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covid_us: CDC COVID-19 Case Surveillance Public Use Data (2020)

Source: R/data.R
covid_us.Rd

A compact aggregation of the U.S. CDC's individual-level COVID-19 case surveillance database. It is the package's worked example for two different things: batch reporting, and the revision process – the optional third date a surveillance record can carry.

Usage

data(covid_us)

Format

A data frame with 192,953 rows and six variables:

onset_dt

Date. The event date – symptom onset.

pos_spec_dt

Date. The report date – collection of the first positive specimen.

cdc_report_dt

Date. The revision date – when the case was registered at CDC.

current_status

character. CDC's classification, either "Laboratory-confirmed case" or "Probable Case". Map it with revision_levels (see above).

sex

character. "Female", "Male", "Other", "Unknown" or "Missing".

n

integer. Number of cases sharing that combination.

Source

Centers for Disease Control and Prevention (CDC), COVID-19 Response. COVID-19 Case Surveillance Public Use Data (version date: June 21, 2024). https://data.cdc.gov/Case-Surveillance/COVID-19-Case-Surveillance-Public-Use-Data/vbim-akqf/about_data. COVID-19 case surveillance data are collected by jurisdictions and reported voluntarily to CDC.

Details

Each row is a unique (onset date, specimen date, CDC report date, status, sex) combination with the number of cases n.

The three dates

The source file carries four date columns. cdc_case_earliest_dt is derived by CDC as the earliest of the others, and equals onset_dt for 99.997% of the rows kept here, so it is dropped as redundant. The three that remain are the only chain that runs forward in time, and they map onto the three roles a tbl_now() knows about:

onset_dt

the event – symptoms begin.

pos_spec_dt

the report – the first positive specimen is collected, which is when the surveillance system first sees the case.

cdc_report_dt

the revision – the case is registered at CDC with a status.

current_status and revision_levels

current_status is kept in CDC's own words rather than recoded, because translating it is exactly what tbl_now(revision_levels = ) is for:

revision_levels = c(
  "Laboratory-confirmed case" = "confirmed",
  "Probable Case"             = "pending"
)

A probable case is one that met the clinical and epidemiological criteria without meeting the laboratory-confirmed definition. Every row here has a positive specimen, so "probable" means the specimen was collected and the case was never laboratory-settled – "pending" in this package's vocabulary. Note what is not there: CDC does not withdraw cases, so "retracted" does not occur in this dataset. It is a two-outcome revision process, and code that needs a retraction has to look elsewhere.

The relationship between the outcome and the revision delay is real rather than fabricated: probable cases are registered a median of 2 days after the specimen, laboratory-confirmed ones 4 days.

What was kept

Cases where all three dates are present, correctly ordered (onset_dt <= pos_spec_dt <= cdc_report_dt) and falling entirely within 2020 – a self-consistent "as of the end of 2020" snapshot. Rows out of order are data-entry errors; rows missing a date cannot be placed on the chain at all. See data-raw/covid_us.R for the exact duckdb aggregation of the 14 GB source file.

The reporting delay is enormous and heavily right-skewed: cases reached CDC not smoothly but in large backlog dumps – a textbook batch-reporting pattern that diagnose_batches() and transport_discriminant() recover.

See also

tbl_now() to declare the date columns; add_revision_date() to attach the third one to an object that has none; revised_cases to count the outcomes; summary() and diagnose() to inspect the result; the package's other datasets – denguedat, mpoxdat, flusight, covid_colombia and hai_bucaramanga.

Examples

library(dplyr)
#> 
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union

data(covid_us)

# The three dates with CDC's labels translated to this package's vocabulary.
covid_us <- covid_us |>
  filter(onset_dt <= as.Date("2020-02-01"))

tn3 <- tbl_now(
  covid_us,
  event_date       = onset_dt,
  report_date      = pos_spec_dt,
  revision_date    = cdc_report_dt,
  revision_type    = current_status,
  revision_levels = c(
    "Laboratory-confirmed case" = "confirmed",
    "Probable Case"             = "pending"
  ),
  case_count = n,
  strata     = sex,
  data_type  = "count-incidence",
  verbose    = FALSE
)