prev next front |1 |2 |3 |4 |5 |6 |7 |8 |9 |10 |11 |12 |13 |14 |15 |16 |17 |18 |19 |20 |21 |22 |23 |24 |25 |review
Calculation and visualization of morbidity and mortality rates for regions

This type of application is particularly well suited to GIS software since it requires that data from different sources be organized and integrated geographically. When developing rates, the case record often comes from a source such as a department of health services, vital statistics, county clinics, etc., while the denominator for the rates must come from census data or from a demographic data vendor. In this case, the case records must be aggregated to the regional level and then be appended to the regional attributes together with the population estimate for each region.
Age can be controlled for by creating separate attribute fields for population by age and for the numbers of cases by age.

Calculation of distance variables for statistical testing

In some situations, a GIS program can be useful as a data preparation tool prior to working with records in another environment. One example is when a distance variable must be calculated so that further analysis can be performed with a statistical analysis program.
For example, your hypothesis is that the closer an individual with TB resides to a clinic, the more likely they are to comply with the full course of TB treatment. In order to test this hypothesis, the distance that each individual resides from the nearest clinic must be calculated and appended to the record which also contains the treatment status. In order to accomplish this, the record must be geocoded and placed as a layer in a GIS program. Additionally, the locations of all clinics providing TB treatment must also be geocoded and placed into another layer. The GIS software can then be used to calculate the distance of each TB case to the nearest clinic and populate the appropriate field with that value. Once the distance has been appended, the table can then be loaded into a statistical analysis program to statistically test the association between the distance variable and the patient compliance.