Associations between the Minority Health Social Vulnerability Index Scores, Rurality, and Histoplasmosis Incidence

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Overview

This repository houses code for analyses for a paper exploring associations between rurality, the Minority Health Social Vulnerability Index, and histoplasmosis incidence in eight states in the US.

All analyses were done in R 4.2.2, using renv for managing dependencies. The package dependencies are versioned in renv.lock, and after cloning this repository and installing renv can be set up by running the following code:

renv::activate() renv::restore()

Data

• All data are stored in the data/raw folder, but not included in this repository.
  • data/raw/NCHS Urban_Rural Codes.xlsx: from the NCHS urban-rural classification scheme for 2013 for the subset of states included in our dataset. Pulled from this dataset.
  • data/raw/mh_svi_20230329.csv: the Minority Health SVI measures as well as the component metrics that go into the each of the indices/themes, available at this link.
  • HistoSVI.xlsx: the histoplasmosis case counts by county and year. This only includes counties and years with any cases of histoplasmosis. This data was from an enhanced surveillance project (2011 - 2014), shared with CDC MDB by state partners, or from NNDSS (2020), available with permissions from each state partner.

Analyses

• The analyses are run using the scripts in the analysis folder in the following order:
  • 01getregional_mhsvi.R: pulls in raw data sources for the MH SVI and the NCHS urban-rural classification scheme to calculate regional specific, and rural classification specific SVIs based on code from (Sarah Rockhill)[https://github.com/s5rockhill/mh-svi].
  • 02cleanhisto_data.R: takes the regional and stratified svi's and joins them with county level histoplasmosis case count and population data across the six years included in the study (2011 - 2014, 2019, 2020). Population data were accessed from US census data using the tidycensus package.
  • 03runmodels.R: using the cleaned histo data, aggregates to the sum of population and histo cases across the six years. Runs a truncated poisson hurdle models on this aggregated cases counts using the R package glmmTMB, both for regional and a stratified analysis by rurality. Uses the R package DHARMa to run diagnostics on simulated model residuals.
  • 04makefigures.R: takes output from previous steps and create main and supplementary figures, as well as summary statistics for Table 1.

Outputs

• Outputs from the first two steps of the analysis are saved to the data folder, but are not included in this repository due to restrictions on sharing.
• The outputs from the other steps of the analyses are included in this repository in the output/ folder, except for the full hurdle model output (which includes the original data set).
• Figures are included in the figs/ folder.
• methodsresultssupp.qmd includes some results, methods, and supplementary text that is pulled in to the initial draft of the main manuscript (although wording may have been revised.)

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