The Geography of Alzheimer's in New Zealand
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Transcript of The Geography of Alzheimer's in New Zealand
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The Geography of Alzheimer's Disease in New Zealand:
A Spatial Epidemiology
AuthorsHamish Robertson
Nick NicholasA/Prof Joanne TravagliaA/Prof Tuly Rosenfeld
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Contents
• Introduction
• The dementias in New Zealand
• A spatial model
• Mapping the dementias
• Spatial visualisation
• Dementia sub-types
• Service infrastructure
• Conclusion
• Future developments
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Introduction
• We keep on saying this – location matters and more so as populations age!
• Information systems need to reflect the world people live, work and survive in
• Geography is central to understanding social policy predicaments because nothing is uniformly distributed – quantity and quality
• Spatial science goes beyond geography to include a variety of approaches centered on space/place relations
• The distribution of health, illness, people and health systems will always be spatially patterned
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The Dementias in New Zealand
• Population ageing – NZ still fairly young population compared to many countries -> specific groups, differential ageing and locational issues
• Context - growing international knowledge but still far from complete – ADI, WHO etc
• Signs of dynamic variation in prevalence rates e.g. Denmark, the UK and Australia
• Limited information base in New Zealand but this will improve in time
• 2008 paper by Tobias et al – Burden of Alzheimer's disease: population-based estimates and projections for New Zealand, 2006-2031
• 2012 report update by Access Economics for Alz NZ
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The Role of Geographic Knowledge• Situations vary be location because populations (social and biological) and
environments vary by location
• Geography supports physical/social system complexity and applied technology (e.g. GIS, GPS, virtual earth, simulation etc)
• Scale is an important factor often missed in modelling activities e.g. often assume sameness up and down in complex systems but this is very problematic (also Boje on systemicities)
• Need to consider interdisciplinarity for coping better with and understanding ageing – not just medicine or health sciences exclusively -> meta-science of ageing
• Most service providers need to understand ageing better – health, finance, social services, legal, police, transport etc
• Ageing is both personal and collective, highly local and globally important – geography helps link these conceptually and practically
• Ageing is (also) a space-place experience – as personal experience will attest
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A Spatial Model
• Prior developmental work presented in 2012
• Modelling updated with 2013 NZ Census, AD estimate data and GIS software
• Maptitude GIS software – NZ (maps) geography and population data in the one package -> low learning curve and cheap too!
• Illustration of these issues using basic prevalence estimates and 2013 Census data
• NB - not just technology for its own sake…
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Official Geographic Boundaries in New Zealand
• meshblock boundaries
• area unit boundaries.
• general and Māori electoral district boundaries
• regional council boundaries
• territorial authority boundaries
• ward boundaries - in these examples mostly
• community boards and local board boundaries
• BUT you can also create your own geographies as well – map community or group perceptions
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Estimated Prevalence 2001By Ward
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Estimated Prevalence 2006By Ward
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Estimated Prevalence 2013By Ward
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Other Forms of Visual EngagementTree Mapping the Same Data
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Scale Factors for Different Audiences
• Keynes said governments don’t like too much information because it makes their decisions harder (!)
• The experience of ageing will differ by location e.g. access to appropriate/quality services, quality/experience/availability of staff, choice, family, community etc
• Sometimes larger places are better, sometimes smaller ones – varies by factor e.g. formal services versus informal care and support
• Scale is central to mapping because the results people perceive change with scale – e.g. global versus neighbourhood
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Localised Prevalence Changes Over Time
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Costing Shifts in Changing Epidemiology
• Shifting dynamics of public versus private service provision (NFP, personal, group?)
• Composition and management vary in significant ways globally
• Philosophical and political debates about who pays for what (if you can buy it)
• Implicit rationing in much of the health and social support system – who gets access to what?
• Costs can be dynamic over time – not just linear
• Impacts of different services can vary over time
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Estimated Costs by Ward
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Some Service Infrastructure Issues
• Demand will differ by location – geography and scale will matter
• Will we have enough facilities, places and people to service demand now and into the future?
• Where will these issues be lesser or greater and what patterns are we likely to see?
• What will be the downstream impacts on services and suppliers?
• What will we do in places where more skilled people won’t live and work?
• What should we be doing now for those future events?• What options do we need to plan for now and trial/test for
future scenarios?• What will we use the facilities/people for when population
ageing peaks?
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The Dynamics of Service Provision and Demand
Source: NZ Ministry of Health 2004 report via Joyce De La Torre on Academia.edu
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Impact on Acute Hospitals by Distance
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Spatial Visualisation
• Visualisation is increasingly central to information sharing and access
• Broad audiences and the public may not share the same understanding of an issue – visualisation adds value to these often complex situations
• Dashboards and other visual formats are increasing in health informatics
• Spatial data representation methods are rising rapidly e.g. qualitative software, Tableau, data mining packages etc
• No longer an expert domain – open source etc
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Dementia Sub-Types
• We can estimate and map (spatially model) sub-types – AD, VaD, DLB, mixed dementias and so on
• Ageing is likely to produce new/emerging conditions just because of the sheer numbers of very old people
• Service issues associated with sub-types can then be modelled e.g. acute, sub-acute, specialist etc
• As data improves assumptions can be tested and revised to better support what is actually happening
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Conclusion
• Dementia and sub-types represent a highly dynamic aspect of the epidemiology of ageing and flow-on effects
• High investment socially, economically and politically
• Spatial technology is moving very fast and supports complexity work – not a replacement but an addition
• Visuo-spatial methods can inform and support the many people and professions involved in population ageing and its consequences
• Also these techniques are increasingly accessible, interesting and useful
• Good science makes use of what is available and works
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Future Developments
• Mapping incidence by address/location• Refining and combining prevalence estimates and
incidence data -> spatial data mining applications• Expand options for visualisation and access by a
broad audience• Building systems for knowledge integration – not
just more data collection in silos• Advance ‘what if’ modelling for trends and
options• Ethics of knowledge and care will expand i.e. if we
hold/possess knowledge and don’t act or advocate in the interests of the community
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New Zealand Maptitude Bundle