denguedat: Dengue fever individual-level reporting data from Puerto Rico

Surveillance data from CDC Division of Vector-Borne Diseases. 1990-2010 case reporting data included.

Usage

data(denguedat)

Format

A data frame with 52,987 rows (one per case) and 3 variables:

onset_week

Date. The week symptoms began – the event date.

report_week

Date. The week the case reached the surveillance system – the report date. Always on or after onset_week.

gender

character. "Male" or "Female". Synthetic; see the note.

Details

Each row represents a case with the columns indicating the following:

• onset_week: the week of symptom onset.

• report_week: the week of case report.

• gender: the gender of the infected individual (randomly assigned with 0.5:0.5 probability of "Male"/"Female").

Note

Data originally from the NobBS package. While onset_week and report_week correspond to actual observed data the gender was constructed exclusively for the examples of NobBS. It is a synthetic (simulated) variable and does not correspond to any reality.

References

MCGOUGH, Sarah F., et al. Nowcasting by Bayesian Smoothing: A flexible, generalizable model for real-time epidemic tracking. PLoS computational biology, 2020, vol. 16, no 4, p. e1007735.

See also

tbl_now() to declare the date columns; summary() and diagnose() to inspect the result; the package's other datasets – denguedat, mpoxdat, flusight, covid_colombia, covid_us and hai_bucaramanga.

Examples

data(denguedat)
head(denguedat)
#>   onset_week report_week gender
#> 1 1990-01-01  1990-01-01   Male
#> 2 1990-01-01  1990-01-01 Female
#> 3 1990-01-01  1990-01-01 Female
#> 4 1990-01-01  1990-01-08 Female
#> 5 1990-01-01  1990-01-08   Male
#> 6 1990-01-01  1990-01-15 Female

# The two dates every nowcast needs. Weekly data, twenty years of it.
range(denguedat$onset_week)
#> [1] "1990-01-01" "2010-11-29"

# Declaring them turns the data frame into a tbl_now.
dengue <- tbl_now(denguedat,
  event_date = onset_week, report_date = report_week,
  strata = gender, verbose = FALSE
)
dengue
#> # A tibble:  52,987 × 6
#> # Data type: "linelist"
#> # Frequency: Event: `weeks` | Report: `weeks`
#>    onset_week   report_week   gender   .event_num .report_num .delay
#>    <date>       <date>        <chr>         <dbl>       <dbl>  <dbl>
#>    [event_date] [report_date] [strata]      [...]       [...]  [...]
#>  1 1990-01-01   1990-01-01    Male              0           0      0
#>  2 1990-01-01   1990-01-01    Female            0           0      0
#>  3 1990-01-01   1990-01-01    Female            0           0      0
#>  4 1990-01-01   1990-01-08    Female            0           1      1
#>  5 1990-01-01   1990-01-08    Male              0           1      1
#>  6 1990-01-01   1990-01-15    Female            0           2      2
#>  7 1990-01-01   1990-01-15    Female            0           2      2
#>  8 1990-01-01   1990-01-15    Female            0           2      2
#>  9 1990-01-01   1990-01-22    Female            0           3      3
#> 10 1990-01-01   1990-01-08    Female            0           1      1
#> # ────────────────────────────────────────────────────────────────────────────────
#> # Now: 2010-12-20 | Event date: "onset_week" | Report date: "report_week"
#> # Strata: "gender"
#> # ────────────────────────────────────────────────────────────────────────────────
#> # ℹ 52,977 more rows

# Most cases arrive within a week or two of onset; a few take much longer.
summary(as.numeric(dengue$.delay))
#>    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
#>   0.000   1.000   1.000   1.738   2.000  26.000