Modeling respiratory related mortality in California from air pollution and social deprivation data

In the application study of our submitted manuscript, we demonstrate our proposed methodology by modeling respiratory related deaths at the county and monthly level across California from 2015-2019. This data is downloaded from the California Department of Public Health's California Vital Data (Cal-ViDa) query tool. The model leverages spatial patterns in social deprivation index (SDI) from the Society of Actuaries (SoA) and air pollutant measurements from the US Environmental Protection Agency (EPA) to estimate the spatiotemporal dependence structure of the response. All of the data used for this application study is publicly available and thus will all be provided in this repository.  
, , # Modeling respiratory related mortality in California from air pollution and social deprivation data

Dataset DOI: [10.5061/dryad.j3tx95xtt](https://doi.org/10.5061/dryad.j3tx95xtt)

## Description of the data and file structure

This folder contains all the datasets and geographic files needed to run the analysis code in INLA-7.2-Final.Rmd. These datasets were downloaded from various publicly available sources. 

### Files and variables

* CA_census_pops1019.xlsx: census population data for counties of California for each year 2010-2019
* REGION: US census region code
* DIVISION: US census division code
* STATE: US census state code
* COUNTY: US census county code
* STNAME: state name (all California) 
* CTYNAME: county name (all Californian counties) 
* POPESTIMATE2010: census population estimate for given county in 2010
* POPESTIMATE201: census population estimate for given county in 2011
* POPESTIMATE2012: census population estimate for given county in 2012
* PO..., The mortality data is from Cal-ViDa which already de-identifies the data. Furthermore, small count cells are censored and must be imputed. The data is aggregated to the county level for the application study.