecting the older working age population. The base population of HealthWealthMOD2030 are the individuals aged 45-64 years with information on their work force status and health from the Australian Bureau of Statistics? Surveys of Disability, Ageing and Carers (SDAC) 2003 and 2009. Projected estimates of income, taxation, income support payments, savings and superannuation from the National Centre for Social and Economic Modelling (NATSEM?s) dynamic Microsimulation Model Australian Population and Policy Simulation Model (APPSIM) were synthetically matched with the base population. HealthWealthMOD2030 project forward the economic impacts of early retirement from ill health to 2030. This will fill substantial gaps in the current Australian evidence of health conditions that will keep older working age Australians out of the labour market over the long-term.
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health wealthmod2030 a Microsimulation Model of the long term economic impacts of disease leading to premature retirements of australians aged 45 64 years old
The International Journal of Microsimulation, 2013Co-Authors: Deborah Schofield, Lennert Veerman, Robert Tanton, Megan Passey, Simon Kelly, Rupendra N Shrestha, Michelle Cunich, Emily J CallanderAbstract:Policymakers in Australia, like in most OECD countries, have recognised the importance of early retirement due to ill health on individuals and families, as well as on the budget balance when planning for the health needs of an ageing population. In order to understand these effects, a unique Microsimulation Model, called Health&WealthMOD2030, was built to estimate the impacts of early retirement due to ill health on labour force participation, personal and household income, economic hardship (poverty), and government taxation revenue, spending and GDP in the years 2010, 2015, 2020, 2025 and 2030. This paper describes the construction of Health&WealthMOD2030. The Model captures the long term projections of demographic change, changing labour force participation patterns, real wages growth and trends in major illnesses affecting the older working age population. The base population of Health&WealthMOD2030 are the individuals aged 45-64 years with information on their work force status and health from the Australian Bureau of Statistics’ Surveys of Disability, Ageing and Carers (SDAC) 2003 and 2009. Projected estimates of income, taxation, income support payments, savings and superannuation from the National Centre for Social and Economic Modelling (NATSEM’s) dynamic Microsimulation Model Australian Population and Policy Simulation Model (APPSIM) were synthetically matched with the base population. Health&WealthMOD2030 project forward the economic impacts of early retirement from ill health to 2030. This will fill substantial gaps in the current Australian evidence of health conditions that will keep older working age Australians out of the labour market over the long-term.
Pamela M Mcmahon - One of the best experts on this subject based on the ideXlab platform.
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Microsimulation Model predicts survival benefit of radiofrequency ablation and stereotactic body radiotherapy versus radiotherapy for treating inoperable stage i non small cell lung cancer
American Journal of Roentgenology, 2013Co-Authors: Angela C Tramontano, Lauren E Cipriano, Chung Yin Kong, Joanne O Shepard, Michael Lanuti, Scott G Gazelle, Pamela M McmahonAbstract:OBJECTIVE. A subset of patients with stage IA and IB non–small cell lung cancer (NSCLC) is ineligible for surgical resection and undergoes radiation therapy. Radiofrequency ablation (RFA) and stereotactic body radiotherapy are newer potentially attractive alternative therapies. MATERIALS AND METHODS. We added RFA and stereotactic body radiotherapy treatment modules to a Microsimulation Model that simulates lung cancer's natural history, detection, and treatment. Natural history parameters were previously estimated via calibration against tumor registry data and cohort studies; the Model was validated with screening study and cohort data. RFA Model parameters were calibrated against 2-year survival from the Radiofrequency Ablation of Pulmonary Tumor Response Evaluation (RAPTURE) study, and stereotactic body radiotherapy Model parameters were calibrated against 3-year survival from a phase 2 prospective trial. We simulated lifetime histories of identical patients with early-stage NSCLC who were ineligible f...
Megan Passey - One of the best experts on this subject based on the ideXlab platform.
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the indirect costs of ischemic heart disease through lost productive life years for australia from 2015 to 2030 results from a Microsimulation Model
BMC Public Health, 2019Co-Authors: Deborah Schofield, Lennert Veerman, Robert Tanton, Megan Passey, Rupendra N Shrestha, Michelle Cunich, Simon KellyAbstract:Most studies measure the impact of ischemic heart disease (IHD) on individuals using quality of life metrics such as disability-adjusted life-years (DALYs); however, IHD also has an enormous impact on productive life years (PLYs). The objective of this study was to project the indirect costs of IHD resulting from lost PLYs to older Australian workers (45–64 years), government, and society 2015–2030. Nationally representative data from the Surveys of Disability, Ageing and Carers (2003, 2009) were used to develop the base population in the Microsimulation Model (HealthW and lost income tax revenue increased from AU$74 (US$71) million in 2015 to AU$117 (US$113) million in 2030 (58% increase). A loss of AU$785 (US$755) million in GDP was projected for 2015, increasing to AU$1125 (US$1082) million in 2030. Significant costs of IHD through lost productivity are incurred by individuals, the government, and society. The benefits of IHD interventions include not only improved health but also potentially economic benefits as workforce capacity.
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the long term economic impacts of arthritis through lost productive life years results from an australian Microsimulation Model
BMC Public Health, 2018Co-Authors: Deborah Schofield, Lennert Veerman, Robert Tanton, Simon Kelly, Rupendra N Shrestha, Michelle Cunich, Megan PasseyAbstract:While the direct (medical) costs of arthritis are regularly reported in cost of illness studies, the 'true' cost to indivdiuals and goverment requires the calculation of the indirect costs as well including lost productivity due to ill-health. Respondents aged 45-64 in the ABS Survey of Disability, Ageing and Carers 2003, 2009 formed the base population. We projected the indirect costs of arthritis using Health&WealthMOD2030 – Australia’s first Microsimulation Model on the long-term impacts of ill-health in older workers – which incorporated outputs from established Microsimulation Models (STINMOD and APPSIM), population and labour force projections from Treasury, and chronic conditions trends for Australia. All costs of arthritis were expressed in real 2013 Australian dollars, adjusted for inflation over time. We estimated there are 54,000 people aged 45-64 with lost PLYs due to arthritis in 2015, increasing to 61,000 in 2030 (13% increase). In 2015, people with lost PLYs are estimated to receive AU$706.12 less in total income and AU$311.67 more in welfare payments per week than full-time workers without arthritis, and pay no income tax on average. National costs include an estimated loss of AU$1.5 billion in annual income in 2015, increasing to AU$2.4 billion in 2030 (59% increase). Lost annual taxation revenue was projected to increase from AU$0.4 billion in 2015 to $0.5 billion in 2030 (56% increase). We projected a loss in GDP of AU$6.2 billion in 2015, increasing to AU$8.2 billion in 2030. Significant costs of arthritis through lost PLYs are incurred by individuals and government. The effectiveness of arthritis interventions should be judged not only on healthcare use but quality of life and economic wellbeing.
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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, 2014Co-Authors: Deborah Schofield, Rupendra Shrestha, Lennert Veerman, Robert Tanton, Simon Kelly, Megan PasseyAbstract:Policymakers in Australia, like in most OECD countries, have recognised the importance of early retirement due to ill health on individuals and families, as well as on the budget balance when planning for the health needs of an ageing population. In order to understand these effects, a unique Microsimulation Model, called HealthWealthMOD2030, was built to estimate the impacts of early retirement due to ill health on labour force participation, personal and household income, economic hardship (poverty), and government taxation revenue, spending and GDP in the years 2010, 2015, 2020, 2025 and 2030. This paper describes the construction of HealthWealthMOD2030. The Model captures the long term projections of demographic change, changing labour force participation patterns, real wages growth and trends in major illnesses affecting the older working age population. The base population of HealthWealthMOD2030 are the individuals aged 45-64 years with information on their work force status and health from the Australian Bureau of Statistics? Surveys of Disability, Ageing and Carers (SDAC) 2003 and 2009. Projected estimates of income, taxation, income support payments, savings and superannuation from the National Centre for Social and Economic Modelling (NATSEM?s) dynamic Microsimulation Model Australian Population and Policy Simulation Model (APPSIM) were synthetically matched with the base population. HealthWealthMOD2030 project forward the economic impacts of early retirement from ill health to 2030. This will fill substantial gaps in the current Australian evidence of health conditions that will keep older working age Australians out of the labour market over the long-term.
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health wealthmod2030 a Microsimulation Model of the long term economic impacts of disease leading to premature retirements of australians aged 45 64 years old
The International Journal of Microsimulation, 2013Co-Authors: Deborah Schofield, Lennert Veerman, Robert Tanton, Megan Passey, Simon Kelly, Rupendra N Shrestha, Michelle Cunich, Emily J CallanderAbstract:Policymakers in Australia, like in most OECD countries, have recognised the importance of early retirement due to ill health on individuals and families, as well as on the budget balance when planning for the health needs of an ageing population. In order to understand these effects, a unique Microsimulation Model, called Health&WealthMOD2030, was built to estimate the impacts of early retirement due to ill health on labour force participation, personal and household income, economic hardship (poverty), and government taxation revenue, spending and GDP in the years 2010, 2015, 2020, 2025 and 2030. This paper describes the construction of Health&WealthMOD2030. The Model captures the long term projections of demographic change, changing labour force participation patterns, real wages growth and trends in major illnesses affecting the older working age population. The base population of Health&WealthMOD2030 are the individuals aged 45-64 years with information on their work force status and health from the Australian Bureau of Statistics’ Surveys of Disability, Ageing and Carers (SDAC) 2003 and 2009. Projected estimates of income, taxation, income support payments, savings and superannuation from the National Centre for Social and Economic Modelling (NATSEM’s) dynamic Microsimulation Model Australian Population and Policy Simulation Model (APPSIM) were synthetically matched with the base population. Health&WealthMOD2030 project forward the economic impacts of early retirement from ill health to 2030. This will fill substantial gaps in the current Australian evidence of health conditions that will keep older working age Australians out of the labour market over the long-term.
Lennert Veerman - One of the best experts on this subject based on the ideXlab platform.
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the indirect costs of ischemic heart disease through lost productive life years for australia from 2015 to 2030 results from a Microsimulation Model
BMC Public Health, 2019Co-Authors: Deborah Schofield, Lennert Veerman, Robert Tanton, Megan Passey, Rupendra N Shrestha, Michelle Cunich, Simon KellyAbstract:Most studies measure the impact of ischemic heart disease (IHD) on individuals using quality of life metrics such as disability-adjusted life-years (DALYs); however, IHD also has an enormous impact on productive life years (PLYs). The objective of this study was to project the indirect costs of IHD resulting from lost PLYs to older Australian workers (45–64 years), government, and society 2015–2030. Nationally representative data from the Surveys of Disability, Ageing and Carers (2003, 2009) were used to develop the base population in the Microsimulation Model (HealthW and lost income tax revenue increased from AU$74 (US$71) million in 2015 to AU$117 (US$113) million in 2030 (58% increase). A loss of AU$785 (US$755) million in GDP was projected for 2015, increasing to AU$1125 (US$1082) million in 2030. Significant costs of IHD through lost productivity are incurred by individuals, the government, and society. The benefits of IHD interventions include not only improved health but also potentially economic benefits as workforce capacity.
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the long term economic impacts of arthritis through lost productive life years results from an australian Microsimulation Model
BMC Public Health, 2018Co-Authors: Deborah Schofield, Lennert Veerman, Robert Tanton, Simon Kelly, Rupendra N Shrestha, Michelle Cunich, Megan PasseyAbstract:While the direct (medical) costs of arthritis are regularly reported in cost of illness studies, the 'true' cost to indivdiuals and goverment requires the calculation of the indirect costs as well including lost productivity due to ill-health. Respondents aged 45-64 in the ABS Survey of Disability, Ageing and Carers 2003, 2009 formed the base population. We projected the indirect costs of arthritis using Health&WealthMOD2030 – Australia’s first Microsimulation Model on the long-term impacts of ill-health in older workers – which incorporated outputs from established Microsimulation Models (STINMOD and APPSIM), population and labour force projections from Treasury, and chronic conditions trends for Australia. All costs of arthritis were expressed in real 2013 Australian dollars, adjusted for inflation over time. We estimated there are 54,000 people aged 45-64 with lost PLYs due to arthritis in 2015, increasing to 61,000 in 2030 (13% increase). In 2015, people with lost PLYs are estimated to receive AU$706.12 less in total income and AU$311.67 more in welfare payments per week than full-time workers without arthritis, and pay no income tax on average. National costs include an estimated loss of AU$1.5 billion in annual income in 2015, increasing to AU$2.4 billion in 2030 (59% increase). Lost annual taxation revenue was projected to increase from AU$0.4 billion in 2015 to $0.5 billion in 2030 (56% increase). We projected a loss in GDP of AU$6.2 billion in 2015, increasing to AU$8.2 billion in 2030. Significant costs of arthritis through lost PLYs are incurred by individuals and government. The effectiveness of arthritis interventions should be judged not only on healthcare use but quality of life and economic wellbeing.
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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, 2014Co-Authors: Deborah Schofield, Rupendra Shrestha, Lennert Veerman, Robert Tanton, Simon Kelly, Megan PasseyAbstract:Policymakers in Australia, like in most OECD countries, have recognised the importance of early retirement due to ill health on individuals and families, as well as on the budget balance when planning for the health needs of an ageing population. In order to understand these effects, a unique Microsimulation Model, called HealthWealthMOD2030, was built to estimate the impacts of early retirement due to ill health on labour force participation, personal and household income, economic hardship (poverty), and government taxation revenue, spending and GDP in the years 2010, 2015, 2020, 2025 and 2030. This paper describes the construction of HealthWealthMOD2030. The Model captures the long term projections of demographic change, changing labour force participation patterns, real wages growth and trends in major illnesses affecting the older working age population. The base population of HealthWealthMOD2030 are the individuals aged 45-64 years with information on their work force status and health from the Australian Bureau of Statistics? Surveys of Disability, Ageing and Carers (SDAC) 2003 and 2009. Projected estimates of income, taxation, income support payments, savings and superannuation from the National Centre for Social and Economic Modelling (NATSEM?s) dynamic Microsimulation Model Australian Population and Policy Simulation Model (APPSIM) were synthetically matched with the base population. HealthWealthMOD2030 project forward the economic impacts of early retirement from ill health to 2030. This will fill substantial gaps in the current Australian evidence of health conditions that will keep older working age Australians out of the labour market over the long-term.
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health wealthmod2030 a Microsimulation Model of the long term economic impacts of disease leading to premature retirements of australians aged 45 64 years old
The International Journal of Microsimulation, 2013Co-Authors: Deborah Schofield, Lennert Veerman, Robert Tanton, Megan Passey, Simon Kelly, Rupendra N Shrestha, Michelle Cunich, Emily J CallanderAbstract:Policymakers in Australia, like in most OECD countries, have recognised the importance of early retirement due to ill health on individuals and families, as well as on the budget balance when planning for the health needs of an ageing population. In order to understand these effects, a unique Microsimulation Model, called Health&WealthMOD2030, was built to estimate the impacts of early retirement due to ill health on labour force participation, personal and household income, economic hardship (poverty), and government taxation revenue, spending and GDP in the years 2010, 2015, 2020, 2025 and 2030. This paper describes the construction of Health&WealthMOD2030. The Model captures the long term projections of demographic change, changing labour force participation patterns, real wages growth and trends in major illnesses affecting the older working age population. The base population of Health&WealthMOD2030 are the individuals aged 45-64 years with information on their work force status and health from the Australian Bureau of Statistics’ Surveys of Disability, Ageing and Carers (SDAC) 2003 and 2009. Projected estimates of income, taxation, income support payments, savings and superannuation from the National Centre for Social and Economic Modelling (NATSEM’s) dynamic Microsimulation Model Australian Population and Policy Simulation Model (APPSIM) were synthetically matched with the base population. Health&WealthMOD2030 project forward the economic impacts of early retirement from ill health to 2030. This will fill substantial gaps in the current Australian evidence of health conditions that will keep older working age Australians out of the labour market over the long-term.