| Term | Definition |
|---|
| Medical/Health geography | the application of geographical perspectives and methods to the study of health, disese and health care, study of spatial variations in human health, and the study of spatial variations in all kinds of health care, formal, and informal |
| rationale - Why GIS and spatial analysis are used in public health studies (3 reasons) | 1) population living in plaaces with disease outbreaks experiences increased exposure to a risk agent (ex: air pollutant) 2) population living there is more susceptible (ex: elderly, poor), 3) can also suggest how the population adapts to its environment |
| relationship between GIS and spatial analysis | association of disease with place |
| poor, elderly | populations that are more susceptible to diseases |
| attributes | measured in different scales - nominal, ordinal, interval, ratio |
| location | measured in coordinate system |
| attributes and location | spatial analysis brings ___and___ together |
| attributes and location | spatial data has two components |
| cholera | Snow'sstudy of __ in 1855 illustrated many important concepts in spatial analysis |
| geography of susceptibility and the geography of exposure | the combination of there two geography factors lead to geography of risk |
| susceptibility, exposure, adaptation | the combinations of these three factors lead to health risk |
| GIS | geographical information systems |
| geographic information systems | 1) spatial database 2) relate points, areas, and lines, and sometimes surfaces to each other 3) add layers of data 4) assess spatial relationships |
| 1) seeing the data - important to medically trained people used to mapping the "body" 2) integration of numerous data 3) interactivity in the analysis 4) ability to use large data sets - critical when effected areas are small 5) increased speed of delivery 6)leads to novel questions and more of them | why GIS in spatial health analysis |
| visualization and exploration | classification schema is through __and__ |
| visualization | mapping otherwise aspatial data (ex: mortality rates) |
| exploration | overlay and cluster analysis |
| 1) enormous increase in GIS for epidemiology and public health research 2) increasing complixity of analysis 3) web based distribution growing | trends in relationship between GIS and public health research |
| visualization, exploration, and modelling | types of spatial analysis |
| visualization of risks. pollution, and covariates | stage 1 of spatial analysis |
| exploration using Boolean overlays | stage 2 of spatial analysis |
| modelling of spatial dependence nd association | stage 3 of spatial analysis |
| visualization | viewing attribute data in map format |
| 1) often suggestive of relationships and hypotheses 2) can educate public and officials | strengths of visualization |
| open to abuse with cartographic tricks (the art or technique od making maps or charts) 2) can be misinterpreted as casual | weaknesses of visualization |
| exploration | searching for relationships with maps meeting certain conditions |
| modelling | 1) usually tests for spaatial dependence in the data or spatial assocition 2) asssesses against a random or control pattern 3) five spatial processes underlie modelling |
| spatial autocorrelation | dels with cocrrelation of the same variable at different spatial locations, Tobler's law, occurs when values at one location depend on values at nearby locations |
| Tobler's Law | everything is connected to everything else, but near things tend to be more connected than distant ones |
| what causes spatial autocorrelation | spatial interaction, mis-sized units of analysis that don't reflect the real world, diffusion of lifestyle, diseases, etc |
| autocorrelation tests | Global Moran's I Statics, global test, local tests |
| Global Moran's I Statistic | most common type of autocorrelation test |
| spatial autocorrelation implications | 1) forms basis of many geostatistical methods 2) can suggest new hypotheses 3) can render trasitional statictical tests invalid because it violates the independent observation assumption |
| interpolation | estimating attribute values at unsampled sites within the area covered by existing observations |
| to fit a plausible surface model to depict spatial variation | goal of interpolation |
| 1) assess point density against some random or control distribution 2) to assess weather points with like attributes are clustered together | goals for point patterns |
| will not control for age, major shortcoming | weakness of point patters |
| autocorrelated residuals | systemtic mis-measurement inthe dependent cariable, significant variables may be missing |
| social environment, physical environment, health care system | healath determinants include these three |
Combine with other sets
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