Prepare SaTScan Case File

Usage

prep_cas(
  df,
  loc_id,
  time = NULL,
  cases = NULL,
  covars = NULL,
  style = c("casewise", "aggregated"),
  time_precision = c("day", "month", "year", "generic")
)

Arguments

df

Data frame containing case data.

loc_id

Column name for location ID (unquoted).

time

Column name for time/date (unquoted, optional).

cases

Column name for case counts (unquoted, optional). If NULL, assumes 1 case per row (casewise).

covars

Character vector of covariate column names.

style

Case input style:

• "casewise": Each row is a single case (cases=1).

• "aggregated": Rows represent counts.

time_precision

Time resolution for formatting: "day", "month", "year", or "generic".

Value

A satscan_table object of kind "cas".

Details

Prepares a case file for SaTScan, enforcing strict sparsity (no zero-case rows) and handling time precision formatting.

SaTScan File Specification

The Case File has the following structure: <LocationID> <NoCases> <Date> <Covariate1> ...

• LocationID: Character or numeric identifier. Matching ID must exist in Geo file.

• NoCases: Number of cases. For "casewise" style without a count column, this is set to 1. Zero-case rows are removed (implicit zeros).

• Date: Formatted according to time_precision:

  • "day": YYYY/MM/DD

  • "month": YYYY/MM

  • "year": YYYY

  • "generic": Time string/number

• Covariates: Optional categorical variables.

See also

ss_cas() for the new ss_tbl interface.

Examples

if (FALSE) { # \dontrun{
# aggregated daily
head(my_daily_data)
#   zipcode       date cases age_group
# 1   10001 2023-01-01     2     child
# 2   10002 2023-01-01     0     child  <-- Removed

cas_obj <- prep_cas(my_daily_data,
    loc_id = zipcode, time = date, cases = cases,
    covars = "age_group", time_precision = "day"
)

# casewise
head(my_cases)
#      id diagnosis_date
# 1 P001     2023-01-15

cas_obj2 <- prep_cas(my_cases,
    loc_id = id, time = diagnosis_date,
    style = "casewise", time_precision = "day"
)
} # }