expoure_estimate_simple: Assess the environmental exposure using the simplest method:...

In Spatial-R/EnvExpInd: Environmental Exposure on the Individual Level

Description

Using the nearest surveillance site as the refrence site to estimate the pollutant exposure.

Usage

expoure_estimate_simple(
  individual_data,
  individual_id,
  reference_id,
  exposure_date,
  pollutant_data,
  pollutant_site = "site",
  pollutant_date = "date",
  pollutant_name = c("pm10", "so2"),
  estimate_interval
)

Arguments

individual_data	data.frame, inludes the refrence id, individual_id and exposure_date
individual_id	character, variable name in the individual_data, which represents the unique id for each individual
refrence_id	character, varibale name in the individual_data, which represents the nearest surveillance site for each individual
exposure_date	character, varibale name in the individual_data, which represents the start date to estimate the environment exposure
pollutant_data	data.frame, contains the pollutant and site informatin. One column represents the site information and other columns represent the concentration of pollutants
pollutant_site	character, varibale name in the pollutant_data, which represents the monitoring site information
pollutant_date	character, varibale name in the pollutant_data, which represents the surveillance date for pollutant concentration
pollutant_name	vector, varibale names in the pollutant_data, which represent the name of the target pollutants to be estimated
estimate_interval	continue numeric vector, the estimation period, for example: 0:30, for each individual we estimate the environment exposure ranging from the exposure_date to exposure_date + 30 days

Value

A list. For each element in the list, there is a dataframe with the first column representing the individual id, the remaining columns represent the exposure estimation in different time points.

Author(s)

Bing Zhang, https://github.com/Spatial-R/EnvExpInd

Examples

 library(EnvExpInd)
 individual_data$date <- as.Date(individual_data$date)
 pollutant_data$date <- as.Date(pollutant_data$date)
 pollutant_data_full <- timeseries_imput(data= pollutant_data,
     date_var = "date",site_var = "site.name",imput_col = 3:8)
 pollutant_data_tem <- merge(pollutant_data_full,site_data,by.x = "site.name",by.y = "site")
 individual_data$refrence_id <- get_refrence_id_simple(
   individual_data = individual_data,
   individual_lat = "lat",
   individual_lon = "lon",
   individual_id = "id",
   site_data = site_data,
   site_lon = "lon",
   site_lat = "lat",
   site_id = "site")
expoure_estimate_simple(
   individual_data = individual_data,
   individual_id = "id",
   refrence_id = "refrence_id",
   exposure_date = "date",
   pollutant_data = pollutant_data_tem,
   pollutant_site = "site.name",
   pollutant_date = "date",
   pollutant_name = c("PM10","PM2.5"),
   estimate_interval = c(0:10))

Spatial-R/EnvExpInd documentation built on Oct. 24, 2020, 1:44 a.m.