diff --git a/R/utils_survey_dhs.R b/R/utils_survey_dhs.R
index c3375b3..ccab94a 100644
--- a/R/utils_survey_dhs.R
+++ b/R/utils_survey_dhs.R
@@ -529,7 +529,7 @@ extract_individual_hiv_dhs <- function(SurveyId, ird_path, mrd_path, ard_path){
                      dob_cmc = v011,
                      indweight = NA,
                      artself)
-  
+
   ## Male recode
   if (!is.null(mrd_path)) {
 
@@ -554,17 +554,17 @@ extract_individual_hiv_dhs <- function(SurveyId, ird_path, mrd_path, ard_path){
                                 indweight = NA,
                                 artself)
              )
-    
+
   }
-  
+
   if (!is.null(ard_path)) {
-    
+
     ar <- readRDS(ard_path)
-    
+
     if (SurveyId == "CI2005AIS") {
       ar$hivnumb <- 100L*ar$hivstruct + ar$hivnumb
     }
-    
+
     if (SurveyId == "ZM2013DHS") {
       ar$hiv03 <- ar$shiv51
     }
@@ -635,7 +635,9 @@ create_survey_meta_dhs <- function(surveys) {
   ## Unsure if filtering on PublicationTitle == "Final Report" is most robust
   ## way to do this.
   final_rep <- dplyr::filter(publications, PublicationTitle == "Final Report")
-  final_rep <- dplyr::select(final_rep, SurveyId, report_url = PublicationURL)
+  final_rep <- dplyr::select(final_rep, SurveyId, report_url = PublicationURL) %>%
+    dplyr::group_by(SurveyId) %>%
+    dplyr::filter(row_number() == 1)
 
   stopifnot( !duplicated(final_rep$SurveyId) )
 
@@ -778,13 +780,13 @@ plot_survey_coordinate_check <- function(survey_clusters,
   survey_region_areas <- dplyr::semi_join(survey_region_areas,
                                           survey_region_boundaries,
                                           by = c("survey_id", "survey_region_id"))
-  
+
   clust_spl <- split(survey_clusters, survey_clusters$survey_id)
   region_spl <- split(survey_region_boundaries, survey_region_boundaries$survey_id)
   area_spl <- split(survey_region_areas, survey_region_areas$survey_id)
-  
+
   plot_one <- function(clust, regions, areas) {
-    
+
     subtitle <- sprintf("Total survey clusters: %d\nClusters missing coordinates: %d\nClusters outside region boundaries: %d",
                         nrow(clust),
                         sum(is.na(clust$geoloc_area_id)),
@@ -792,7 +794,7 @@ plot_survey_coordinate_check <- function(survey_clusters,
 
     regions <- dplyr::arrange(regions, survey_id, survey_region_id)
     regions$survey_region_name <- forcats::as_factor(regions$survey_region_name)
-    
+
     clust <- dplyr::left_join(
                       clust,
                       sf::st_drop_geometry(regions),