Calculate Health Coverage Indicators
Source:R/2_denominators_calculate_indicator_coverage.R
calculate_indicator_coverage.Rd
calculate_indicator_coverage
computes key health coverage indicators across
specified administrative levels (national, adminlevel_1, and district). The function
integrates data from multiple sources, including DHIS-2, UN estimates, ANC-1,
and Penta-1 survey data. It calculates coverage rates for a variety of vaccinations
and health metrics based on projected, survey-derived, and estimated denominators.
Usage
calculate_indicator_coverage(
.data,
admin_level = c("national", "adminlevel_1", "district"),
un_estimates = NULL,
sbr = 0.02,
nmr = 0.025,
pnmr = 0.024,
anc1survey = 0.98,
dpt1survey = 0.97,
twin = 0.015,
preg_loss = 0.03
)
Arguments
- .data
A
cd_data
tibble containing DHIS-2, UN, ANC-1, and Penta-1 data. This dataset must include columns for key population and vaccination metrics.- admin_level
Character. Specifies the administrative level for calculations. Options include:
"national", "adminlevel_1"
, and"district"
.- un_estimates
Optional. A tibble containing UN population estimates. Required for national-level calculations.
- sbr
Numeric. The stillbirth rate. Default is
0.02
.- nmr
Numeric. Neonatal mortality rate. Default is
0.025
.- pnmr
Numeric. Post-neonatal mortality rate. Default is
0.024
.- anc1survey
Numeric. Survey-derived coverage rate for ANC-1 (antenatal care, first visit). Default is
0.98
.- dpt1survey
Numeric. Survey-derived coverage rate for Penta-1 (DPT1 vaccination). Default is
0.97
.- twin
Numeric. Twin birth rate. Default is
0.015
.- preg_loss
Numeric. Pregnancy loss rate. Default is
0.03
.
Value
A tibble of class cd_indicator_coverage
containing calculated coverage
indicators for the specified administrative level.
Examples
if (FALSE) { # \dontrun{
# Calculate coverage indicators at the national level
coverage_data <- calculate_indicator_coverage(
.data = dhis2_data,
admin_level = "national",
un_estimates = un_data
)
# Calculate coverage indicators at the district level
coverage_data <- calculate_indicator_coverage(
.data = dhis2_data,
admin_level = "district"
)
} # }