Simulated epidemiological data with independent spatial fields by year

A simulated longitudinal dataset containing complete environmental exposure profiles for fixed field locations observed across multiple years. The dataset is intended for demonstrating distributed exposure-lag models with separate spatial fields by year.

Usage

spatial_year

Format

A data frame with rows representing temporal observations within epidemic exposure profiles and the following variables:

epi_id: Unique identifier combining field location and year.
location_id: Identifier for the field location.
year: Year identifying the independent spatial field.
block: Experimental block identifier within a year.
block_id: Identifier combining year and experimental block.
time: Chronological time index within each epidemic profile.
x_coord: First numeric spatial coordinate of the field location.
y_coord: Second numeric spatial coordinate of the field location.
tmean: Daily mean temperature in degrees Celsius.
wetness: Daily leaf wetness duration in hours.
rain: Daily rainfall in millimeters.
y: Non-negative count disease outcome repeated across the rows of each epidemic profile.

Source

Simulated for the EpiExposure package.

Details

The response and location-level descriptors are repeated across the temporal rows belonging to the same epidemic because each complete exposure profile is associated with one final epidemic-level disease outcome.

Examples

data("spatial_year", package = "EpiExposure")
head(spatial_year)
#>      epi_id location_id year block block_id time    x_coord  y_coord    tmean
#> 1 L001_2022        L001 2022   B01 2022_B01    0 -0.6698125 0.622697 24.38006
#> 2 L001_2022        L001 2022   B01 2022_B01    1 -0.6698125 0.622697 24.53832
#> 3 L001_2022        L001 2022   B01 2022_B01    2 -0.6698125 0.622697 24.90186
#> 4 L001_2022        L001 2022   B01 2022_B01    3 -0.6698125 0.622697 26.04159
#> 5 L001_2022        L001 2022   B01 2022_B01    4 -0.6698125 0.622697 23.60107
#> 6 L001_2022        L001 2022   B01 2022_B01    5 -0.6698125 0.622697 25.79864
#>     wetness      rain y
#> 1  4.903199 12.904436 3
#> 2  6.781023  7.651138 3
#> 3 11.195548  0.000000 3
#> 4 10.530333  0.000000 3
#> 5 10.322681  0.000000 3
#> 6 12.433350  0.000000 3