sleacr (version 0.1.3)

estimate_coverage_overall: Weighted post-stratification estimation of coverage over several service delivery units

Description

Weighted post-stratification estimation of coverage over several service delivery units

Usage

estimate_coverage_overall(cov_df, pop_df, strata, u5, p, k = 3)
estimate_coverage(cov_df, cov_type = c("cf", "tc"), k = 3)

Value

A list of overall coverage estimates with corresponding 95% confidence intervals for case-finding effectiveness and treatment coverage.

Arguments

cov_df

A data.frame() of stratified coverage survey data to get overall coverage estimates of. cov_df should have a variable named cases_in for number of SAM or MAM cases in the programme found during the survey, cases_out for number SAM or MAM cases not in the programme found during the survey, and rec_in for children recovering from SAM or MAM who are in the programme found during the survey. A final required variable should be one that contains identifying geographical information corresponding to the location from which each row of the survey data was collected from.

pop_df

A data.frame() with at least two variables: strata for the stratification/grouping information that matches the grouping information in cov_df and pop for information on population for the given grouping information.

strata

A character value of the variable name in cov_df that corresponds to the strata values to match with values in pop_df.

u5

A numeric value for the proportion of the population that is under years old.

p

Prevalence of SAM or MAM in the given population.

k

Correction factor. Ratio of the mean length of an untreated episode to the mean length of a CMAM treatment episode

cov_type

Coverage estimator to report. Either "cf" for case-finding effectiveness or "tc" for treatment coverage. Default is "cf".

Examples

cov_df <- survey_data

pop_df <- pop_data |>
  setNames(nm = c("strata", "pop"))

estimate_coverage_overall(
  cov_df, pop_df, strata = "district", u5 = 0.177, p = 0.01
)