inst/extdata/README.md

In multigroup.vaccine: Analyze Outbreak Models of Multi-Group Populations with Vaccination

Example Census Data

This directory contains example U.S. Census Bureau population estimate data files and city-specific American Community Survey (ACS) data included with the package.

County-Level Census Data

• cc-est2024-syasex-49.csv - Utah (FIPS code 49) county-level population estimates by single-year age and sex, 2020-2024

City-Level ACS Data

• hildale_ut_2023.csv - Hildale city, Utah population by age from ACS 5-Year Estimates (2019-2023)
• hildale_ut_2023_metadata.csv - Metadata for Hildale ACS data (variable descriptions)
• colorado_city_az_2023.csv - Colorado City town, Arizona population by age from ACS 5-Year Estimates (2019-2023)
• colorado_city_az_2023_metadata.csv - Metadata for Colorado City ACS data (variable descriptions)
• centennial_park_az_2023.csv - Centennial Park, AZ population by age from ACS 5-Year Estimates (2019-2023)

Source

County-Level Data

Data downloaded from the U.S. Census Bureau Population Estimates Program: https://www2.census.gov/programs-surveys/popest/datasets/2020-2024/counties/asrh/

City-Level Data

Data downloaded from the U.S. Census Bureau American Community Survey (ACS) 5-Year Estimates via data.census.gov: - Hildale, UT: Table S0101 (Age and Sex), 2019-2023 ACS 5-Year Estimates - Colorado City, AZ: Table S0101 (Age and Sex), 2019-2023 ACS 5-Year Estimates - Centennial Park, AZ: Table S0101 (Age and Sex), 2019-2023 ACS 5-Year Estimates

Usage

County-Level Census Data

Access county data in your code using:

library(multigroup.vaccine)

# Get the path to the example data file
utah_csv <- getCensusDataPath()

# Use it with getCensusData
slc_data <- getCensusData(
  state_fips = "49",
  county_name = "Salt Lake County",
  year = 2024,
  csv_path = getCensusDataPath()
)

City-Level ACS Data

Access city data using:

library(multigroup.vaccine)

# Load Hildale data with default 5-year age groups
hildale_data <- getCityData(
  city_name = "Hildale city, Utah",
  csv_path = system.file("extdata", "hildale_ut_2023.csv", 
                         package = "multigroup.vaccine")
)

# Load Colorado City data
colorado_city_data <- getCityData(
  city_name = "Colorado City town, Arizona",
  csv_path = system.file("extdata", "colorado_city_az_2023.csv",
                         package = "multigroup.vaccine")
)

# Load with custom age groups
hildale_custom <- getCityData(
  city_name = "Hildale city, Utah",
  csv_path = system.file("extdata", "hildale_ut_2023.csv",
                         package = "multigroup.vaccine"),
  age_groups = c(0, 5, 18, 65)
)

Purpose

This file is included to: 1. Enable package examples to run without internet access 2. Support R CMD check and pkgdown building processes 3. Allow offline testing and development 4. Provide a working example for users

Data Format

The CSV file contains the following columns: - SUMLEV - Summary level (50 = county) - STATE - State FIPS code - COUNTY - County FIPS code - STNAME - State name - CTYNAME - County name - YEAR - Estimate year code (1 = April 1, 2020 base; 2 = 2020; 3 = 2021; etc.) - AGE - Single year of age (0-85+) - TOT_POP - Total population - TOT_MALE - Male population - TOT_FEMALE - Female population

Updating

To update this file with newer data:

# Download the latest file
url <- "https://www2.census.gov/programs-surveys/popest/datasets/2020-2024/counties/asrh/cc-est2024-syasex-49.csv"
download.file(url, "inst/extdata/cc-est2024-syasex-49.csv")

Then rebuild the package documentation with devtools::document().

multigroup.vaccine documentation built on Sept. 19, 2026, 1:06 a.m.