Visualisation as exploratory science

15

Click here to load reader

Transcript of Visualisation as exploratory science

Page 1: Visualisation as exploratory science

Visualisation as Exploratory Science: The Role of Spatial Methods in Health and Disability Research

PresenterHamish Robertson

PhD CandidateAustralian Institute of Health Innovation

Faculty of MedicineUniversity of NSW

ENRGHI14

Page 2: Visualisation as exploratory science

Contents

• Introduction• Population ageing overview• Research focus and extension• Knowledge gaps: ageing and disability• Visualisation as exploratory science• Health and disability catch up• Conclusion

Page 3: Visualisation as exploratory science

Introduction

• Background in multicultural health and ageing research including Aboriginal ageing

• Converted from Masters to a PhD programme in 2012• Focus on aspects of population ageing including

politics, policy, demography etc• Interest in GIS and systems that accommodate real-

world complexities including temporal and dynamic • Critical emphasis, not just reproduction of the field• Active presentation agenda – national, regional and

international• This is an overview with some commentary – hopefully

useful and possibly interesting

Page 4: Visualisation as exploratory science

Research Focus

What will be the localised effects of age-related diseases (specifically AD) across New South Wales on communities and (current) health and social support systems?

Doing this through:- simulation (system dynamics);- spatialisation (GIS);- visualisation (Google Earth).

Page 5: Visualisation as exploratory science

PhD Research Structure

• Major components:– Demographic modelling– Epidemiological modelling – condition + severity– Cost of care sub-model (possible)

e.g. annualised cost of RACF and community-based care options

– Spatial modelling – distribution and scale issues– Spatial analysis (against existing infrastructure)– Visualisation and exploration– What-if analyses e.g. if x and we do y, what result

might we expect to see?

Page 6: Visualisation as exploratory science

Global Population and Health Trends

• Falling population growth and fertility rates (mostly) – some exceptions, others speeding up

• Rising older populations – totals and proportion• More elderly people living alone in the community• Rising numbers with chronic diseases• Rising numbers with disability• Rising numbers with neuroepidemiological (brain)

conditions (dementias, motor and gait problems)• Complexity of the theory and epidemiology of age

and ageing (genetic, physiological, biological, psycho-social, cultural, definitional etc)

Page 7: Visualisation as exploratory science

Population Ageing is a Global Phenomenon

Page 8: Visualisation as exploratory science

Significant Data Limitations Ferri et al, (2005) “Global prevalence of dementia: a Delphi consensus study”, The Lancet

Page 9: Visualisation as exploratory science

ADI Global Consensus RatesSource: Alzheimer’s Disease International Fact Sheet 2008

Page 10: Visualisation as exploratory science

Issues with Modelling Prevalence

• The dementias in general and AD in particular• Differential rates including sub-types vary by

location – non-uniform distributions• Quality and currency of population data • Coverage in low resource and/or conflict settings• Global population and prevalence estimations• Dynamic variables such as rates by sub-type,

diagnosis, educational levels, economic capacity, training, workforce, safety in the field etc

• Population-level knowledge versus clinical studies versus informed estimates

Page 11: Visualisation as exploratory science

Cohort-Specific Ageing in Australia2006-2021 and 2006-2031

Source: Australian Innovation System Report 2012

Page 12: Visualisation as exploratory science

Knowledge Gaps: Ageing and Disability

• Many studies are sample-based only – no universal data on prevalence or incidence of specific conditions e.g. Alzheimer’s disease

• Some global estimates are Delphi-based i.e. informed ‘guesstimates’ by a panel of experts

• Many conditions have mixed aetiologies – correlate data good but causal chain poor

• Non-linearity an issue with population-level projections e.g. recent research on dementia rates suggests rising and falling possible

Page 13: Visualisation as exploratory science

Visualisation as Exploratory Science• Started presenting internationally and found a complete lack of familiarity

with spatial analysis and representation – similar in social policy etc• Adding a spatial dimension to modelling activities is useful and interesting

for mixed audiences who may not share professional backgrounds, methods etc

• Started trialling basic models of AD for Australia, New Zealand etc• Then applied basic concepts to Africa using LandScan data set – example

in KML format• Now moving into the disability sector where GIS etc also (mostly) poorly

understood and applied• As mentioned, disability and ageing correlate well but politics of disability

may be an issue (identity versus functional impairment or adjustment)• Spatial modelling and visualisation extend basic demographic-

epidemiological estimates and can add scale and distribution patterns to our understanding of poorly understood diseases and their impact

Page 14: Visualisation as exploratory science

Health and Disability (Need to) Catch Up

• Spatial literacy low in much of the health and disability sciences + planning + policy + business practices

• Significant information gaps in both health and disability sectors e.g. gender, diversity etc

• Emphasis on technology often exceeds scientific understanding i.e. they like new things

• New technology has its own consequences (Tenner etc), often unplanned for entirely – positive emphasis dominates

• Complexity of health and disability makes spatial perspective central but it remains marginal

• Claims to ‘evidence-based’ planning and implementation need to be checked against actual and potential effects

• Ageing will affect both health and disability domains in significant ways but many policy responses avoid close examination of localised impacts.

Page 15: Visualisation as exploratory science

Conclusion

• Many aspects of health and disability are patterned spatially because of social structures, policies and processes

• Population ageing will have a huge global impact until at least 2050 – hyper-ageing of societies

• Many age-related conditions lack good data at the global level and below – emphasis on MDG diseases

• Spatial science and technology plus geographic theory have a potential contribution to make (I think a significant one but…)

• Health and medical geography (HMG) should be central to policy-level responses and below – science often quite selective

• Critical HMG has a role to play in critiquing public and private sector responses to these issues and adding to the potential of advocacy and related organisations and their work