findSVI

findSVI: an R package to calculate the Social Vulnerability Index at multiple geographical levels - Published in JOSS (2024)

https://github.com/heli-xu/findsvi

Science Score: 93.0%

This score indicates how likely this project is to be science-related based on various indicators:

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CITATION.cff file
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Found .zenodo.json file
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Found 4 DOI reference(s) in README and JOSS metadata
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Links to: joss.theoj.org
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JOSS paper metadata
Published in Journal of Open Source Software

Scientific Fields

Engineering Computer Science - 40% confidence

Last synced: 6 months ago · JSON representation

Repository

Calculate CDC/ATSDR Social Vulnerability Index

Basic Info

Host: GitHub
Owner: heli-xu
License: other
Language: R
Default Branch: main
Homepage: https://heli-xu.github.io/findSVI/
Size: 18.9 MB

Statistics

Stars: 14
Watchers: 3
Forks: 3
Open Issues: 1
Releases: 3

Created about 3 years ago · Last pushed 8 months ago

Metadata Files

Readme Changelog License

README.Rmd

---
output: github_document
---



```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# findSVI 



[![R-CMD-check](https://github.com/heli-xu/findSVI/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/heli-xu/findSVI/actions/workflows/R-CMD-check.yaml)

[![DOI](https://joss.theoj.org/papers/10.21105/joss.06525/status.svg)](https://doi.org/10.21105/joss.06525)



The goal of findSVI is to calculate regional CDC/ATSDR Social Vulnerability Index (SVI) (former site: www.atsdr.cdc.gov/placeandhealth/svi/index.html) at a geographic level of interest using US census data from American Community Survey.

## Overview

CDC/ATSDR releases SVI biannually at the counties/census tracts level for US or an individual state. findSVI aims to support more flexible and specific SVI analysis with additional options for years (2012-2022) and geographic levels (e.g., ZCTA/places, combining multiple states).

To find SVI for one or multiple year-state pair(s):

-   `find_svi()`: retrieves US census data (Census API key required) and calculates SVI based on CDC/ATSDR SVI documentation (www.atsdr.cdc.gov/placeandhealth/svi/data_documentation_download.html) for each year-state pair at the same geography level.

In most cases, `find_svi()` would be the easiest option. If you'd like to include simple feature geometry or have more customized requests for census data retrieval (e.g., different geography level for each year-state pair, multiple states for one year), you can process individual entry using the following:

-   `get_census_data()`: retrieves US census data (Census API key required);
-   `get_svi()`: calculates SVI from the census data supplied.

Essentially, `find_svi()` is a wrapper function for `get_census_data()` and `get_svi()` that also supports iteration over 1-year-and-1-state pairs at the same geography level.

## Installation

Install the findSVI package via CRAN:

```{r, eval=FALSE}
install.packages("findSVI")
```

Alternatively, you can install the development version of findSVI from GitHub with:

```{r, eval=FALSE}
# install.packages("devtools")
devtools::install_github("heli-xu/findSVI")
```

## Usage

**To find county-level SVI for New Jersey (NJ) for 2017, and for Pennsylvania (PA) for 2018:**

```{r find_svi, eval=FALSE, warning=FALSE}
library(findSVI)
library(dplyr)

summarise_results <- find_svi(
  year = c(2017, 2018),
  state = c("NJ", "PA"),
  geography = "county"
)
summarise_results %>% 
  group_by(year, state) %>% 
  slice_head(n = 5)
```

```{r summarise_results, echo=FALSE, warning=FALSE, message=FALSE}
library(findSVI)
library(dplyr)

load(system.file("extdata", "summarise_results.rda", package = "findSVI"))
summarise_results %>% 
  group_by(year, state) %>% 
  slice_head(n = 5)
```

(First 5 rows of results for 2017-NJ and 2018-PA are shown. 'RPL_themes\` indicates overall SVI, and 'RPL_theme1' to 'RPL_theme4' indicate theme-specific SVIs.)

**To retrieve county-level census data *and then* get SVI for PA for 2020:**

```{r get_census_data, eval=FALSE}
data <- get_census_data(2020, "county", "PA")
data[1:10, 1:10]
```

```{r censusdata, echo=FALSE}
load(system.file("testdata","pa_cty_raw2020.rda",package = "findSVI"))
pa_cty_raw2020[1:10, 1:10]
```

(First 10 rows and columns are shown, with the rest of columns being other census variables for SVI calculation.)

```{r get_svi, eval = FALSE}
result <- get_svi(2020, data)
glimpse(result)
```

```{r svi, echo=FALSE}
load(system.file("testdata", "pa_cty_result2020.rda", package = "findSVI"))
glimpse(pa_cty_result2020)
```

**To find SVI for custom geographic boundaries:**

```{r, eval=FALSE}
cz_svi <- find_svi_x(
  year = 2020,
  geography = "county",
  xwalk = cty_cz_2020_xwalk #county-commuting zone crosswalk
)
```

...where `xwalk` is supplied by users to define the relationship between a Census geography ('GEOID') and the custom geographic level ('GEOID2'). The Census geography should be fully nested in the custom geographic level of interest. As an example, first 10 rows of the county-commuting zone crosswalk are shown below:

```{r}
cty_cz_2020_xwalk %>% head(10)
```

With the crosswalk, county-level census data are aggregated to the commuting zone-level, and SVI is calculated for each commuting zone. Below shows the overall and theme-specific SVI of the first 10 rows, with GEOIDs representing the commuting zone IDs.

```{r, eval=FALSE}
cz_svi %>% 
  select(GEOID, contains("RPL")) %>%
  head(10)
```

```{r, echo=FALSE}
load(system.file("extdata","cz_svi2020.rda",package = "findSVI"))
cz_svi2020
```

Owner

Login: heli-xu
Kind: user

Repositories: 3
Profile: https://github.com/heli-xu

JOSS Publication

findSVI: an R package to calculate the Social Vulnerability Index at multiple geographical levels

Published

July 05, 2024

DOI

10.21105/joss.06525

Volume 9, Issue 99, Page 6525

Authors

Heli Xu

Urban Health Collaborative, Drexel Dornsife School of Public Health, Philadelphia, PA, United States of America

Ran Li

Urban Health Collaborative, Drexel Dornsife School of Public Health, Philadelphia, PA, United States of America

Usama Bilal

Urban Health Collaborative, Drexel Dornsife School of Public Health, Philadelphia, PA, United States of America, Department of Epidemiology and Biostatistics, Drexel Dornsife School of Public Health, Philadelphia, PA, United States of America

Editor

Øystein Sørensen

GitHub Events

Total

Create event: 1
Commit comment event: 1
Release event: 1
Issues event: 15
Watch event: 11
Issue comment event: 8
Push event: 35
Pull request event: 1

Last Year

Create event: 1
Commit comment event: 1
Release event: 1
Issues event: 15
Watch event: 11
Issue comment event: 8
Push event: 35
Pull request event: 1

Committers

Last synced: 7 months ago

All Time

Total Commits: 225
Total Committers: 1
Avg Commits per committer: 225.0
Development Distribution Score (DDS): 0.0

Past Year

Commits: 38
Committers: 1
Avg Commits per committer: 38.0
Development Distribution Score (DDS): 0.0

Top Committers

Name	Email	Commits
Heli Xu	x**1@g**m	225

Issues and Pull Requests

Last synced: 6 months ago

All Time

Total issues: 27
Total pull requests: 6
Average time to close issues: 2 months
Average time to close pull requests: 3 days
Total issue authors: 8
Total pull request authors: 4
Average comments per issue: 2.81
Average comments per pull request: 0.83
Merged pull requests: 3
Bot issues: 0
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Past Year

Issues: 8
Pull requests: 2
Average time to close issues: 16 days
Average time to close pull requests: 7 days
Issue authors: 5
Pull request authors: 1
Average comments per issue: 0.88
Average comments per pull request: 1.0
Merged pull requests: 0
Bot issues: 0
Bot pull requests: 0

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ran-codes (9)
heli-xu (8)
usamabilal (4)
osorensen (2)
epiben (1)
brendensm (1)
rsbivand (1)
hschoi11 (1)
sabohashem (1)

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ran-codes (2)
eltociear (2)
nightwatch-analytics (2)
heli-xu (2)

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Total packages: 1
Total downloads:
- cran 234 last-month

Total dependent packages: 0
Total dependent repositories: 0
Total versions: 2
Total maintainers: 1

cran.r-project.org: findSVI

Calculate Social Vulnerability Index for Communities

Homepage: https://github.com/heli-xu/findSVI
Documentation: http://cran.r-project.org/web/packages/findSVI/findSVI.pdf
License: MIT + file LICENSE
Latest release: 0.2.0
published about 1 year ago

Versions: 2
Dependent Packages: 0
Dependent Repositories: 0
Downloads: 234 Last month

Rankings

Forks count: 21.5%

Dependent packages count: 28.4%

Stargazers count: 31.3%

Dependent repos count: 37.0%

Average: 41.2%

Downloads: 87.9%

Maintainers (1)

xuheli91@gmail.com

Last synced: 6 months ago

Dependencies

.github/workflows/R-CMD-check.yaml actions

actions/checkout v3 composite
r-lib/actions/check-r-package v2 composite
r-lib/actions/setup-pandoc v2 composite
r-lib/actions/setup-r v2 composite
r-lib/actions/setup-r-dependencies v2 composite

.github/workflows/pkgdown.yaml actions

JamesIves/github-pages-deploy-action v4.4.1 composite
actions/checkout v3 composite
r-lib/actions/setup-pandoc v2 composite
r-lib/actions/setup-r v2 composite
r-lib/actions/setup-r-dependencies v2 composite

DESCRIPTION cran

R >= 2.10 depends
cli * imports
dplyr * imports
magrittr * imports
purrr * imports
rlang * imports
stringr * imports
tidycensus * imports
tidyr * imports
tidyselect * imports
utils * imports
ggplot2 * suggests
glue * suggests
htmltools * suggests
knitr * suggests
leaflet * suggests
reactable * suggests
rmarkdown * suggests
sf * suggests
testthat >= 3.0.0 suggests
tmap * suggests

findSVI

Science Score: 93.0%

Scientific Fields

Repository

Basic Info

Statistics

Metadata Files

README.Rmd

Owner

JOSS Publication

findSVI: an R package to calculate the Social Vulnerability Index at multiple geographical levels

Authors

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