Applies polbrdn to every row of a table with one row
per area (forward sortation area, census tract, neighbourhood, ...) and
returns the rows sorted by attributable cases, worst first. Use it to
see where in a city or region the pollution burden falls, for example
to rank neighbourhoods for an intervention.
Usage
polbrdarea(
areatab,
areacol = "fsa",
expcol = "exposure",
popcol = "population",
basratecol = "brate",
poll = "NO2",
y = "allcause",
rare = FALSE,
hirate = FALSE
)Arguments
- areatab
A data frame with one row per area: a label, the exposure in micrograms per cubic metre, the population in persons and the baseline rate per person-year (0.008 is 800 per 100,000).
- areacol, expcol, popcol, basratecol
Column names (single strings) of the label, exposure, population and rate; defaults
"fsa","exposure","population"and"brate".- poll, y, rare, hirate
Passed to
polbrdnfor every area: the pollutant (default"NO2"), the outcome (default all-cause mortality), and the switches that admit a rate below 1e-5 or above 0.1 per person-year.
Value
A data frame with one row per area, sorted by
attrcases, largest first, and row names reset: the four
input columns (exposure, population and rate as numbers) plus
rr (relative risk), paf (attributable fraction),
attrcases and basecases (per year).
Details
Each area is treated as wholly exposed at its own concentration
(expoprev = 1), with the pollutant's default reference
concentration. Every area is checked as polbrdn
checks a single population, and the first area that fails stops the
call with that area's error. Refusals: a column name that is not a single
string or not in the table, an empty table, and a non-numeric exposure,
population or rate column. The area labels can be of any type.
See also
expconcidx for how the burden
is spread across income.
Examples
t <- data.frame(fsa = c("M6H", "M5V"), exposure = c(28, 18),
population = c(40000, 60000), brate = 0.008)
polbrdarea(t)
#> ╭── Pollution burden by area ─────────────────────────────────────────────╮
#> │ Areas 2 │
#> │ Attributable cases 18.75 │
#> │ Baseline cases 800 │
#> │ Share attributable 2.34% │
#> │ │
#> │ fsa exposure population brate rr paf attrcases │
#> │ --- -------- ---------- -------- ----- ------- --------- │
#> │ M6H 28 40,000 0.008000 1.036 0.03502 11.205 │
#> │ M5V 18 60,000 0.008000 1.016 0.01572 7.544 │
#> │ │
#> │ fsa basecases │
#> │ --- --------- │
#> │ M6H 320 │
#> │ M5V 480 │
#> │ │
#> │ The areas are sorted by the cases attributable to the exposure, │
#> │ largest first: rr is the relative risk at the area's exposure and paf │
#> │ the share of its cases the exposure accounts for. │
#> ╰─────────────────────────────────────────────────────────────────────────╯
# PM2.5 and different column names.
u <- data.frame(tract = c("A", "B", "C"), pm = c(7, 11, 9),
pop = c(5000, 8000, 6500), rate = 0.0075)
polbrdarea(u, areacol = "tract", expcol = "pm",
popcol = "pop", basratecol = "rate",
poll = "PM2.5")
#> ╭── Pollution burden by area ─────────────────────────────────────────────╮
#> │ Areas 3 │
#> │ Attributable cases 3.884 │
#> │ Baseline cases 146.2 │
#> │ Share attributable 2.66% │
#> │ │
#> │ tract pm pop rate rr paf attrcases basecases │
#> │ ----- -- ----- -------- ----- ------- --------- --------- │
#> │ B 11 8,000 0.007500 1.041 0.03923 2.354 60.00 │
#> │ C 9 6,500 0.007500 1.025 0.02433 1.186 48.75 │
#> │ A 7 5,000 0.007500 1.009 0.00919 0.345 37.50 │
#> │ │
#> │ The areas are sorted by the cases attributable to the exposure, │
#> │ largest first: rr is the relative risk at the area's exposure and paf │
#> │ the share of its cases the exposure accounts for. │
#> ╰─────────────────────────────────────────────────────────────────────────╯
# A missing column is named in the error.
try(polbrdarea(t[, c("fsa", "exposure")]))
#> Error : areatab missing columns: population, brate