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A computer model of dementia prevalence in Australia: foreseeing outcomes of delaying dementia onset, slowing disease progression, and eradicating dementia types.

机译:澳大利亚痴呆症患病率的计算机模型:预见延迟痴呆症发作,减慢疾病进展和消除痴呆症类型的结果。

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BACKGROUND: A computer model was designed to test hypothetical scenarios regarding dementia prevalence in Australia (2001-2040). METHODS: The study implemented 3 scenarios: delaying dementia onset, slowing disease progression and, in a previously unpublished experiment, eradicating dementia types. Sensitivity analysis and parameter variation were the main methods of experimentation. RESULTS: The model predicts that delaying dementia onset by 5 years will reduce the 2040 prevalence by 37%. An onset delay of 2 years, introduced in 2010, will reduce the 2040 prevalence by 16%. Slowing disease progression increases the 2040 prevalence by 4-7%. Total eradication of Alzheimer's disease (currently approximately 50% of all dementia cases) in 2020 will decrease the 2040 prevalence by 42%. CONCLUSION: Computer modeling of future scenarios and interventions helps health and aged care planners understand the likely challenges society will face with the ageing of the world's population.
机译:背景:设计了一种计算机模型来测试有关澳大利亚(2001-2040年)痴呆症患病率的假设情景。方法:该研究实施了3种情况:延迟痴呆发作,减慢疾病进程以及在以前未发表的实验中消除痴呆类型。灵敏度分析和参数变化是主要的实验方法。结果:该模型预测,痴呆症的发作延迟5年将使2040年的患病率降低37%。从2010年开始推迟2年发病,将使2040年的患病率降低16%。疾病进展缓慢会使2040年的患病率增加4-7%。到2020年完全根除阿尔茨海默氏病(目前约占所有痴呆症病例的50%)将使2040年的患病率降低42%。结论:对未来情景和干预措施的计算机建模可帮助卫生保健和老年护理计划制定者了解社会随着世界人口老龄化而可能面临的挑战。

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