February 29, 2020
We continued our discussion on health geography this week going over the major applications for GIS, spatial epidemiology, and exposure assessment.
Spatial epidemiology uses individual level data and small area counts to describe and understand spatial variation in disease risk to control health problems. However, spatial epidemiology relies on frequent and quality population data, and data on population movements and population counts on exposure to the disease variable because they must have well defined population groups, good survey data, allowance for heterogeneity of exposure, latency time, and population movement effects. As an example, Australia has a model called AIRA (accessibility/remoteness index of Australia) that is capable of calculating accessibility to any type of service from any populated place in Australia. Components of spatial epidemiology include disease mapping, cluster detection, spatial exposure assessment, and assessment of risk of disease.
Environmental hazards are present in the environment, and are far more simple of a process to measure because there is direct contract between the agent and target that produces ill affects.
Exposure assessment is the study of human contact with chemical, physical, biological, and social agents that arise in the environment, examining the dynamics of biological events and how they relate to human health outcomes. This can be assessed through direct methods like biomonitoring or self-reporting, but GIS is the indict method. It uses proximity, interpolation of estimated values (kriging is a good method to use here), land use regressional modelling, and satellite data as methods for exposure calculation. In general, there is no right way to calculate exposure but the finer the resolution and smaller the study area the more accurate the results will be, but a sensitivity analyses is always necessary when assigning concentration value estimates.
We also started Lab 3: Introduction to CrimeStat this week.