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PM25-HIA-methodology
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library(units) | |
install_symbolic_unit("person") | |
install_conversion_constant("person", "death", const = -1) | |
options(digits = 8) | |
# For convenience, let's assume a population of 1 million people. | |
pop <- as_units(1e6, "person") | |
# Let's assume that the baseline annual all-cause mortality rate is | |
# about 1%, i.e., about 10,000 per million (per year). | |
(y_all_0 <- as_units(10e3, "death/(Mperson*yr)")) | |
# Let's assume that 1% of that is cause-specific (i.e., due to X). | |
(y_PM25_0 <- set_units(0.01 * y_all_0, "death/(Mperson*yr)")) | |
# Let's assume this is the cause-specific risk ratio, i.e., | |
# the multiplicative change in risk per +10 ug/m3. | |
β <- 1.03 | |
# Since our unit change in X is +10 ug/m3, this corresponds | |
# to an increase of +1 ug/m3, i.e., 0.1 * +10 ug/m3. | |
Δx <- 0.1 | |
# As in Fang (2013) ... here is our first result. | |
show(y_all_0 * (1 - exp(-β * Δx)) * pop) | |
# As in Fann (2011) ... here is our second result. It should be the same as the first. | |
show(y_PM25_0 * (exp(β * Δx) - 1) * pop) |
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