mpoxdat: Mpox reporting data from the 2022 New York City outbreak
mpoxdat.RdSurveillance line list data provided by the New York City (NYC) Health Department at https://github.com/nychealth/mpox_nowcast_eval, to accompany a nowcasting performance evaluation (doi: 10.2196/56495). Patients with a confirmed or probable mpox diagnosis or illness onset from July 8 through September 30, 2022 were included. The original dataset was aggregated and pre-processed as described in the note below.
Usage
data(mpoxdat)Format
A data frame with 1,417 rows and 4 variables:
- dx_date
Date. Specimen collection date of the first positive result – the event date.- dx_report_date
Date. When the Health Department received that result – the report date.- race
character. Synthetic; see the note.- n
integer. Number of cases with that combination.
Details
This is count data: each row holds the number of cases sharing a diagnosis date, a report date and a race. The columns are as follows:
dx_date: is the specimen collection date of the first positive mpox laboratory result,dx_report_date: is the date the report of first positive mpox laboratory result was received by the NYC Health Department,n: the case count of individuals within those dates.race: the race corresponding to those cases. Race was randomly assigned with probabilities "Non-Hispanic White" = 0.309, "Hispanic" = 0.283, "Black" = 0.202, "Asian" = 0.156, and "Other" = 0.05 which follow what has been reported for the US Census.
Note
While dx_date, dx_report_date and n correspond to actual observed data the race was
constructed exclusively for the examples of this package. It is a synthetic (simulated)
variable and does not correspond to any reality.
References
ROHRER, Rebecca, et al. Nowcasting to Monitor Real-Time Mpox Trends During the 2022 Outbreak in New York City: Evaluation Using Reportable Disease Data Stratified by Race or Ethnicity. Online Journal of Public Health Informatics, 2025, vol. 17, no 1, p. e56495.
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(mpoxdat)
head(mpoxdat)
#> # A tibble: 6 × 4
#> # Rowwise:
#> dx_date dx_report_date race n
#> <date> <date> <chr> <int>
#> 1 2022-07-08 2022-07-12 Asian 4
#> 2 2022-07-08 2022-07-12 Black 6
#> 3 2022-07-08 2022-07-12 Hispanic 6
#> 4 2022-07-08 2022-07-12 Non-Hispanic White 6
#> 5 2022-07-08 2022-07-13 Asian 2
#> 6 2022-07-08 2022-07-13 Black 3
# Count data, and daily rather than weekly -- unlike denguedat.
mpox <- tbl_now(mpoxdat,
event_date = dx_date, report_date = dx_report_date,
case_count = n, strata = race, verbose = FALSE
)
mpox
#> # A tibble: 1,417 × 7
#> # Data type: "count-incidence"
#> # Frequency: Event: `days` | Report: `days`
#> dx_date dx_report_date race n .event_num .report_num .delay
#> <date> <date> <chr> <int> <dbl> <dbl> <dbl>
#> [event_date] [report_date] [strata] [cas… [...] [...] [...]
#> 1 2022-07-08 2022-07-12 Asian 4 0 4 4
#> 2 2022-07-08 2022-07-12 Black 6 0 4 4
#> 3 2022-07-08 2022-07-12 Hispanic 6 0 4 4
#> 4 2022-07-08 2022-07-12 Non-Hispanic… 6 0 4 4
#> 5 2022-07-08 2022-07-13 Asian 2 0 5 5
#> 6 2022-07-08 2022-07-13 Black 3 0 5 5
#> 7 2022-07-08 2022-07-13 Hispanic 8 0 5 5
#> 8 2022-07-08 2022-07-13 Non-Hispanic… 5 0 5 5
#> 9 2022-07-08 2022-07-14 Black 1 0 6 6
#> 10 2022-07-08 2022-07-14 Hispanic 3 0 6 6
#> # ────────────────────────────────────────────────────────────────────────────────
#> # Now: 2023-05-19 | Event date: "dx_date" | Report date: "dx_report_date"
#> # Strata: "race"
#> # ────────────────────────────────────────────────────────────────────────────────
#> # ℹ 1,407 more rows
# A short, sharp outbreak: about three months of data.
range(mpoxdat$dx_date)
#> [1] "2022-07-08" "2022-10-12"
sum(mpoxdat$n)
#> [1] 3323