Read in the dataset of incident case counts

Each row of the table corresponds to a single facilities' cases for a reference-date/report-date/disease tuple. We want to aggregate these counts to the level of geographic aggregate/report-date/reference-date/disease.

Usage

read_data(
  data_path,
  disease = c("COVID-19", "Influenza", "test"),
  state_abb,
  report_date,
  max_reference_date,
  min_reference_date
)

Arguments

data_path

The path to the local file. This could contain a glob and must be in parquet format.

disease

One of "COVID-19" or "Influenza"

state_abb

A two-letter uppercase abbreviation. "US" is also an option

report_date

The desired single report date

max_reference_date, min_reference_date

The first and last reference dates, inclusive, of the timeseries

Value

A dataframe with one or more rows and columns report_date, reference_date, state_abb, confirm

Details

We handle two distinct cases for geographic aggregates:

1. A single state: Subset to facilities in that state only and aggregate up to the state level 2. The US overall: Aggregate over all facilities without any subsetting

Note that we do not apply exclusions here. The exclusions are applied later, after the aggregations. That means that for the US overall, we aggregate over points that might potentially be excluded at the state level. Our recourse in this case is to exclude the US overall aggregate point.