Keep on keeping on: predicting who will be able to work until they are 70 years old

[Extract] The Federal Government announced in its 2015 budget that, in addition to increasing the age of eligibility for the Age Pension to 67 years by 2023, it plans to further increase the age of eligibility to 70 years by 2035[1]. The economic drivers for this policy were emphasised twelve months earlier in the National Commission of Audit Report (2014): Once the impacts of an ageing population and expected lower growth prospects in the longer term are taken into account a growing fiscal gap will emerge at all levels of government across Australia if current expenditure and revenue policies remain unchanged.… Today we have five people working for every one retired person, by 2050 we will only have 2.7[2]. Justification for increasing the age of eligibility for the Age Pension has centred on increasing longevity and related costs of pension payments and health and aged care. Treasury’s 2015 Intergenerational Report (IGR) highlighted this point, stating: “A greater proportion of the population will be aged 65 and over. The number of Australians in this age group is projected to more than double by 2054-55 compared with today” and thus the Government has also implemented policies to increase the labour force participation of older Australians[3]. However, the capacity of people to work until the age of 70 not only depends on the availability of incentives and employment opportunities but their health capacity to do so. Although the Australian population is living longer, there is evidence that they are not a healthier population (Productivity Commission report on An Ageing Australia, 2014)[4]. We estimated there are 512,700 people aged 65-69 years who will be in the labour force. Of these, 500,600 are projected to be able to keep working until the age of 70 (312,600 in full-time and 188,000 in part-time) and 97,700 who will not be able to work due to their ill-health. We also estimated the effects (and ranking) of the individual’s main chronic condition on their probability of participating in the workforce, where arthritis, back problems and other diseases of the musculoskeletal system were the top three conditions that would keep most people out of the labour force. The fundamental role of health in enabling labour force participation has, and will continue to be, a key concern for policymakers. For example, the Council of Australian Governments’ (COAG) current agenda for human capital and mature-age employment states that: “The foundation of the nation’s human capital is the health of its people. A strong economy requires a healthy current and future workforce”[5]. The current project provides much needed information about how many people will have the health capacity to work beyond the age of 65

Projecting the impacts of illness on labour force participation: An application of Health&WealthMOD

Health&WealthMOD is the first Australian microsimulation model designed to determine the economic impacts of disease on older workers, aged 45 to 65 years. Chronic health conditions are known to be associated with early retirement. This paper describes an application of Health&WealthMOD to estimate the impact of this association on projected labour force participation to 2020 given the ageing population and long-term trend in chronic conditions. Due to ageing and disease trends, the number of people with chronic conditions in the 45-64 years age group was expected to rise to about 4.8 million by 2020, an increase of 82% from the 2003 population of the same age group. About 904,000 persons in the 45-64 age group were projected to be out of the labour force due to ill health in 2020, when only the ageing and population growth were considered. When trends in illness were captured, the figure was increased to about 1.2 million persons. This demonstrates that health is a major driver of labour force participation and retirement and that economic policies alone, with no consideration of health interventions to treat or prevent chronic illness, will only have a limited impact on labour force participation. Thus, it is important that the government focuses on both health policies and economic policies in order to make sure that there will be an adequate supply of labour force in future.impacts of illness, labour force, participation, Health&WealthMOD

Case Studies - Health&WealthMOD: a microsimulation model of the economic impacts of diseases on older workers

The Australian Government is seeking to encourage older workers to remain in the labour force longer to overcome future labour shortages and ensure adequate taxation revenue to fund the needs of an ageing population. Longer labour force participation also has benefits to individuals in terms of available income and capacity to save for a better standard of living in retirement. While the Government recognises that not all older workers are able to participate in the labour force, there is little information on what health conditions keep people from working, or what the costs are to the government or the individual. This case study outlines how a new micro simulation model, Health&WealthMOD, is being designed to fill this information gap by estimating the economic impacts of illness. The general approach adopted is outlined, following which two early applications of the model are presented. The model is used to explore the determinants of the duration spent in retirement and to generate projections of retirement due to illness to 2020.health; disability; wealth; retirement period

Detection of Latent HIV-1 Infection and Drug Resistant Mutation Testing in Nepal: HIV-1 env V3 DNA Sequence and RT Gene (M184V) Mutation

HIV-1 resistance to antiretroviral therapy (ART) is a crucial issue, despite various effective drugs are available for the treatment. Although the viral RNA is suppressed below the detection limit (<50 copies/ml) with the use of potent antiviral drugs, the mutation can be archived in the cellular reservoir as proviral DNA. The detection of proviral DNA and mutation screening in HIV 1 RNA for genotypic resistance is the sole basis for monitoring the effectiveness of ART. Our study aim to access the extent of latent HIV infections by detecting env V3 DNA and also testing of M184V (meth184val; ATG - GTG substitution at 184th codon) specific mutations in HIV-1 RT gene to monitor the effectiveness of ART. The HIV-1 env V3 DNA sequence was amplified using multiple upstream and downstream primes to show the latent HIV infections, whereas polymerase chain reaction- restriction fragment digestion assay (PCR-RFDA) was used for testing M184V mutation in HIV-1 RT gene. In the study, out of 15 HIV infected patient blood samples, 12 shows amplification of env V3 DNA, confirming the latent HIV infections while 3 were negative for env V3 DNA. HIV-1 RT gene tested for M184V mutation in all 15 samples showed wild type after analysis using PCR-RFDA. After digestion with CviAII, three bands were observed in wild type whereas in mutant only two bands. Although the study shows negative for the M184V resistance mutation, screening of various panels of drug resistance mutations should be performed in recently infected HIV-1 patients for planning the effective ART strategy. The data is not enough to compare the overall scenario of the Nepal thus warrant urgency for large scale study with standard genotypic tools

Modelling the cost of ill health in Health&WealthMOD (Version II): lost labour force participation, income and taxation, and the impact of disease prevention

This paper provides a detailed description of the construction of Health&WealthMOD (Version II). It is Australia’s only microsimulation model of health and illness and their impacts on labour force participation, income, wealth and government revenue and expenditure. In this paper, we describe Health&WealthMOD (Version II) and its architecture, the application of the model, and some of the results it has produced.Health&WealthMOD, cost of ill health, lost labour force participation, income, taxation, disease prevention

The Personal and National Costs of Lost Labour Force Participation Due to Arthritis: An Economic Study

Background: The costs of arthritis to the individuals and the state are considerable.\ud \ud Methods: Cross-sectional analysis of the base population of Health&WealthMOD, a microsimulation model of 45 to 64 year old Australians built on data from the Australian Bureau of Statistics' Survey of Disability, Ageing and Carers and STINMOD, an income and savings microsimulation model.\ud \ud Results: Individuals aged 45 to 64 years who had retired early due to arthritis had a median value of AU$260 in total weekly income whereas those who were employed full time were likely to average more than five times this. The large national aggregate impact of early retirement due to arthritis includes AU$9.4 billion in lost GDP, attributable to arthritis through its impact on labour force participation.\ud \ud When looking at the ongoing impact of being out of the labour force those who retired from the labour force early due to arthritis were estimated to have a median value of total savings by the time they are 65 of as little as $300 (for males aged 45–54). This is far lower than the median value of savings for those males aged 45–54 who remained in the labour force full time, who would have an estimated$339 100 of savings at age 65.\ud \ud Conclusions: The costs of arthritis to the individuals and the state are considerable. The impacts on the state include loss of productivity from reduced workforce participation, lost income taxation revenue, and increased government support payments – in addition to direct health care costs. Individuals bear the economic costs of lost income and the reduction of their savings over the long term

The Economic Impacts of Illness in Older Workers: Quantifying the impact of illness on income, tax revenue and government spending

Background: Long term illness has far reaching impacts on individuals, and also places a large burden upon government. This paper quantifies the indirect economic impacts of illness related early retirement on individuals and government in Australia in 2009.\ud \ud Methods: The output data from a microsimulation model, Health&WealthMOD, was analysed. Health&WealthMOD is representative of the 45 to 64 year old Australian population in 2009. The average weekly total income, total government support payments, and total taxation revenue paid, for individuals who are employment full-time, employed part-time and not in the labour force due to ill health was quantified.\ud \ud Results: It was found that persons out of the labour force due to illness had significantly lower incomes ($218 per week as opposed to$1167 per week for those employed full-time), received significantly higher transfer payments, and paid significantly less tax than those employed full-time or part-time. This results in an annual national loss of income of over $17 billion, an annual national increase of$1.5 billion in spending on government support payments, and an annual loss of $2.1 billion in taxation revenue.\ud \ud Conclusions: Illness related early retirement has significant economic impacts on both the individual and on governments as a result of lost income, lost taxation revenue and increased government support payments. This paper has quantified the extent of these impacts for Australia

Histomorphologic Profile of Skin Tumors

Introduction: Skin tumors are not uncommon in the Nepalese community. Accurate diagnosis and categorization of these into different types is important because of its effect on prognosis and management. We conducted this study to find out the frequency of different histological types of skin tumors, correlate with their clinicopathologic profile and to determine the stage of malignant tumors. Methods: This is a descriptive cross-sectional study of skin tumors during the period February 2015 to January 2017. All the patients who were subjected to skin biopsy for skin tumors were included in this study. The biopsies taken were fixed in 10% formalin and then processed. Four microns thick sections were taken and stained with Haematoxylin and Eosin stain (H&E). Results: Total of 108 cases of skin tumors were included of which 68 (62.97%) cases were histologically diagnosed as benign and 40 (37.03%) cases were diagnosed as malignant tumors. Keratinocytic tumors were predominant among both benign and malignant skin tumors. Conclusions: Histopathological examination is the gold standard for accurate diagnosis and prognostic assessment of the patient. Staging of the malignant tumors in excision biopsy specimen needs to be emphasized since it is a predictor of prognosis