Chapter 6 Application
Here, we detail the methods used to apply the parcel-level synthetic population to a use-case example as well as a hypothetical health impact assessment.
6.1 Use-case: proximity to major roadway
We assign proximity to major roadway for each parcel as a proxy for air pollution using the following scripts:
[04] - [Distance-to-road] - CALCULATE.R
- Calculates shortest distance to major roadways.
[04b] - [Distance-to-road] - MERGE with synth pop.R
- Merges the distances for parcels with the synthetic population households in the respective parcels.
[05a] - [Distance-to-road] - Make calculated and misclassified datasets.R
- Randomize to make a ‘misclassified’ version of the parcel-level data
[05b] - [Distance-to-road] - Make combined dataset.R
- Combine calculated and ‘misclassified’ versions into one dataset
[05c] - [Distance-to-road] - Make combined plots and maps.R
- Creates plots and maps showing the results
[06a] - [Distance-to-road] - Checking for related variables.R
- Examines potential social determinants of health that may be associated with proximity to major roadway (as a proxy for air pollution exposure)
6.2 Hypothetical health impact assessment
To evaluate whether the use of a synthetic population produced with matched vs. random allocation leads to different conclusions about health impacts, we conducted a hypothetical health impact assessment.
Health impact assessments use exposure-response associations derived from the epidemiological literature. We constructed a conceptual model for a logit regression that can be applied for our example with both a main effect and a modifier variable (for example, income-level).
\[ \text{logit}(Y) = \beta_0 + \beta_M \cdot \text{modifier} + \beta_E \cdot \text{exposure} + \beta_I \cdot \text{modifier} \cdot \text{exposure} \]
We used this model to estimate: the change in cases among householders with the exposure and modifier, testing different exposure-modifier associations and model coefficients.
While this model is presented as a hypothetical, exposures might include:
- particulate matter
- heat index
- greenspace
Modifiers may include:
- median household income
- householder race and ethnicity
- householder tenure
- householder education status
The code used to conduct the hypothetical health impact assessment is provided here:
[HIA] - hypothetical health impact assessment.R