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config.R
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config.R
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## Make your selections here (NSW, VIC, ACT, WA, NT, SA, QLD, TAS)
state <- "WA"
# optional setting for a sub-state region
## currently only works for SA3s
specific_stdy_reg <- FALSE
specific_sa3_code <- NA
## AND MAKE SURE TO UPDATE THE STATE TO MATCH THE SA3
timepoints <- 2014:2016
# health_impact_function
rr <- 1.062
rr_lci <- 1.040
rr_uci <- 1.083
# this is a RR per 10 unit change
unit_change <- 10
beta <- log(rr)/unit_change
beta
## what counterfactual method to use? NB only regional minimum implemented here.
## review R/load_enviro_monitor_model_counterfactual_linked.R to change this
do_env_counterfactual <- "min"
# COESRA:
datadir <- "../data_provided"
# OR CLOUD-CARDAT
# datadir <- "cloud-car-dat/Environment_General"
## mb
indir_mb <- file.path(datadir, sprintf("ABS_data/ABS_meshblocks/abs_meshblocks_2016_data_provided/"))
infile_mb <- sprintf("MB_2016_%s.shp", state)
## meshblock pops
indir_mb_pops <- file.path(datadir, "ABS_data/ABS_meshblocks/abs_meshblocks_2016_pops_data_provided")
dir(indir_mb_pops)
infile_mb_pops <- "2016 census mesh block counts.csv"
mb_pops_varlist <- c("MB_CODE16", "MB_CATEGORY_NAME_2016", "Person")
## pops at sa2
indir_pop <- file.path(datadir, "ABS_data/ABS_Census_2016/abs_gcp_2016_data_derived")
infile_pop_sa2 <- "abs_sa2_2016_agecatsV2_total_persons_20180405.csv"
## load health rates standard
indir_death <- file.path(datadir, "Australian_Mortality_ABS/ABS_MORT_2006_2016/data_provided/")
infile_death <- "DEATHS_AGESPECIFIC_OCCURENCEYEAR_04042018231304281.csv"
indat_death_varlist <- c("Region", "Sex", "Age", "Measure", "Time", "Value")
## exposure
indir_expo <- file.path(datadir, "Air_pollution_model_GlobalGWR_PM25/GlobalGWR_PM25_V4GL02/data_derived/")
## SA3
indir_sa3 <- file.path(datadir, "ABS_data/ABS_Census_2016/abs_sa3_2016_data_provided")
infile_sa3 <- "SA3_2016_AUST.shp"