#' This generates a csv template for vaccination campaigns in order to calculate population level vaccination coverage
#' @examples
#' gen_csv_template()
#' @export
#'
gen_csv_template<-function(){
df<-data.frame("vac.id"="Unique ID for campaign",
"country"="Country campaign took place in",
"country.code"="3 letter ISO code for country",
"year"="Year campaign took place in",
"month"="Month campaign took place in",
"location.id"="GADM1 encoding for location, adm1 and adm2 units are seperated by a colon (:), and adm1 units by a semi-colon (;). This means that 361:10207;625 is read as adm2 unit 10207 in 361 and all of adm1 unit 625",
"adm1"="adm1 unit in GADM2 or GADM2.8 encoding",
"adm2"="adm2 unit in GADM2 or GADM2.8 encoding",
"location.encoding"="Type of location encoding used, accepteds GADM1,GADM2 and GADM2.8",
"target.population"="Population targeted for vaccination",
"doses"="Number of doses used in vaccination",
"coverage.planned"="Planned coverage, 1 = 100%",
"coverage.adm"="Administrative coverage achieved, 1 = 100%",
"coverage.survey"="Coverage calculated through survey, 1 = 100%",
"agemin"="Minimum age targeted for vaccination",
"agemax"="Maximum age targeted for vaccination",
"campaign.type"="Type of campaign, response, preventive",
"scenario"="This changes underlying assumptions of population size. Base does nothing, hiCov reduces population by 25 percent, loCov increases population by 25 percent.",
"skew"="This affects how vaccination campaigns are applied. If skew is set to -1 then campaigns are applied to whole population, regardless of prior vaccination status. If skew is set to 0 then campaigns are applied only to unvaccinated population.",
"source"="This is a reference so you know where data came from",
"remarks"="User remarks")
write.csv(df,"vaccination_campaign_template.csv",row.names = FALSE)
}
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