Geospatial Methods
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Geospatial Methods

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Geospatial Methods Geospatial Methods Presentation Transcript

  • Using maps and spatial analysis to inform global health decision making Peter Speyer Director of Data Development @peterspeyer / speyer@uw.edu UNIVERSITY OF WASHINGTON
  • Institute for Health Metrics and Evaluation • Independent research center at the University of Washington • Core funding by Bill & Melinda Gates Foundation and State of Washington • 160 faculty, researchers and staff • Providing independent, rigorous, and scientific measurement and evaluations • “Our goal is to improve the health of the world’s populations by providing the best information on population health”
  • The Global Burden of Disease Study • A systematic scientific effort to quantify the comparative magnitude of health loss due to diseases, injuries, risk factors • Created 1993, commissioned by the World Bank • GBD 2010 covers 291 causes, 67 risk factors in 187 countries for 1990, 2005 and 2010 by age and sex • GBD country hierarchy 7 super-regions and 21 regions, based on geographic proximity and epidemiological profiles with • Almost 600 country, disease and risk factor experts from 80+ countries 3
  • 21 GBD regions 4
  • Measuring burden of diseases and injuries Health Disability Weight YLDs YLDs Deaths YLLs (Years of Life Lost) YLDs (Years Lived with Disability) YLLs DALYs (Disability-Adjusted Life Years) Age Death Average life expectancy 5
  • GBD process & spatial challenges Find & manage data Analyze data • Standards • Missing data • Coverage • Missing values • Representativeness • Geographies over time Get data used • Interactive visualizations • Mapping • Making data actionable 6
  • GBD process & spatial challenges Find & manage data Analyze data • Standards • Missing data • Coverage • Missing values • Representativeness • Geographies over time Get data used • Interactive visualizations • Mapping • Making data actionable 7
  • Data inputs Population based • Surveys • Censuses • Vital registration • Verbal autopsy • Disease registries Encounter level • Hospital / ambulatory / primary care records • Claims data Other • Literature reviews • Sensor data • Mortuaries / burial sites • Police records • Surveillance systems 8
  • Global Health Data Exchange (http://www.ghdx.org) 9
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  • GBD process & spatial challenges Find & manage data Analyze data • Standards • Missing data • Coverage • Missing values • Representativeness • Geographies over time Get data used • Interactive visualizations • Mapping • Making data actionable 14
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  • GBD covariates and risk factors • 300+ covariates, e.g. GDP per capita, access to water & sanitation, education • Gridded population used for several covariates (incl. AfriPop, AsiaPop, AmeriPop) – Population in coastal areas – Population weighted average elevation, rainfall, temperature – Population density – Population at risk for causes like malaria • Ambient air pollution, ambient ozone pollution (satellite, surface monitor, TM5 global atmospheric chemistry transport model) 16
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  • • Show GBD Compare map for risk factors – Ambient air pollution 18
  • GBD – spatial-temporal regression • Capture more information than simple covariate models • Use weighted average of residuals, based on distance in time, age and space • Geographic weights based on GBD regional hierarchy (country/region/super-region) • Vary weights based on data availability to increase/decrease smoothing 19
  • Add graph from COD Viz 20
  • GBD process & spatial challenges Find & manage data Analyze data • Standards • Missing data • Coverage • Missing values • Representativeness • Geographies over time Get data used • Interactive visualizations • Mapping • Making data actionable 21
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  • Small area estimation • Analyze health patterns outcomes and intervention coverage for 72 districts in Zambia • Most data only representative at country/province level • Modeling approaches – Pooling data over several years – Borrowing strength by exploiting spatial correlations – Using covariates • Add validation environment – Identify most appropriate measurement strategy – Establish minimum sample size for future data collection 27
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  • Remaining tasks and challenges • Add more spatial covariates • Conduct burden study at sub-national level • Identify best practices for managing geographies (national, subnational) globally over time • Is there a portal for gridded data? 34