In ercbk/indianacovid19data: indianacovid19data: COVID-19 data for Indiana
knitr::opts_chunk$set(echo = FALSE,
warning = FALSE,
message = FALSE,
out.width = "100%",
collapse = TRUE,
comment = "#>"
)
library(indianacovid19data)
library(dplyr)
library(purrr)
library(gt)
library(gtsummary)
Historical Weekly COVID-19 Cases by Age for Indiana
Description
Processed data for Demographics heatmaps that shows a breakdown of weekly COVID-19 cases by age group.
Reference Entry
Script
Processing: process-demog-data.R
Raw Sources
Indiana Data Hub: COVID-19 CASE DEMOGRAPHICS
tidycensus R package: website, 2018 age populations for Indiana
Notes
Other variables:
- end_date: Ordered factor; date of the last day of the weekly interval
- daily_cases: Cases for the end_date; vestigial column that was used to calculate weekly_cases
- pop: 2018 age populations for Indiana that's used to calculate prop_cases
\
ach_var_defs <- c("Age group",
"",
"",
"",
"",
"",
"",
"",
"",
"Weekly count of COVID-19 confirmed cases by age group",
"Number of cases scaled to per 1000 residents per age group")
# table width responsive to length of var_defs text, so may not appear full.width
# use show_header_names to get col names being used by tbl_summary
tbl_summary(age_cases_heat,
missing = "ifany",
missing_text = "Missing",
include = c(age_grp, weekly_cases, prop_cases)) %>%
modify_header(update = list(
label ~ 'Variable')) %>%
modify_table_body(dplyr::mutate, defs = ach_var_defs) %>%
modify_header(defs = "Definition") %>%
# show_header_names()
as_gt() %>%
tab_options(table.align = "left") %>%
cols_align("left", vars(stat_0, defs)) %>%
as_raw_html()
\
\
\
Historical Weekly COVID-19 Deaths by Age Group for Indiana
Description
Processed data for Demographics line charts that shows counts and trends of weekly COVID-19 deaths by age group.
Reference Entry
Script
Processing: process-demog-data.R
Raw Sources
Indiana Data Hub: COVID-19 CASE DEMOGRAPHICS
Notes
Other variables:
- date_text: date label for the chart
- tooltip: pop-up text for points in chart with death counts and date
\
adl_var_defs <- c("Date of the last day of the weekly interval",
"Age group",
"",
"",
"",
"",
"",
"",
"",
"",
"Weekly count of COVID-19 confirmed deaths by age group")
# table width responsive to length of var_defs text, so may not appear full.width
# use show_header_names to get col names being used by tbl_summary
tbl_summary(age_death_line,
missing = "ifany",
missing_text = "Missing",
include = c(end_date, agegrp, weekly_total)) %>%
modify_header(update = list(
label ~ 'Variable')) %>%
modify_table_body(dplyr::mutate, defs = adl_var_defs) %>%
modify_header(defs = "Definition") %>%
# show_header_names()
as_gt() %>%
tab_options(table.align = "left") %>%
cols_align("left", vars(stat_0, defs)) %>%
as_raw_html()
\
\
\
Historical Daily COVID-19 Hospital Admissions by Age Group for Indiana
Description
Raw data for the Hospitals line charts that shows daily COVID-19 hospital admissions by age group and gender.
Reference Entry
Script
Collection: scrape-regenstrief-tableau.R
Raw Sources
Regenstrief Institute: dashboard
Notes
This dataset is incomplete with random gaps between days.
\
ahl_var_defs <- c("Date (Daily)",
"Age group",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"Daily COVID-19 male hospital admissions by age group",
"Daily COVID-19 female hospital admissions by age group",
"Daily COVID-19 total hospital admissions by age group")
# table width responsive to length of var_defs text, so may not appear full.width
# use show_header_names to get col names being used by tbl_summary
tbl_summary(age_hosp_line,
missing = "ifany",
missing_text = "Missing",
include = everything()) %>%
modify_header(update = list(
label ~ 'Variable')) %>%
modify_table_body(dplyr::mutate, defs = ahl_var_defs) %>%
modify_header(defs = "Definition") %>%
# show_header_names()
as_gt() %>%
tab_options(table.align = "left") %>%
cols_align("left", vars(stat_0, defs)) %>%
as_raw_html()
\
\
\
Historical Daily ICU Beds and Ventilators for Indiana
Description
Raw data for the Static Charts Hospitalizations, ICU Beds and Ventilator Availability that shows resource counts of ICU beds and ventilators.
Reference Entry
Script
Collection: build-datasets.R
Raw Sources
Indiana Data Hub: COVID-19 BEDS AND VENTS
Notes
The source publishs daily excel spreadsheets with total resource counts, and these spreadsheets are collected and joined daily to produce a dataset with historical values.
\
bvc_var_defs <- c("Date (Daily)",
"Total ICU beds",
"Total ICU beds occupied with COVID-19 patients",
"Total ICU beds occupied with non-COVID-19 patients",
"Total available ICU beds",
"Total ventilators",
"Total ventilators being used by COVID-19 patients",
"Total ventilators being used by non-COVID-19 patients",
"Total available ventilators")
# table width responsive to length of var_defs text, so may not appear full.width
# use show_header_names to get col names being used by tbl_summary
tbl_summary(beds_vents_complete,
missing = "ifany",
missing_text = "Missing",
include = everything()) %>%
modify_header(update = list(
label ~ 'Variable')) %>%
modify_table_body(dplyr::mutate, defs = bvc_var_defs) %>%
modify_header(defs = "Definition") %>%
# show_header_names()
as_gt() %>%
tab_options(table.align = "left") %>%
cols_align("left", vars(stat_0, defs)) %>%
cols_width(vars(stat_0) ~ "150px") %>%
as_raw_html()
\
\
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Historical Google Maps Mobility Indices for Indiana
Description
Processed data for the Google Maps Mobility Indices line chart that shows percent differences from a mobility baseline that was calculated during the 5-week period Jan 3 – Feb 6, 2020. These percent changes show how lengths-of-stay at different locations have changed from pre-pandemic conditions.
Reference Entry
Script
Miscellaneous: goog-mob-line.R
Raw Sources
Google Mobility Reports: website
Notes
\
goog_var_defs <- c("Date (Daily)",
"Length-of-stay (mobility) measurements are calculated for these location categories",
"",
"",
"",
"Percent difference from the mobility baseline for each category",
"TRUE/FALSE binary for whether the date is on a weekend or not")
# table width responsive to length of var_defs text, so may not appear full.width
# use show_header_names to get col names being used by tbl_summary
tbl_summary(goog_mob_ind,
missing = "ifany",
missing_text = "Missing",
include = everything()) %>%
modify_header(update = list(
label ~ 'Variable')) %>%
modify_table_body(dplyr::mutate, defs = goog_var_defs) %>%
modify_header(defs = "Definition") %>%
# show_header_names()
as_gt() %>%
tab_options(table.align = "left") %>%
cols_align("left", vars(stat_0, defs)) %>%
cols_width(vars(stat_0) ~ px(150)) %>%
as_raw_html()
\
\
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Historical State Hospital Staff Shortages, Hospital Mortality Rate, Hospital Admissions and Ages Skewness of Admissions for Indiana
Description
Processed data for Hospitals line charts that shows state hospital staff shortages, hospital mortality rate, hospital admissions, and age skewness of hospital admissions towards older patients.
Reference Entry
Script
Process: process-hospitals-data.R
Raw Sources
Regenstrief Institute: dashboard
Department of Health and Human Services: COVID-19 Reported Patient Impact and Hospital Capacity by State Timeseries
Department of Health and Human Services: COVID-19 Reported Patient Impact and Hospital Capacity by Facility
Notes
Other variables:
- date: Ordered factor, Month Day format
\
msas_var_defs <- c("Percent of reporting hospitals that have reported staffing shortages for that day. That percentage is averaged over a rolling, seven day window",
"Ratio of deaths of hospitalized COVID-19 patients and unique COVID-19 hospital admissions. Each rate is calculated over a rolling, 14-day window",
"Daily total of unique individuals that have tested positive for COVID-19 and been admitted to a hospital on the that day. Those daily counts are averaged over a rolling, seven day window",
"Measurement of the age makeup of the COVID-19 hospital admissions data. It's calculated over a rolling, 14 day window")
# table width responsive to length of var_defs text, so may not appear full.width
# use show_header_names to get col names being used by tbl_summary
tbl_summary(hosp_msas_line,
missing = "ifany",
missing_text = "Missing",
include = -date) %>%
modify_header(update = list(
label ~ 'Variable')) %>%
modify_table_body(dplyr::mutate, defs = msas_var_defs) %>%
modify_header(defs = "Definition") %>%
# show_header_names()
as_gt() %>%
tab_options(table.align = "left") %>%
cols_align("left", vars(stat_0, defs)) %>%
cols_width(vars(stat_0) ~ px(150)) %>%
as_raw_html()
\
\
\
Local Hospital Capacity for Indiana
Description
Processed data for the Hospitals Local Hospital Capacity table that shows capacity measures and counts of COVID-19 patients for hospitals at the local level.
Reference Entry
Script
Process: process-hospitals-data.R
Raw Sources
Department of Health and Human Services: COVID-19 Reported Patient Impact and Hospital Capacity by State Timeseries
Notes
Other variables:
- hospital_name: char, Name of hospital
- address: char, Street address of hospital
- city_zip: char, City and zip code
- county_name: char, Name of county
- avgCovIcuTenKList: nested list, end_date and average daily number of ICU beds being used by confirmed and suspected COVID-19 patients over the weekly interval
- avgCovHospTenKList: nested list, end_date and average daily number of hospital beds being used by confirmed and suspected COVID-19 patients over the weekly interval
- avgTotImpBedsList: end_date and avgTotImpBeds, the average daily number of staffed total beds available over the weekly interval
\
num_end_dates <- hosp_react_tab %>%
distinct(end_date) %>%
summarize(num_dates = n()) %>%
pull(num_dates)
hrt_var_defs <- purrr::reduce(list(
"Last day the data was updated for a particular hospital",
rep("", num_end_dates),
"Proportion of the seven-day average of occupied ICU beds to the seven-day average of available ICU beds.",
"",
"Proportion of the seven-day average of occupied hospital beds to the seven-day average of available hospital beds.",
""
), append)
# table width responsive to length of var_defs text, so may not appear full.width
# use show_header_names to get col names being used by tbl_summary
tbl_summary(hosp_react_tab,
missing = "ifany",
missing_text = "Missing",
include = c(end_date, sev_day_icu_perc_occup, sev_day_hosp_perc_occup)) %>%
modify_header(update = list(
label ~ 'Variable')) %>%
modify_table_body(dplyr::mutate, defs = hrt_var_defs) %>%
modify_header(defs = "Definition") %>%
# show_header_names()
as_gt() %>%
tab_options(table.align = "left") %>%
cols_align("left", vars(stat_0, defs)) %>%
cols_width(vars(stat_0) ~ px(150)) %>%
as_raw_html()
\
\
\
Historical Daily Tests, Cases and Deaths by Age for Indiana
Description
Raw data for Demographics line charts that shows daily case and death counts by age group.
Reference Entry
Script
Collection: build-datasets.R
Raw Sources
Indiana Data Hub: COVID-19 CASE DEMOGRAPHICS
Notes
The source publishs daily excel spreadsheets with total resource counts, and these spreadsheets are collected and joined daily to produce a dataset with historical values.
Other variables:
- date: date, yyyy-mm-dd format
\
iac_var_defs <- c("Date (Daily)",
"Age Group",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"",
"Number of cases by age group",
"Number of deaths by age group",
"Number of tests by age group",
"Percent of daily cases",
"Percent of daily deaths",
"Percent of daily tests")
# table width responsive to length of var_defs text, so may not appear full.width
# use show_header_names to get col names being used by tbl_summary
tbl_summary(ind_age_complete,
missing = "ifany",
missing_text = "Missing",
include = everything()) %>%
modify_header(update = list(
label ~ 'Variable')) %>%
modify_table_body(dplyr::mutate, defs = iac_var_defs) %>%
modify_header(defs = "Definition") %>%
# show_header_names()
as_gt() %>%
tab_options(table.align = "left") %>%
cols_align("left", vars(stat_0, defs)) %>%
cols_width(vars(stat_0) ~ px(190)) %>%
as_raw_html()
\
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Historical Daily Cases and Deaths by Race for Indiana
Description
Raw data that shows daily case and death counts by race.
Reference Entry
Script
Collection: build-datasets.R
Raw Sources
The Covid Tracking Project: The COVID Racial Data Tracker
Notes
The source publishs data every 3 or 4 days.
\
# table width responsive to length of var_defs text, so may not appear full.width
# use show_header_names to get col names being used by tbl_summary
tbl_summary(ind_race_complete,
missing = "ifany",
missing_text = "Missing",
include = c(date, everything())) %>%
modify_header(update = list(
label ~ 'Variable')) %>%
as_gt() %>%
tab_options(table.align = "left") %>%
cols_align("left", vars(stat_0)) %>%
as_raw_html()
\
\
\
Historical Weekly Median Age of Cases, Weekly Tests and Deaths for Indiana
Description
Processed data for the Demographics bubble chart that shows the number of tests, number of deaths, and median age of the cases per week.
Reference Entry
Script
Processing: process-demog-data.R
Raw Sources
Indiana Data Hub: COVID-19 CASE DATA
Notes
Other variables:
- end_date: ordered factor, Month Day format; end date of weekly interval
\
mab_var_defs <- c("Median age of cases for that week",
"Number of tests for that week",
"Number of deaths for that week")
# table width responsive to length of var_defs text, so may not appear full.width
# use show_header_names to get col names being used by tbl_summary
tbl_summary(median_age_bubble,
missing = "ifany",
missing_text = "Missing",
include = -end_date) %>%
modify_header(update = list(
label ~ 'Variable')) %>%
modify_table_body(dplyr::mutate, defs = mab_var_defs) %>%
modify_header(defs = "Definition") %>%
# show_header_names()
as_gt() %>%
tab_options(table.align = "left") %>%
cols_align("left", vars(stat_0, defs)) %>%
cols_width(vars(stat_0) ~ px(200)) %>%
as_raw_html()
\
\
\
Historical Daily Hospital Admissions and Deaths for Indiana
Description
Raw data for the Hospitals line charts that shows daily COVID-19 hospital admissions, hospital deaths, and hospital death rate.
Reference Entry
Script
Collection: scrape-regenstrief-tableau.R
Raw Sources
Regenstrief Institute: dashboard
Notes
This dataset is incomplete with random gaps between days.
\
mhl_var_defs <- c("Date (Daily)",
"Number of individuals hospitalized for COVID-19 who died while in the hospital",
"Number of unique individuals who have been hospitalized and tested positive for COVID-19",
"Percent of individuals hospitalized for COVID-19 who died while in the hospital")
# table width responsive to length of var_defs text, so may not appear full.width
# use show_header_names to get col names being used by tbl_summary
tbl_summary(mort_hosp_line,
missing = "ifany",
missing_text = "Missing",
include = everything()) %>%
modify_header(update = list(
label ~ 'Variable')) %>%
modify_table_body(dplyr::mutate, defs = mhl_var_defs) %>%
modify_header(defs = "Definition") %>%
# show_header_names()
as_gt() %>%
tab_options(table.align = "left") %>%
cols_align("left", vars(stat_0, defs)) %>%
cols_width(vars(stat_0) ~ "180px") %>%
as_raw_html()
\
\
\
Historical Weekly Positivity Rates and Daily Cases per 100,000 Indiana Residents
Description
Processed data for the Indiana COVIDcast Dashboard that shows weekly positivity rate and daily cases per 100,000 residents per metropolitan statistical area.
Reference Entry
Scripts
Processing: process-hist-regional-dat.R
Raw Sources
covidcast R package: website
Michigan Disease Surveillance System: website
Wisconsin Department of Health Services: website
Illinois Department of Public Health: website
Indiana Data Hub: website
Notes
The missing values for pos_rate are partly because this dataset has a row for every day and the positivity rate is calculated every week. The other missing values are for Cincinnati, Louisville, and Evansville. At the time this dashboard was created, those states with counties included in those areas didn't publicly release the necessary data to calcuate their positivity rates.
Other variables:
- geo_value: FIPS codes for msa
- start_date: Start date of the weekly interval for pos_rate
- data_date: Date when data was last updated
\
msa_hist_var_defs <- purrr::reduce(list("date for daily cases_100k",
"Metropolitan Statistical Area",
rep("", 15),
"Daily cases per 100,000 residents per MSA",
"Weekly positivity rate per MSA",
""), append)
# table width responsive to length of var_defs text, so may not appear full.width
# use show_header_names to get col names being used by tbl_summary
tbl_summary(msa_cases100_posrate_historic,
missing = "ifany",
missing_text = "Missing",
include = c(date, msa, cases_100k, pos_rate)) %>%
modify_header(update = list(
label ~ 'Variable')) %>%
modify_table_body(dplyr::mutate, defs = msa_hist_var_defs) %>%
modify_header(defs = "Definition") %>%
# show_header_names()
as_gt() %>%
tab_options(table.align = "left") %>%
cols_align("left", vars(stat_0, defs)) %>%
as_raw_html()
\
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Historical Daily Values of Delphi Research Groups Combined Indicator for Indiana
Description
Processed data for the Indiana COVIDcast Dashboard that shows historic daily values of Delphi Research Group's Combined Indicator for each methropolitan statistical area.
Reference Entry
Scripts
Processing: process-dashboard-data.R
Raw Sources
covidcast R package: website
Notes
\
dcl_var_defs <- purrr::reduce(list("Date (Daily)",
"Metropolitan Statistical Area",
rep("", 15),
"Delphi Research Group's “Combined” indicator"), append)
# table width responsive to length of var_defs text, so may not appear full.width
# use show_header_names to get col names being used by tbl_summary
tbl_summary(dash_ci_line,
missing = "ifany",
missing_text = "Missing",
include = c(time_value, name, value)) %>%
modify_header(update = list(label ~ 'Variable')) %>%
modify_table_body(dplyr::mutate, defs = dcl_var_defs) %>%
modify_header(defs = "Definition") %>%
# show_header_names()
as_gt() %>%
tab_options(table.align = "left") %>%
cols_align("left", vars(stat_0, defs)) %>%
as_raw_html()
\
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Historical Weekly COVID-19 Statistics and Counts for Illinois Counties
Description
Raw data for the Indiana COVIDcast Dashboard that shows various weekly COVID-19 county statistics for Illinois
Reference Entry
Scripts
Collection: build-regional-dat.R
Raw Sources
Illinois Department of Public Health: website
Notes
These data are published in weekly intervals into a HTML table then scraped and collected.
There are other missing data not shown in the table below. Illinois DPH changes/improves the format of their webpage from time to time, and I haven't been changing my scraping code to match in a timely manner. They do have a data portal which has cases, tests, and deaths for each county, but not a historical dataset with exact fields as below. Here are weekly ranges that are missing:
2021-7-18 to 2021-7-24
2021-7-25 to 2021-7-31
2021-9-12 to 2021-9-18
2021-9-5 to 2021-9-11
2021-9-26 to 2021-10-9
2021-10-10 to 2021-10-16
Other variables:
- week: int; week of the year
- County: char; Illinois county name
- New Cases per 100,000: string; format: "\<int> cases" or "\<int> per 100k" or "\<int> per 100kwarning"
- Test Positivity %: string; format: "\<float>%\r\n New Tests: \<int>"
- (%) CLI ED Visits, Adults: string; format: "\<int>%"
- ICU (%) Available: string; format: "\<float>%"
\
ill_var_defs <- c("First day of the weekly interval",
"Last day of the weekly interval",
"Number of COVID-19 deaths per week per county",
"")
# table width responsive to length of var_defs text, so may not appear full.width
# use show_header_names to get col names being used by tbl_summary
tbl_summary(illinois_tests_complete,
missing = "ifany",
missing_text = "Missing",
include = c(start_date, end_date, `Number of Deaths`)) %>%
modify_header(update = list(label ~ 'Variable')) %>%
modify_table_body(dplyr::mutate, defs = ill_var_defs) %>%
modify_header(defs = "Definition") %>%
# show_header_names()
as_gt() %>%
tab_options(table.align = "left") %>%
cols_align("left", vars(stat_0, defs)) %>%
as_raw_html()
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Historical Daily COVID-19 Test Results for Indiana Counties
Description
Raw data for the Indiana COVIDcast Dashboard that shows daily COVID-19 county test results for Indiana
Reference Entry
Scripts
Collection: build-regional-dat.R
Raw Sources
Indiana Data Hub: COVID-19 COUNTY-WIDE TEST, CASE, AND DEATH TRENDS
Notes
Other variables:
- county: County name
\
ind_var_defs <- c("Date (Daily)",
"Number of COVID-19 cases per day per county",
"Number of COVID-19 tests per day per county")
# table width responsive to length of var_defs text, so may not appear full.width
# use show_header_names to get col names being used by tbl_summary
tbl_summary(ind_tests_complete,
missing = "ifany",
missing_text = "Missing",
include = c(date, positives, num_tests)) %>%
modify_header(update = list(label ~ 'Variable')) %>%
modify_table_body(dplyr::mutate, defs = ind_var_defs) %>%
modify_header(defs = "Definition") %>%
# show_header_names()
as_gt() %>%
tab_options(table.align = "left") %>%
cols_align("left", vars(stat_0, defs)) %>%
as_raw_html()
\
\
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Historical Daily COVID-19 Test Results for Michigan Counties
Description
Raw data for the Indiana COVIDcast Dashboard that shows daily COVID-19 county test results for Michigan
Reference Entry
Scripts
Collection: build-regional-dat.R
Raw Sources
Michigan Department of Health and Human Services: COVID-19 Tests by County
Notes
Other variables:
- county: County name
\
mich_var_defs <- c("Date (Daily)",
"Number of COVID-19 positive tests per day per county",
"Number of COVID-19 negative tests per day per county",
"Total number of COVID-19 tests per day per county")
# table width responsive to length of var_defs text, so may not appear full.width
# use show_header_names to get col names being used by tbl_summary
tbl_summary(mich_tests_complete,
missing = "ifany",
missing_text = "Missing",
include = c(date, positive, negative, total)) %>%
modify_header(update = list(label ~ 'Variable')) %>%
modify_table_body(dplyr::mutate, defs = mich_var_defs) %>%
modify_header(defs = "Definition") %>%
# show_header_names()
as_gt() %>%
tab_options(table.align = "left") %>%
cols_align("left", vars(stat_0, defs)) %>%
as_raw_html()
\
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OpenTable Year-Over-Year Seated Diners for Regional States
Description
Processed data for the OpenTable Year-Over-Year Seated Diners line charts that shows reservation data from a sample of restaurants across Indiana and other regional states. Each data point is the median daily percent difference in seated diners from 2019 to either 2020 or 2021 depending on the date.
Reference Entry
Script
Miscellaneous: opentab-rest-line.R
Raw Sources
OpenTable: State of the Industry
Notes
\
ot_var_defs <- c("Date (Daily)",
"State",
"",
"",
"",
"",
"",
"",
"Median daily percent difference in seated diners for each state",
"TRUE/FALSE binary for whether the date is on a weekend or not")
# table width responsive to length of var_defs text, so may not appear full.width
# use show_header_names to get col names being used by tbl_summary
tbl_summary(open_tab_reg,
missing = "ifany",
missing_text = "Missing",
include = c(date, everything())) %>%
modify_header(update = list(
label ~ 'Variable')) %>%
modify_table_body(dplyr::mutate, defs = ot_var_defs) %>%
modify_header(defs = "Definition") %>%
# show_header_names()
as_gt() %>%
tab_options(table.align = "left") %>%
cols_align("left", vars(stat_0, defs)) %>%
cols_width(vars(stat_0) ~ px(150)) %>%
as_raw_html()
\
\
\
Historical Daily COVID-19 Test Results for Wisconsin Counties
Description
Raw data for the Indiana COVIDcast Dashboard that shows daily COVID-19 county test results for Wisconsin
Reference Entry
Scripts
Collection: build-regional-dat.R
Raw Sources
Wisconsin Department of Health Services: COVID-19 Historical Data by County
Notes
Other variables:
- county: County name
\
wisc_var_defs <- c("Date (Daily)",
"Number of COVID-19 positive tests per day per county",
"Number of COVID-19 negative tests per day per county",
"")
# table width responsive to length of var_defs text, so may not appear full.width
# use show_header_names to get col names being used by tbl_summary
tbl_summary(wisc_tests_complete,
missing = "ifany",
missing_text = "Missing",
include = c(date, positive, negative)) %>%
modify_header(update = list(label ~ 'Variable')) %>%
modify_table_body(dplyr::mutate, defs = wisc_var_defs) %>%
modify_header(defs = "Definition") %>%
# show_header_names()
as_gt() %>%
tab_options(table.align = "left") %>%
cols_align("left", vars(stat_0, defs)) %>%
as_raw_html()
\
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ercbk/indianacovid19data documentation built on Dec. 20, 2021, 5:27 a.m.
R Package Documentation
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
knitr::opts_chunk$set(echo = FALSE, warning = FALSE, message = FALSE, out.width = "100%", collapse = TRUE, comment = "#>" ) library(indianacovid19data) library(dplyr) library(purrr) library(gt) library(gtsummary)
Historical Weekly COVID-19 Cases by Age for Indiana
Description
Processed data for Demographics heatmaps that shows a breakdown of weekly COVID-19 cases by age group.
Reference Entry
Script
Processing: process-demog-data.R
Raw Sources
Indiana Data Hub: COVID-19 CASE DEMOGRAPHICS
tidycensus R package: website, 2018 age populations for Indiana
Notes
Other variables:
- end_date: Ordered factor; date of the last day of the weekly interval
- daily_cases: Cases for the end_date; vestigial column that was used to calculate weekly_cases
- pop: 2018 age populations for Indiana that's used to calculate prop_cases
\
ach_var_defs <- c("Age group", "", "", "", "", "", "", "", "", "Weekly count of COVID-19 confirmed cases by age group", "Number of cases scaled to per 1000 residents per age group") # table width responsive to length of var_defs text, so may not appear full.width # use show_header_names to get col names being used by tbl_summary tbl_summary(age_cases_heat, missing = "ifany", missing_text = "Missing", include = c(age_grp, weekly_cases, prop_cases)) %>% modify_header(update = list( label ~ 'Variable')) %>% modify_table_body(dplyr::mutate, defs = ach_var_defs) %>% modify_header(defs = "Definition") %>% # show_header_names() as_gt() %>% tab_options(table.align = "left") %>% cols_align("left", vars(stat_0, defs)) %>% as_raw_html()
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Historical Weekly COVID-19 Deaths by Age Group for Indiana
Description
Processed data for Demographics line charts that shows counts and trends of weekly COVID-19 deaths by age group.
Reference Entry
Script
Processing: process-demog-data.R
Raw Sources
Indiana Data Hub: COVID-19 CASE DEMOGRAPHICS
Notes
Other variables:
- date_text: date label for the chart
- tooltip: pop-up text for points in chart with death counts and date
\
adl_var_defs <- c("Date of the last day of the weekly interval", "Age group", "", "", "", "", "", "", "", "", "Weekly count of COVID-19 confirmed deaths by age group") # table width responsive to length of var_defs text, so may not appear full.width # use show_header_names to get col names being used by tbl_summary tbl_summary(age_death_line, missing = "ifany", missing_text = "Missing", include = c(end_date, agegrp, weekly_total)) %>% modify_header(update = list( label ~ 'Variable')) %>% modify_table_body(dplyr::mutate, defs = adl_var_defs) %>% modify_header(defs = "Definition") %>% # show_header_names() as_gt() %>% tab_options(table.align = "left") %>% cols_align("left", vars(stat_0, defs)) %>% as_raw_html()
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Historical Daily COVID-19 Hospital Admissions by Age Group for Indiana
Description
Raw data for the Hospitals line charts that shows daily COVID-19 hospital admissions by age group and gender.
Reference Entry
Script
Collection: scrape-regenstrief-tableau.R
Raw Sources
Regenstrief Institute: dashboard
Notes
This dataset is incomplete with random gaps between days.
\
ahl_var_defs <- c("Date (Daily)", "Age group", "", "", "", "", "", "", "", "", "", "Daily COVID-19 male hospital admissions by age group", "Daily COVID-19 female hospital admissions by age group", "Daily COVID-19 total hospital admissions by age group") # table width responsive to length of var_defs text, so may not appear full.width # use show_header_names to get col names being used by tbl_summary tbl_summary(age_hosp_line, missing = "ifany", missing_text = "Missing", include = everything()) %>% modify_header(update = list( label ~ 'Variable')) %>% modify_table_body(dplyr::mutate, defs = ahl_var_defs) %>% modify_header(defs = "Definition") %>% # show_header_names() as_gt() %>% tab_options(table.align = "left") %>% cols_align("left", vars(stat_0, defs)) %>% as_raw_html()
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Historical Daily ICU Beds and Ventilators for Indiana
Description
Raw data for the Static Charts Hospitalizations, ICU Beds and Ventilator Availability that shows resource counts of ICU beds and ventilators.
Reference Entry
Script
Collection: build-datasets.R
Raw Sources
Indiana Data Hub: COVID-19 BEDS AND VENTS
Notes
The source publishs daily excel spreadsheets with total resource counts, and these spreadsheets are collected and joined daily to produce a dataset with historical values.
\
bvc_var_defs <- c("Date (Daily)", "Total ICU beds", "Total ICU beds occupied with COVID-19 patients", "Total ICU beds occupied with non-COVID-19 patients", "Total available ICU beds", "Total ventilators", "Total ventilators being used by COVID-19 patients", "Total ventilators being used by non-COVID-19 patients", "Total available ventilators") # table width responsive to length of var_defs text, so may not appear full.width # use show_header_names to get col names being used by tbl_summary tbl_summary(beds_vents_complete, missing = "ifany", missing_text = "Missing", include = everything()) %>% modify_header(update = list( label ~ 'Variable')) %>% modify_table_body(dplyr::mutate, defs = bvc_var_defs) %>% modify_header(defs = "Definition") %>% # show_header_names() as_gt() %>% tab_options(table.align = "left") %>% cols_align("left", vars(stat_0, defs)) %>% cols_width(vars(stat_0) ~ "150px") %>% as_raw_html()
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Historical Google Maps Mobility Indices for Indiana
Description
Processed data for the Google Maps Mobility Indices line chart that shows percent differences from a mobility baseline that was calculated during the 5-week period Jan 3 – Feb 6, 2020. These percent changes show how lengths-of-stay at different locations have changed from pre-pandemic conditions.
Reference Entry
Script
Miscellaneous: goog-mob-line.R
Raw Sources
Google Mobility Reports: website
Notes
\
goog_var_defs <- c("Date (Daily)", "Length-of-stay (mobility) measurements are calculated for these location categories", "", "", "", "Percent difference from the mobility baseline for each category", "TRUE/FALSE binary for whether the date is on a weekend or not") # table width responsive to length of var_defs text, so may not appear full.width # use show_header_names to get col names being used by tbl_summary tbl_summary(goog_mob_ind, missing = "ifany", missing_text = "Missing", include = everything()) %>% modify_header(update = list( label ~ 'Variable')) %>% modify_table_body(dplyr::mutate, defs = goog_var_defs) %>% modify_header(defs = "Definition") %>% # show_header_names() as_gt() %>% tab_options(table.align = "left") %>% cols_align("left", vars(stat_0, defs)) %>% cols_width(vars(stat_0) ~ px(150)) %>% as_raw_html()
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Historical State Hospital Staff Shortages, Hospital Mortality Rate, Hospital Admissions and Ages Skewness of Admissions for Indiana
Description
Processed data for Hospitals line charts that shows state hospital staff shortages, hospital mortality rate, hospital admissions, and age skewness of hospital admissions towards older patients.
Reference Entry
Script
Process: process-hospitals-data.R
Raw Sources
Regenstrief Institute: dashboard
Department of Health and Human Services: COVID-19 Reported Patient Impact and Hospital Capacity by State Timeseries
Department of Health and Human Services: COVID-19 Reported Patient Impact and Hospital Capacity by Facility
Notes
Other variables:
- date: Ordered factor, Month Day format
\
msas_var_defs <- c("Percent of reporting hospitals that have reported staffing shortages for that day. That percentage is averaged over a rolling, seven day window", "Ratio of deaths of hospitalized COVID-19 patients and unique COVID-19 hospital admissions. Each rate is calculated over a rolling, 14-day window", "Daily total of unique individuals that have tested positive for COVID-19 and been admitted to a hospital on the that day. Those daily counts are averaged over a rolling, seven day window", "Measurement of the age makeup of the COVID-19 hospital admissions data. It's calculated over a rolling, 14 day window") # table width responsive to length of var_defs text, so may not appear full.width # use show_header_names to get col names being used by tbl_summary tbl_summary(hosp_msas_line, missing = "ifany", missing_text = "Missing", include = -date) %>% modify_header(update = list( label ~ 'Variable')) %>% modify_table_body(dplyr::mutate, defs = msas_var_defs) %>% modify_header(defs = "Definition") %>% # show_header_names() as_gt() %>% tab_options(table.align = "left") %>% cols_align("left", vars(stat_0, defs)) %>% cols_width(vars(stat_0) ~ px(150)) %>% as_raw_html()
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Local Hospital Capacity for Indiana
Description
Processed data for the Hospitals Local Hospital Capacity table that shows capacity measures and counts of COVID-19 patients for hospitals at the local level.
Reference Entry
Script
Process: process-hospitals-data.R
Raw Sources
Department of Health and Human Services: COVID-19 Reported Patient Impact and Hospital Capacity by State Timeseries
Notes
Other variables:
- hospital_name: char, Name of hospital
- address: char, Street address of hospital
- city_zip: char, City and zip code
- county_name: char, Name of county
- avgCovIcuTenKList: nested list, end_date and average daily number of ICU beds being used by confirmed and suspected COVID-19 patients over the weekly interval
- avgCovHospTenKList: nested list, end_date and average daily number of hospital beds being used by confirmed and suspected COVID-19 patients over the weekly interval
- avgTotImpBedsList: end_date and avgTotImpBeds, the average daily number of staffed total beds available over the weekly interval
\
num_end_dates <- hosp_react_tab %>% distinct(end_date) %>% summarize(num_dates = n()) %>% pull(num_dates) hrt_var_defs <- purrr::reduce(list( "Last day the data was updated for a particular hospital", rep("", num_end_dates), "Proportion of the seven-day average of occupied ICU beds to the seven-day average of available ICU beds.", "", "Proportion of the seven-day average of occupied hospital beds to the seven-day average of available hospital beds.", "" ), append) # table width responsive to length of var_defs text, so may not appear full.width # use show_header_names to get col names being used by tbl_summary tbl_summary(hosp_react_tab, missing = "ifany", missing_text = "Missing", include = c(end_date, sev_day_icu_perc_occup, sev_day_hosp_perc_occup)) %>% modify_header(update = list( label ~ 'Variable')) %>% modify_table_body(dplyr::mutate, defs = hrt_var_defs) %>% modify_header(defs = "Definition") %>% # show_header_names() as_gt() %>% tab_options(table.align = "left") %>% cols_align("left", vars(stat_0, defs)) %>% cols_width(vars(stat_0) ~ px(150)) %>% as_raw_html()
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Historical Daily Tests, Cases and Deaths by Age for Indiana
Description
Raw data for Demographics line charts that shows daily case and death counts by age group.
Reference Entry
Script
Collection: build-datasets.R
Raw Sources
Indiana Data Hub: COVID-19 CASE DEMOGRAPHICS
Notes
The source publishs daily excel spreadsheets with total resource counts, and these spreadsheets are collected and joined daily to produce a dataset with historical values.
Other variables:
- date: date, yyyy-mm-dd format
\
iac_var_defs <- c("Date (Daily)", "Age Group", "", "", "", "", "", "", "", "", "", "", "", "", "", "", "Number of cases by age group", "Number of deaths by age group", "Number of tests by age group", "Percent of daily cases", "Percent of daily deaths", "Percent of daily tests") # table width responsive to length of var_defs text, so may not appear full.width # use show_header_names to get col names being used by tbl_summary tbl_summary(ind_age_complete, missing = "ifany", missing_text = "Missing", include = everything()) %>% modify_header(update = list( label ~ 'Variable')) %>% modify_table_body(dplyr::mutate, defs = iac_var_defs) %>% modify_header(defs = "Definition") %>% # show_header_names() as_gt() %>% tab_options(table.align = "left") %>% cols_align("left", vars(stat_0, defs)) %>% cols_width(vars(stat_0) ~ px(190)) %>% as_raw_html()
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Historical Daily Cases and Deaths by Race for Indiana
Description
Raw data that shows daily case and death counts by race.
Reference Entry
Script
Collection: build-datasets.R
Raw Sources
The Covid Tracking Project: The COVID Racial Data Tracker
Notes
The source publishs data every 3 or 4 days.
\
# table width responsive to length of var_defs text, so may not appear full.width # use show_header_names to get col names being used by tbl_summary tbl_summary(ind_race_complete, missing = "ifany", missing_text = "Missing", include = c(date, everything())) %>% modify_header(update = list( label ~ 'Variable')) %>% as_gt() %>% tab_options(table.align = "left") %>% cols_align("left", vars(stat_0)) %>% as_raw_html()
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Historical Weekly Median Age of Cases, Weekly Tests and Deaths for Indiana
Description
Processed data for the Demographics bubble chart that shows the number of tests, number of deaths, and median age of the cases per week.
Reference Entry
Script
Processing: process-demog-data.R
Raw Sources
Indiana Data Hub: COVID-19 CASE DATA
Notes
Other variables:
- end_date: ordered factor, Month Day format; end date of weekly interval
\
mab_var_defs <- c("Median age of cases for that week", "Number of tests for that week", "Number of deaths for that week") # table width responsive to length of var_defs text, so may not appear full.width # use show_header_names to get col names being used by tbl_summary tbl_summary(median_age_bubble, missing = "ifany", missing_text = "Missing", include = -end_date) %>% modify_header(update = list( label ~ 'Variable')) %>% modify_table_body(dplyr::mutate, defs = mab_var_defs) %>% modify_header(defs = "Definition") %>% # show_header_names() as_gt() %>% tab_options(table.align = "left") %>% cols_align("left", vars(stat_0, defs)) %>% cols_width(vars(stat_0) ~ px(200)) %>% as_raw_html()
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Historical Daily Hospital Admissions and Deaths for Indiana
Description
Raw data for the Hospitals line charts that shows daily COVID-19 hospital admissions, hospital deaths, and hospital death rate.
Reference Entry
Script
Collection: scrape-regenstrief-tableau.R
Raw Sources
Regenstrief Institute: dashboard
Notes
This dataset is incomplete with random gaps between days.
\
mhl_var_defs <- c("Date (Daily)", "Number of individuals hospitalized for COVID-19 who died while in the hospital", "Number of unique individuals who have been hospitalized and tested positive for COVID-19", "Percent of individuals hospitalized for COVID-19 who died while in the hospital") # table width responsive to length of var_defs text, so may not appear full.width # use show_header_names to get col names being used by tbl_summary tbl_summary(mort_hosp_line, missing = "ifany", missing_text = "Missing", include = everything()) %>% modify_header(update = list( label ~ 'Variable')) %>% modify_table_body(dplyr::mutate, defs = mhl_var_defs) %>% modify_header(defs = "Definition") %>% # show_header_names() as_gt() %>% tab_options(table.align = "left") %>% cols_align("left", vars(stat_0, defs)) %>% cols_width(vars(stat_0) ~ "180px") %>% as_raw_html()
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Historical Weekly Positivity Rates and Daily Cases per 100,000 Indiana Residents
Description
Processed data for the Indiana COVIDcast Dashboard that shows weekly positivity rate and daily cases per 100,000 residents per metropolitan statistical area.
Reference Entry
Scripts
Processing: process-hist-regional-dat.R
Raw Sources
covidcast R package: website
Michigan Disease Surveillance System: website
Wisconsin Department of Health Services: website
Illinois Department of Public Health: website
Indiana Data Hub: website
Notes
The missing values for pos_rate are partly because this dataset has a row for every day and the positivity rate is calculated every week. The other missing values are for Cincinnati, Louisville, and Evansville. At the time this dashboard was created, those states with counties included in those areas didn't publicly release the necessary data to calcuate their positivity rates.
Other variables:
- geo_value: FIPS codes for msa
- start_date: Start date of the weekly interval for pos_rate
- data_date: Date when data was last updated
\
msa_hist_var_defs <- purrr::reduce(list("date for daily cases_100k", "Metropolitan Statistical Area", rep("", 15), "Daily cases per 100,000 residents per MSA", "Weekly positivity rate per MSA", ""), append) # table width responsive to length of var_defs text, so may not appear full.width # use show_header_names to get col names being used by tbl_summary tbl_summary(msa_cases100_posrate_historic, missing = "ifany", missing_text = "Missing", include = c(date, msa, cases_100k, pos_rate)) %>% modify_header(update = list( label ~ 'Variable')) %>% modify_table_body(dplyr::mutate, defs = msa_hist_var_defs) %>% modify_header(defs = "Definition") %>% # show_header_names() as_gt() %>% tab_options(table.align = "left") %>% cols_align("left", vars(stat_0, defs)) %>% as_raw_html()
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Historical Daily Values of Delphi Research Groups Combined Indicator for Indiana
Description
Processed data for the Indiana COVIDcast Dashboard that shows historic daily values of Delphi Research Group's Combined Indicator for each methropolitan statistical area.
Reference Entry
Scripts
Processing: process-dashboard-data.R
Raw Sources
covidcast R package: website
Notes
\
dcl_var_defs <- purrr::reduce(list("Date (Daily)", "Metropolitan Statistical Area", rep("", 15), "Delphi Research Group's “Combined” indicator"), append) # table width responsive to length of var_defs text, so may not appear full.width # use show_header_names to get col names being used by tbl_summary tbl_summary(dash_ci_line, missing = "ifany", missing_text = "Missing", include = c(time_value, name, value)) %>% modify_header(update = list(label ~ 'Variable')) %>% modify_table_body(dplyr::mutate, defs = dcl_var_defs) %>% modify_header(defs = "Definition") %>% # show_header_names() as_gt() %>% tab_options(table.align = "left") %>% cols_align("left", vars(stat_0, defs)) %>% as_raw_html()
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Historical Weekly COVID-19 Statistics and Counts for Illinois Counties
Description
Raw data for the Indiana COVIDcast Dashboard that shows various weekly COVID-19 county statistics for Illinois
Reference Entry
Scripts
Collection: build-regional-dat.R
Raw Sources
Illinois Department of Public Health: website
Notes
These data are published in weekly intervals into a HTML table then scraped and collected.
There are other missing data not shown in the table below. Illinois DPH changes/improves the format of their webpage from time to time, and I haven't been changing my scraping code to match in a timely manner. They do have a data portal which has cases, tests, and deaths for each county, but not a historical dataset with exact fields as below. Here are weekly ranges that are missing:
2021-7-18 to 2021-7-24
2021-7-25 to 2021-7-31
2021-9-12 to 2021-9-18
2021-9-5 to 2021-9-11
2021-9-26 to 2021-10-9
2021-10-10 to 2021-10-16
Other variables:
- week: int; week of the year
- County: char; Illinois county name
- New Cases per 100,000: string; format: "\<int> cases" or "\<int> per 100k" or "\<int> per 100kwarning"
- Test Positivity %: string; format: "\<float>%\r\n New Tests: \<int>"
- (%) CLI ED Visits, Adults: string; format: "\<int>%"
- ICU (%) Available: string; format: "\<float>%"
\
ill_var_defs <- c("First day of the weekly interval", "Last day of the weekly interval", "Number of COVID-19 deaths per week per county", "") # table width responsive to length of var_defs text, so may not appear full.width # use show_header_names to get col names being used by tbl_summary tbl_summary(illinois_tests_complete, missing = "ifany", missing_text = "Missing", include = c(start_date, end_date, `Number of Deaths`)) %>% modify_header(update = list(label ~ 'Variable')) %>% modify_table_body(dplyr::mutate, defs = ill_var_defs) %>% modify_header(defs = "Definition") %>% # show_header_names() as_gt() %>% tab_options(table.align = "left") %>% cols_align("left", vars(stat_0, defs)) %>% as_raw_html()
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Historical Daily COVID-19 Test Results for Indiana Counties
Description
Raw data for the Indiana COVIDcast Dashboard that shows daily COVID-19 county test results for Indiana
Reference Entry
Scripts
Collection: build-regional-dat.R
Raw Sources
Indiana Data Hub: COVID-19 COUNTY-WIDE TEST, CASE, AND DEATH TRENDS
Notes
Other variables:
- county: County name
\
ind_var_defs <- c("Date (Daily)", "Number of COVID-19 cases per day per county", "Number of COVID-19 tests per day per county") # table width responsive to length of var_defs text, so may not appear full.width # use show_header_names to get col names being used by tbl_summary tbl_summary(ind_tests_complete, missing = "ifany", missing_text = "Missing", include = c(date, positives, num_tests)) %>% modify_header(update = list(label ~ 'Variable')) %>% modify_table_body(dplyr::mutate, defs = ind_var_defs) %>% modify_header(defs = "Definition") %>% # show_header_names() as_gt() %>% tab_options(table.align = "left") %>% cols_align("left", vars(stat_0, defs)) %>% as_raw_html()
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Historical Daily COVID-19 Test Results for Michigan Counties
Description
Raw data for the Indiana COVIDcast Dashboard that shows daily COVID-19 county test results for Michigan
Reference Entry
Scripts
Collection: build-regional-dat.R
Raw Sources
Michigan Department of Health and Human Services: COVID-19 Tests by County
Notes
Other variables:
- county: County name
\
mich_var_defs <- c("Date (Daily)", "Number of COVID-19 positive tests per day per county", "Number of COVID-19 negative tests per day per county", "Total number of COVID-19 tests per day per county") # table width responsive to length of var_defs text, so may not appear full.width # use show_header_names to get col names being used by tbl_summary tbl_summary(mich_tests_complete, missing = "ifany", missing_text = "Missing", include = c(date, positive, negative, total)) %>% modify_header(update = list(label ~ 'Variable')) %>% modify_table_body(dplyr::mutate, defs = mich_var_defs) %>% modify_header(defs = "Definition") %>% # show_header_names() as_gt() %>% tab_options(table.align = "left") %>% cols_align("left", vars(stat_0, defs)) %>% as_raw_html()
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OpenTable Year-Over-Year Seated Diners for Regional States
Description
Processed data for the OpenTable Year-Over-Year Seated Diners line charts that shows reservation data from a sample of restaurants across Indiana and other regional states. Each data point is the median daily percent difference in seated diners from 2019 to either 2020 or 2021 depending on the date.
Reference Entry
Script
Miscellaneous: opentab-rest-line.R
Raw Sources
OpenTable: State of the Industry
Notes
\
ot_var_defs <- c("Date (Daily)", "State", "", "", "", "", "", "", "Median daily percent difference in seated diners for each state", "TRUE/FALSE binary for whether the date is on a weekend or not") # table width responsive to length of var_defs text, so may not appear full.width # use show_header_names to get col names being used by tbl_summary tbl_summary(open_tab_reg, missing = "ifany", missing_text = "Missing", include = c(date, everything())) %>% modify_header(update = list( label ~ 'Variable')) %>% modify_table_body(dplyr::mutate, defs = ot_var_defs) %>% modify_header(defs = "Definition") %>% # show_header_names() as_gt() %>% tab_options(table.align = "left") %>% cols_align("left", vars(stat_0, defs)) %>% cols_width(vars(stat_0) ~ px(150)) %>% as_raw_html()
\ \ \
Historical Daily COVID-19 Test Results for Wisconsin Counties
Description
Raw data for the Indiana COVIDcast Dashboard that shows daily COVID-19 county test results for Wisconsin
Reference Entry
Scripts
Collection: build-regional-dat.R
Raw Sources
Wisconsin Department of Health Services: COVID-19 Historical Data by County
Notes
Other variables:
- county: County name
\
wisc_var_defs <- c("Date (Daily)", "Number of COVID-19 positive tests per day per county", "Number of COVID-19 negative tests per day per county", "") # table width responsive to length of var_defs text, so may not appear full.width # use show_header_names to get col names being used by tbl_summary tbl_summary(wisc_tests_complete, missing = "ifany", missing_text = "Missing", include = c(date, positive, negative)) %>% modify_header(update = list(label ~ 'Variable')) %>% modify_table_body(dplyr::mutate, defs = wisc_var_defs) %>% modify_header(defs = "Definition") %>% # show_header_names() as_gt() %>% tab_options(table.align = "left") %>% cols_align("left", vars(stat_0, defs)) %>% as_raw_html()
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