Get potential impact fraction (PIF)

This function calculates the potential impact fraction of a health outcome due to exposure to an environmental stressor

Usage

get_pif(rr_at_exp_1, rr_at_exp_2, prop_pop_exp_1, prop_pop_exp_2)

Arguments

rr_at_exp_1: Numerical value showing the risk estimate of the concentration response function for a specific concentration in the scenario 1. The population attributable fraction is normally calculated using the risk estimate that refers to the concentration that reflects the population exposure and the cut-off. This risk estimate is obtained after re-scaling from the epidemiological study with a particular increment (e.g. for PM2.5 10 or 5 ug/m3) to the aimed concentration.
rr_at_exp_2: Numerical value showing the risk estimate of the concentration response function for a specific concentration in the scenario 2. The population attributable fraction is normally calculated using the risk estimate that refers to the concentration that reflects the population exposure and the cut-off. This risk estimate is obtained after re-scaling from the epidemiological study with a particular increment (e.g. for PM2.5 10 or 5 ug/m3) to the aimed concentration.
prop_pop_exp_1: Numerical value showing the fraction ([0,1]) of population exposed to the environmental stressor in the scenario 1. Per default = 1 (i.e. 100% of population is exposed).
prop_pop_exp_2: Numerical value showing the fraction ([0,1]) of population exposed to the environmental stressor in the scenario 1. Per default = 1 (i.e. 100% of population is exposed).

Value

This function returns the potential impact fraction as a numeric value.

Details

Methodology

This function is internally used inside the healthiar function compare(). The potential impact fraction (PIF) is calculated as described in WHO (2003) , Murray et al. (2003) and Askari and Namayandeh (2020) .

Detailed information about the methodology (including equations) is available in the package vignette. More specifically, see chapters:

comparison of two health scenarios

References

Askari M, Namayandeh SM (2020). “The Difference between the Population Attributable Risk (PAR) and the Potentioal Impact Fraction (PIF).” Iranian Journal of Public Health, 49(10), 2018–2019. doi:10.18502/ijph.v49i10.4713 , https://pmc.ncbi.nlm.nih.gov/articles/PMC7719653/.

Murray CJL, Ezzati M, Lopez AD, Rodgers A, Vander Hoorn S (2003). “Comparative quantification of health risks conceptual framework and methodological issues.” Popul. Health Metr., 1(1), 1.

WHO (2003). “Introduction and methods: Assessing the environmental burden of disease at national and local levels.” World Health Organization. https://www.who.int/publications/i/item/9241546204.

Author

Alberto Castro & Axel Luyten

Examples

# Goal: calculate the potential impact fraction (PIF)
results <- get_pif(
  rr_at_exp_1 = 1.043879,
  rr_at_exp_2 = 1.011217,
  prop_pop_exp_1 = 1,
  prop_pop_exp_2 = 1
)
print(results)
#> [1] 0.03128907