Kaiser Family Foundation US County-level ICU bed data
kff_icu_beds()a data.frame
Other data-import:
acaps_government_measures_data(),
acaps_secondary_impact_data(),
apple_mobility_data(),
beoutbreakprepared_data(),
cci_us_vaccine_data(),
cdc_aggregated_projections(),
cdc_excess_deaths(),
cdc_social_vulnerability_index(),
coronadatascraper_data(),
coronanet_government_response_data(),
cov_glue_lineage_data(),
cov_glue_newick_data(),
cov_glue_snp_lineage(),
covidtracker_data(),
descartes_mobility_data(),
ecdc_data(),
econ_tracker_consumer_spending,
econ_tracker_employment,
econ_tracker_unemp_data,
economist_excess_deaths(),
financial_times_excess_deaths(),
google_mobility_data(),
government_policy_timeline(),
jhu_data(),
jhu_us_data(),
nytimes_county_data(),
oecd_unemployment_data(),
owid_data(),
param_estimates_published(),
test_and_trace_data(),
us_county_geo_details(),
us_county_health_rankings(),
us_healthcare_capacity(),
us_hospital_details(),
us_state_distancing_policy(),
usa_facts_data(),
who_cases()
Other healthcare-systems:
us_hospital_details()
res = kff_icu_beds()
colnames(res)
#> [1] "fips" "county"
#> [3] "st" "state"
#> [5] "hospitals_in_cost_reports" "Hospitals_in_HC"
#> [7] "all_icu" "Total_pop"
#> [9] "60plus" "60plus_pct"
#> [11] "60plus_per_each_icu_bed"
head(res)
#> # A tibble: 6 × 11
#> fips county st state hospitals_in_co… Hospitals_in_HC all_icu Total_pop
#> <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 01001 Autauga AL Alabama 1 1 6 55036
#> 2 01003 Baldwin AL Alabama 3 3 51 203360
#> 3 01005 Barbour AL Alabama 1 1 5 26201
#> 4 01007 Bibb AL Alabama 1 1 0 22580
#> 5 01009 Blount AL Alabama 1 1 6 57667
#> 6 01011 Bullock AL Alabama 1 1 0 10478
#> # … with 3 more variables: `60plus` <dbl>, `60plus_pct` <dbl>,
#> # `60plus_per_each_icu_bed` <dbl>
dplyr::glimpse(res)
#> Rows: 3,142
#> Columns: 11
#> $ fips <chr> "01001", "01003", "01005", "01007", "01009",…
#> $ county <chr> "Autauga", "Baldwin", "Barbour", "Bibb", "Bl…
#> $ st <chr> "AL", "AL", "AL", "AL", "AL", "AL", "AL", "A…
#> $ state <chr> "Alabama", "Alabama", "Alabama", "Alabama", …
#> $ hospitals_in_cost_reports <dbl> 1, 3, 1, 1, 1, 1, 1, 2, 0, 1, 1, 1, 2, 1, 0,…
#> $ Hospitals_in_HC <dbl> 1, 3, 1, 1, 1, 1, 1, 2, 0, 1, 1, 1, 2, 1, 0,…
#> $ all_icu <dbl> 6, 51, 5, 0, 6, 0, 7, 24, 0, 0, 6, 0, 0, 4, …
#> $ Total_pop <dbl> 55036, 203360, 26201, 22580, 57667, 10478, 2…
#> $ `60plus` <dbl> 10523, 53519, 6150, 4773, 13600, 2371, 5151,…
#> $ `60plus_pct` <dbl> 0.191, 0.263, 0.235, 0.211, 0.236, 0.226, 0.…
#> $ `60plus_per_each_icu_bed` <dbl> 1754, 1049, 1230, NA, 2267, NA, 736, 1130, N…
summary(res)
#> fips county st state
#> Length:3142 Length:3142 Length:3142 Length:3142
#> Class :character Class :character Class :character Class :character
#> Mode :character Mode :character Mode :character Mode :character
#>
#>
#>
#>
#> hospitals_in_cost_reports Hospitals_in_HC all_icu
#> Min. : 0.000 Min. : 0.000 Min. : 0.00
#> 1st Qu.: 1.000 1st Qu.: 1.000 1st Qu.: 0.00
#> Median : 1.000 Median : 1.000 Median : 0.00
#> Mean : 1.439 Mean : 1.457 Mean : 23.64
#> 3rd Qu.: 2.000 3rd Qu.: 2.000 3rd Qu.: 12.00
#> Max. :74.000 Max. :76.000 Max. :2126.00
#>
#> Total_pop 60plus 60plus_pct 60plus_per_each_icu_bed
#> Min. : 74 Min. : 27 Min. :0.0580 Min. : 40
#> 1st Qu.: 10945 1st Qu.: 2813 1st Qu.:0.2120 1st Qu.: 715
#> Median : 25692 Median : 6307 Median :0.2440 Median :1089
#> Mean : 102166 Mean : 21310 Mean :0.2473 Mean :1300
#> 3rd Qu.: 67445 3rd Qu.: 16084 3rd Qu.:0.2780 3rd Qu.:1639
#> Max. :10105722 Max. :1800341 Max. :0.6420 Max. :8469
#> NA's :1665