Alzheimer’s and other dementias in Canada, 2011 to 2031: a microsimulation Population Health Modeling (POHEM) study of projected prevalence, health burden, health services, and caregiving use

Dujovny, Manuel; Garner, Rochelle; Finès, Philippe; Bancej, Christina; Flanagan, W. Michael; Tu, Karen; Reimer, Kim; Chambers, Larry W.; Bernier, Julie

doi:10.1186/s12963-016-0107-z

Cited by 56 publications

(48 citation statements)

References 20 publications

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“…This involves modelling the aggregate flows of older people between age groups and dementia states. 28 A key advantage of macro-simulation over the simpler extrapolation approach is that more nuanced alternative scenarios of changing incidence and mortality can be considered.…”

Section: Methodsmentioning

confidence: 99%

“…Relative mortality rates are elevated for younger dementia cases with little difference in the oldest age categories. 28 42 46 47 In this study, the relative mortality for 65 year old age cohorts is selected from a range of 2 to 5 28 , and allowed to decay with age such that the overall relative mortality rate for people with dementia is twice that of the non-dementia population. We assume that the relationship between dementia and non-dementia mortality RM i is allowed to vary by age but is constant over time.…”

Section: Methodsmentioning

confidence: 99%

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Generating national projections of dementia cases for Ireland using a calibrated macro-simulation model

2020

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IntroductionEpidemiological data on dementia is not available in many European countries and regions due to the high cost and complexity of conducting large scale dementia screening studies. The available epidemiological studies identify potentially substantial variation in the prevalence of dementia over time and across Europe.MethodsIn this paper we generate simulations of the number of dementia cases in Ireland from 1991 to 2036 using a three-state Markov illness-death model. Parameters values are selected for each simulation from a range using a random parameter search pattern. We employ a novel calibration method which exploits the strong relationship between dementia, ageing and mortality. Simulation weights are generated based on differences between observed and modelled cohorts of older people and the reported number of deaths from dementia. Irish Census data from 1991 to 2016 and the number of recorded deaths due to dementia in 2018 are used as calibration points. A weighted average projection of the number of dementia cases is generated.ResultsWe estimate a weighted average number of cases of dementia in 2016 of 54 877 increasing to 98 946 in 2036; this estimate is substantially lower than the estimates generated using extrapolation methods. We show the wide range of possible outcomes given the range in the available parameter estimates and show that irrespective of whether the incidence rate of dementia is declining the number of cases of dementia is rapidly increasing due to population ageing.ConclusionPrevious studies have used parameter estimates from meta-analyses of the literature or from individual studies. In this paper we supplement these with a calibration approach using observed cause of death and population age structure data. These additional sources of data can be used to generate estimates of dementia prevalence in any country or region which has census data and data on deaths due to dementia.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Generating national projections of dementia cases for Ireland using a calibrated macro-simulation model

2020

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“…Most projections of the prevalence of dementia, including those of ADI [36], are obtained by macro-simulation, where population projections by age are multiplied by age-specific prevalence of the disease. An important study at Statistics Canada has used, instead, a population-based longitudinal micro-simulation approach [39, 40]. This starts with the census population, including each person’s characteristics, and projects each person forward year-by-year as they are exposed to various risks, until their departure from the population (death or emigration).…”

Section: A Micro-simulation For Canada: Prevalence Incidence Costsmentioning

confidence: 99%

Screening for Dementia Caused by Modifiable Lifestyle Choices Using Hybrid PET/MRI

Prato

Pavlosky

Foster

et al. 2019

ADR

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Significant advances in positron emission tomography (PET) and magnetic resonance imaging (MRI) brain imaging in the early detection of dementia indicate that hybrid PET/MRI would be an effective tool to screen for dementia in the population living with lifestyle risk factors. Here we investigate the associated costs and benefits along with the needed imaging infrastructure. A demographic analysis determined the prevalence of dementia and its incidence. The expected value of the screening program was calculated assuming a sensitivity and specificity of 0.9, a prevalence of 0.1, a QALY factor of 0.348, a willingness to pay $114,000 CAD and the cost per PET/MRI scan of $2,000 CAD. It was assumed that each head PET/MRI could screen 3,000 individuals per year. The prevalence of dementia is increasing by almost two-fold every 20 years due to the increased population at ages where dementia is more prevalent. It has been shown that a five-year delay in the incidence of dementia would decrease the prevalence by some 45%. In Canada, a five-year delay corresponds to a health care savings of $27,000 CAD per subject per year. The expected value for screening was estimated at $23,745 CAD. The number of subjects to be screened per year in Canada, USA, and China between 60 and 79 was 11,405,000. The corresponding number of head-only hybrid PET/MRI systems needed is 3,800. A brain PET/MRI screening program is financially justifiable with respect to health care costs and justifies the continuing development of MRI compatible brain PET technology.

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“…With the aging of the population [1,2], there is increasing attention being paid to older adult driving. On one hand, older adults remain healthier when they are physically, cognitively and socially active [3,4], all of which are facilitated when they stay driving [5].…”

Section: Introductionmentioning

confidence: 99%

Naturalistic Driving: A Framework and Advances in Using Big Data

2018

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Abstract:Driving is an activity that facilitates physical, cognitive, and social stimulation in older adults, ultimately leading to better physical and cognitive health. However, aging is associated with declines in vision, physical health, and cognitive health, all of which can affect driving ability. One way of assessing driving ability is with the use of sensors in the older adult's own vehicle. This paper provides a framework for driving assessment and addresses how naturalistic driving studies can assist in such assessments. The framework includes driving characteristics (how much driving, speed, position, type of road), actions and reactions (lane changes, intersections, passing, merging, traffic lights, pedestrians, other vehicles), destinations (variety and distance, sequencing and route planning), and driving conditions (time of day and season). Data from a subset of Ottawa drivers from the Candrive study is used to illustrate the use of naturalistic driving data. Challenges in using naturalistic driving big data and the changing technology in vehicles are discussed.

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Alzheimer’s and other dementias in Canada, 2011 to 2031: a microsimulation Population Health Modeling (POHEM) study of projected prevalence, health burden, health services, and caregiving use

Cited by 56 publications

References 20 publications

Generating national projections of dementia cases for Ireland using a calibrated macro-simulation model

Generating national projections of dementia cases for Ireland using a calibrated macro-simulation model

Screening for Dementia Caused by Modifiable Lifestyle Choices Using Hybrid PET/MRI

Naturalistic Driving: A Framework and Advances in Using Big Data

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