Modified slides from a conference presented in New Zealand in 2014.

1. The Geography of Alzheimer's Disease
in New Zealand:
A Spatial Epidemiology
Authors
Hamish Robertson
Nick Nicholas
A/Prof Joanne Travaglia
A/Prof Tuly Rosenfeld

2. Contents
• Introduction
• The dementias in New Zealand
• A spatial model
• Mapping the dementias
• Spatial visualisation
• Dementia sub-types
• Service infrastructure
• Conclusion
• Future developments

3. 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

4. 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

6. 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

7. 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…

8. 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

10. Estimated
Prevalence
2001
By Ward

11. Estimated
Prevalence
2006
By Ward

12. Estimated
Prevalence
2013
By Ward

13. Other Forms of Visual Engagement
Tree Mapping the Same Data

14. 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

15. Localised Prevalence Changes Over Time

16. 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

17. Estimated Costs by Ward

18. 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?

19. The Dynamics of Service Provision and Demand
Source: NZ Ministry of Health 2004 report via Joyce De La Torre on Academia.edu

20. Impact on Acute Hospitals by Distance

21. 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

22. 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

23. 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

24. 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

25. New Zealand Maptitude Bundle