diff --git a/NAMESPACE b/NAMESPACE
index 50b9fd3..ca7e4fa 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -7,7 +7,7 @@ export(check_data)
 export(check_land_water)
 export(check_leap_issue)
 export(check_missing)
-export(compare_polis_afp_snapshots)
+export(compare_polis_snapshots)
 export(correct_flipped_geo_coords)
 export(create_gt_table)
 export(create_summary_by_group)
diff --git a/R/prep_detections.R b/R/prep_detections.R
index b3ff6de..0102395 100644
--- a/R/prep_detections.R
+++ b/R/prep_detections.R
@@ -130,10 +130,14 @@ prep_new_detections_table <- function(polis_df_old,
     prev_detection <- polis_df_old |>
         dplyr::mutate(across(where(is.factor), as.character)) |>
         dplyr::mutate(
-            VirusTypeName = ifelse(VirusTypeName == "WILD1", "WPV1", VirusTypeName)
+            VirusTypeName = ifelse(
+                VirusTypeName == "WILD1", "WPV1", VirusTypeName
+            )
+        ) |>
+        dplyr::filter(
+            stringr::str_detect(VirusTypeName, "^WPV|^VDPV|^cVDPV") &
+                SurveillanceTypeName %in% c("AFP", "Environmental")
         ) |>
-        dplyr::filter(stringr::str_detect(VirusTypeName, "^WPV|^VDPV|^cVDPV")) |>
-        dplyr::filter(SurveillanceTypeName %in% c("AFP", "Environmental")) |>
         dplyr::mutate(VirusDate = as.Date(VirusDate)) |>
         dplyr::group_by(Admin0Name, VirusTypeName) |>
         dplyr::reframe(`Previous Detection` = max(VirusDate))
diff --git a/R/validate_data.R b/R/validate_data.R
index 2c7e4ad..2b4180a 100644
--- a/R/validate_data.R
+++ b/R/validate_data.R
@@ -2334,11 +2334,17 @@ get_polis_detections <- function(data, case_type = c("ES", "AFP")) {
       !is.na(if (case_type == "ES") CollectionDate else ParalysisOnsetDate)
     ) |>
     dplyr::mutate(
-      cVDPV1 = "VDPV1" %in% names(data) & VDPV1 &
-        VdpvClassifications == "Circulating",
-      cVDPV2 = "VDPV2" %in% names(data) & VDPV2 &
-        VdpvClassifications == "Circulating",
-      WPV1 = "WILD1" %in% names(data) & WILD1
+      cVDPV1 = if ("VDPV1" %in% names(data)) {
+        VDPV1 & VdpvClassifications == "Circulating"
+      } else {
+        FALSE
+      },
+      cVDPV2 = if ("VDPV2" %in% names(data)) {
+        VDPV2 & VdpvClassifications == "Circulating"
+      } else {
+        FALSE
+      },
+      WPV1 = if ("WILD1" %in% names(data)) WILD1 else FALSE
     ) |>
     dplyr::mutate(
       virus_type = dplyr::case_when(
@@ -2350,24 +2356,26 @@ get_polis_detections <- function(data, case_type = c("ES", "AFP")) {
     )
 }
 
-#' Compare AFP POLIS Snapshots
+#' Compare POLIS Snapshots
 #'
-#' This function performs a detailed comparison between two POLIS datasets,
-#' focusing on Acute Flaccid Paralysis (AFP) cases. It conducts various
-#' validations and analyses to identify differences and changes.
+#' This function performs a detailed comparison between two POLIS snapshots,
+#' focusing on either Acute Flaccid Paralysis (AFP) cases or Environmental
+#' Surveillance (ES) samples. It conducts various validations and analyses
+#' to identify differences and changes between the two snapshots.
 #'
 #' Key operations include:
 #' 1. Checking for removed columns
 #' 2. Identifying new blank columns
-#' 3. Detecting removed EPIDs
+#' 3. Detecting removed EPIDs/SampleIds
 #' 4. Finding lost detections
-#' 5. Analyzing changes in AFP detections, comparing various fields
+#' 5. Analyzing changes in detections, comparing various fields
 #'
 #' The function outputs informative CLI messages throughout the process,
 #' providing insights into the differences between the datasets.
 #'
 #' @param data1 First POLIS dataset (data frame)
 #' @param data2 Second POLIS dataset (data frame)
+#' @param type Type of data to compare: "AFP" or "ES"
 #'
 #' @return A list containing:
 #'   - results: Detailed validation results
@@ -2378,19 +2386,31 @@ get_polis_detections <- function(data, case_type = c("ES", "AFP")) {
 #'
 #' @examples
 #' \dontrun{
-#' results <- compare_polis_afp_snapshots(old_data, new_data)
-#' print(results$gt_tab)
+#' results_afp <- compare_polis_snapshots(old_data_afp, new_data_afp, "AFP")
+#' results_es <- compare_polis_snapshots(old_data_es, new_data_es, "ES")
+#' print(results_afp$gt_tab)
+#' print(results_es$gt_tab)
 #' }
-compare_polis_afp_snapshots <- function(data1, data2) {
+compare_polis_snapshots <- function(data1, data2, type) {
+  if (!type %in% c("AFP", "ES")) {
+    stop("Type must be either 'AFP' or 'ES'")
+  }
+
   # Get detections table
-  detections1 <- get_polis_detections(data1, "AFP") |>
+  detections1 <- get_polis_detections(data1, type) |>
     dplyr::filter(cVDPV1 | cVDPV2 | WPV1)
-  detections2 <- get_polis_detections(data2, "AFP") |>
+  detections2 <- get_polis_detections(data2, type) |>
     dplyr::filter(cVDPV1 | cVDPV2 | WPV1)
 
+  data1 <- data1 |>
+    dplyr::mutate(across(where(is.factor), as.character))
+
+  data2 <- data2 |>
+    dplyr::mutate(across(where(is.factor), as.character))
+
   # Establish labels for the different datasets
-  lab_date1 <- format(as.Date(max(data1$LastUpdateDate)), "%d %b %Y")
-  lab_date2 <- format(as.Date(max(data2$LastUpdateDate)), "%d %b %Y")
+  lab_date1 <- format(as.Date(max(data1$LastUpdateDate, na.rm = T)), "%d %b %Y")
+  lab_date2 <- format(as.Date(max(data2$LastUpdateDate, na.rm = T)), "%d %b %Y")
 
   # Create labels for CLI messages and table headers
   cli_label1 <- paste0("Dataset 1 (", lab_date1, ")")
@@ -2450,45 +2470,48 @@ compare_polis_afp_snapshots <- function(data1, data2) {
   results$blank_columns_new <- new_blank_cols
   results$blank_columns_new_count <- length(new_blank_cols)
 
-  # 3. Check for removed EPIDs -----------------------------------------------
-  cli::cli_h1("Checking for removed EPIDs")
+  # 3. Check for removed EPIDs/SampleIds ---------------------------------------
+  cli::cli_h1(
+    paste0("Checking for removed ", ifelse(type == "AFP", "EPIDs", "SampleIds"))
+  )
 
-  removed_epids <- setdiff(data1$EPID, data2$EPID)
+  id_col <- ifelse(type == "AFP", "EPID", "SampleId")
+  removed_ids <- setdiff(data1[[id_col]], data2[[id_col]])
 
   # Get the number of detections in the first dataset
   number_detections <- detections1 |>
-    dplyr::filter(EPID %in% removed_epids) |>
+    dplyr::filter(!!rlang::sym(id_col) %in% removed_ids) |>
     nrow()
 
-  if (length(removed_epids) > 0) {
+  if (length(removed_ids) > 0) {
     cli::cli_alert_warning(paste0(
-      "Number of EPIDs from {cli_label1} removed in {cli_label2}: ",
-      crayon::red(big_mark(length(removed_epids))), "\n",
+      "Number of ", id_col, "s from {cli_label1} removed in {cli_label2}: ",
+      crayon::red(big_mark(length(removed_ids))), "\n",
       "Number of these that were detections in {cli_label1}: ",
       crayon::red(big_mark(number_detections))
     ))
   } else {
     cli::cli_alert_success(
-      "All EPIDs from {cli_label1} are present in {cli_label2}"
+      "All ", id_col, "s from {cli_label1} are present in {cli_label2}"
     )
   }
-  results$removed_epids <- removed_epids
-  results$removed_epids_count <- length(removed_epids)
+  results$removed_ids <- removed_ids
+  results$removed_ids_count <- length(removed_ids)
 
   # 4. Check for removed detections in dataset --------------------------------
 
-  cli::cli_h1("Checking for lost AFP detections")
+  cli::cli_h1(paste0("Checking for lost ", type, " detections"))
 
   data1_counts <- detections1 |>
-    dplyr::group_by(EPID) |>
+    dplyr::group_by(!!rlang::sym(id_col)) |>
     dplyr::summarise(n = dplyr::n_distinct(virus_type))
 
   data2_counts <- detections2 |>
-    dplyr::group_by(EPID) |>
+    dplyr::group_by(!!rlang::sym(id_col)) |>
     dplyr::summarise(n = dplyr::n_distinct(virus_type))
 
   lost_detections <- dplyr::full_join(data1_counts, data2_counts,
-    by = "EPID",
+    by = id_col,
     suffix = c("_data1", "_data2")
   ) |>
     dplyr::filter(!is.na(n_data1), !is.na(n_data2), n_data2 < n_data1) |>
@@ -2496,7 +2519,7 @@ compare_polis_afp_snapshots <- function(data1, data2) {
 
   if (nrow(lost_detections) > 0) {
     cli::cli_alert_warning(paste0(
-      "Number of EPIDs with lost detections between ",
+      "Number of ", id_col, "s with lost detections between ",
       "{cli_label1} and {cli_label2}: ",
       crayon::red(big_mark(nrow(lost_detections)))
     ))
@@ -2504,56 +2527,52 @@ compare_polis_afp_snapshots <- function(data1, data2) {
     cli::cli_alert_success("No detections were lost between datasets")
   }
 
-  results$lost_detections <- unique(lost_detections$EPID)
+  results$lost_detections <- unique(lost_detections[[id_col]])
   results$lost_detections_count <- nrow(lost_detections)
 
   # 5. Check for changes in detections dataset ---------------------------------
-  cli::cli_h1("Checking for changes in AFP detections dataset")
+  cli::cli_h1(paste0("Checking for changes in ", type, " detections dataset"))
+
+  # Define columns to compare based on type
+  columns_to_compare <- if (type == "AFP") {
+    c(
+      "CountryISO3Code", "Admin0Name", "Admin0GUID", "Admin1GUID",
+      "Admin2GUID", "Admin1Name", "Admin2Name", "Latitude", "Longitude",
+      "PersonSex", "PersonAgeInMonths", "PersonAgeInYears", "DosesIPVNumber",
+      "DosesTotal", "DosesIPVRoutine", "TotalNumberOfDoses",
+      "ParalysisOnsetDate", "VdpvClassifications", "Stool1Condition",
+      "Stool2Condition", "NotificationDate", "InvestigationDate",
+      "Stool1CollectionDate", "Stool2CollectionDate",
+      "DateNotificationtoHQ", "SurveillanceTypeName",
+      "PolioVirusTypes", "VdpvEmergenceGroupNames", "FinalCultureResult",
+      "NtChanges"
+    )
+  } else {
+    c(
+      "CountryISO3Code", "Admin0Name", "Admin0GUID", "Admin1GUID",
+      "Admin2GUID", "Admin1Name", "Admin2Name", "SiteXCoordinate",
+      "SiteYCoordinate", "SiteName", "CollectionDate",
+      "DateFinalSeqResult", "DateFinalResultsReported", "DateReceivedInLab",
+      "SampleCondition", "FinalCellCultureResult", "VaccineOrigins",
+      "NtChanges", "DateShippedToRefLab", "VirusTypes", "VirusClusters"
+    )
+  }
 
   # Compare with corresponding rows in data2 and identify changes
   changed_rows <- detections1 |>
-    dplyr::left_join(data2, by = "EPID") |>
+    dplyr::left_join(data2,
+      by = id_col,
+      relationship = "many-to-many"
+    ) |>
     dplyr::mutate(
       changes = dplyr::case_when(
-        CountryISO3Code.x != CountryISO3Code.y ~ "CountryISO3Code",
-        Admin0Name.x != Admin0Name.y ~ "Admin0Name",
-        Admin0GUID.x != Admin0GUID.y ~ "Admin0GUID",
-        Admin1GUID.x != Admin1GUID.y ~ "Admin1GUID",
-        Admin2GUID.x != Admin2GUID.y ~ "Admin2GUID",
-        Admin1Name.x != Admin1Name.y ~ "Admin1Name",
-        Admin2Name.x != Admin2Name.y ~ "Admin2Name",
-        Latitude.x != Latitude.y ~ "Latitude",
-        Longitude.x != Longitude.y ~ "Longitude",
-        PersonSex.x != PersonSex.y ~ "PersonSex",
-        PersonAgeInMonths.x != PersonAgeInMonths.y ~ "PersonAgeInMonths",
-        PersonAgeInYears.x != PersonAgeInYears.y ~ "PersonAgeInYears",
-        DosesIPVNumber.x != DosesIPVNumber.y ~ "DosesIPVNumber",
-        DosesTotal.x != DosesTotal.y ~ "DosesTotal",
-        DosesIPVRoutine.x != DosesIPVRoutine.y ~ "DosesIPVRoutine",
-        TotalNumberOfDoses.x != TotalNumberOfDoses.y ~ "TotalNumberOfDoses",
-        ParalysisOnsetDate.x != ParalysisOnsetDate.y ~ "ParalysisOnsetDate",
-        VdpvClassifications.x != VdpvClassifications.y ~ "VdpvClassifications",
-        TotalNumberOfDoses.x != TotalNumberOfDoses.y ~ "TotalNumberOfDoses",
-        Stool1Condition.x != Stool1Condition.y ~ "Stool1Condition",
-        Stool2Condition.x != Stool2Condition.y ~ "Stool2Condition",
-        NotificationDate.x != NotificationDate.y ~ "NotificationDate",
-        InvestigationDate.x != InvestigationDate.y ~ "InvestigationDate",
-        Stool1CollectionDate.x != Stool1CollectionDate.y ~
-          "Stool1CollectionDate",
-        Stool2CollectionDate.x != Stool2CollectionDate.y ~
-          "Stool2CollectionDate",
-        DateNotificationtoHQ.x != DateNotificationtoHQ.y ~
-          "DateNotificationtoHQ",
-        VdpvClassifications.x != VdpvClassifications.y ~
-          "VdpvClassifications",
-        SurveillanceTypeName.x != SurveillanceTypeName.y ~
-          "SurveillanceTypeName",
-        PolioVirusTypes.x != PolioVirusTypes.y ~ "PolioVirusTypes",
-        VdpvEmergenceGroupNames.x != VdpvEmergenceGroupNames.y ~
-          "VdpvEmergenceGroupNames",
-        # Classification.x != Classification.y ~ "Classification",
-        FinalCultureResult.x != FinalCultureResult.y ~ "FinalCultureResult",
-        NtChanges.x != NtChanges.y ~ "NtChanges",
+        !!!lapply(columns_to_compare, function(col) {
+          rlang::expr(
+            !!rlang::sym(
+              paste0(col, ".x")
+            ) != !!rlang::sym(paste0(col, ".y")) ~ !!col
+          )
+        }),
         TRUE ~ NA_character_
       )
     ) |>
@@ -2567,7 +2586,7 @@ compare_polis_afp_snapshots <- function(data1, data2) {
   # Total number of changed rows
   total_changed <- nrow(changed_rows)
   cli::cli_alert_info(paste0(
-    "Number of changed rows in AFP detections dataset from ",
+    "Number of changed rows in ", type, " detections dataset from ",
     "{cli_label1} to {cli_label2}: ",
     crayon::red(big_mark(total_changed))
   ))
@@ -2593,19 +2612,19 @@ compare_polis_afp_snapshots <- function(data1, data2) {
     val_type = c(
       "Removed Columns",
       "New Blank Columns",
-      "Removed EPIDs",
+      paste0("Removed ", id_col, "s"),
       "Lost Detections"
     ),
     Validation = c(
       glue::glue("Removed Columns in {table_header2}"),
       glue::glue("New Blank Columns in {table_header2}"),
-      glue::glue("Removed EPIDs in {table_header2}"),
+      glue::glue("Removed {id_col}s in {table_header2}"),
       glue::glue("Lost Detections in {table_header2}")
     ),
     Difference = c(
       results$removed_columns_count,
       results$blank_columns_new_count,
-      results$removed_epids_count,
+      results$removed_ids_count,
       results$lost_detections_count
     )
   ) |>
@@ -2615,7 +2634,7 @@ compare_polis_afp_snapshots <- function(data1, data2) {
         dplyr::mutate(
           `Validation Type` = "Changes in Detections Dataset",
           changes = glue::glue(
-            "Changes in {changes} in AFP Detections in {table_header2}"
+            "Changes in {changes} in {type} Detections in {table_header2}"
           )
         ) |> dplyr::select(
           `Validation Type`,
@@ -2627,7 +2646,6 @@ compare_polis_afp_snapshots <- function(data1, data2) {
     gt::gt() |>
     gt::data_color(
       columns = 3,
-      # rows = row_start:nrow(summary_df),
       fn = function(x) {
         # Handle potential negative values or NAs for this row
         x_clean <- pmax(x, 0, na.rm = TRUE)
@@ -2644,7 +2662,7 @@ compare_polis_afp_snapshots <- function(data1, data2) {
       }
     ) |>
     gt::tab_header(
-      title = "Comparison of POLIS AFP Snapshots",
+      title = paste0("Comparison of POLIS ", type, " Snapshots"),
       subtitle = glue::glue("{table_header1} Vs {table_header2}")
     ) |>
     gt::cols_align(align = "left", columns = 2) |>
diff --git a/README.md b/README.md
index 3cad44a..fea66dd 100644
--- a/README.md
+++ b/README.md
@@ -32,12 +32,10 @@ We plan to add a number of functions which do the following:
 - [x] Clean and fix names of places including geolocations.
 - [x] Check and clean geo-coordinates.
 - [x] Match variables naming conventions & datatypes within two dataframes.
-- [x] Validate POLIS data.
+- [x] Validate AFP & ES POLIS data.
 - [x] Validate AFP Surveillance data.
-- [ ] Validate Environmental Surveillance data.
-- [ ] Validate all Lab data.
-- [ ] Produce validation reports and scorecards.
-
+- [x] Validate A Surveillance data.
+- [x] Create New Detections Table from POLIS data.
 
 ## :incoming_envelope: Contacting us
 
diff --git a/man/compare_polis_afp_snapshots.Rd b/man/compare_polis_afp_snapshots.Rd
deleted file mode 100644
index ac07190..0000000
--- a/man/compare_polis_afp_snapshots.Rd
+++ /dev/null
@@ -1,45 +0,0 @@
-% Generated by roxygen2: do not edit by hand
-% Please edit documentation in R/validate_data.R
-\name{compare_polis_afp_snapshots}
-\alias{compare_polis_afp_snapshots}
-\title{Compare AFP POLIS Snapshots}
-\usage{
-compare_polis_afp_snapshots(data1, data2)
-}
-\arguments{
-\item{data1}{First POLIS dataset (data frame)}
-
-\item{data2}{Second POLIS dataset (data frame)}
-}
-\value{
-A list containing:
-\itemize{
-\item results: Detailed validation results
-\item summary: A summary data frame of key changes
-\item gt_tab: A formatted GT table for easy visualization
-}
-}
-\description{
-This function performs a detailed comparison between two POLIS datasets,
-focusing on Acute Flaccid Paralysis (AFP) cases. It conducts various
-validations and analyses to identify differences and changes.
-}
-\details{
-Key operations include:
-\enumerate{
-\item Checking for removed columns
-\item Identifying new blank columns
-\item Detecting removed EPIDs
-\item Finding lost detections
-\item Analyzing changes in AFP detections, comparing various fields
-}
-
-The function outputs informative CLI messages throughout the process,
-providing insights into the differences between the datasets.
-}
-\examples{
-\dontrun{
-results <- compare_polis_afp_snapshots(old_data, new_data)
-print(results$gt_tab)
-}
-}
diff --git a/man/compare_polis_snapshots.Rd b/man/compare_polis_snapshots.Rd
new file mode 100644
index 0000000..18fb7fb
--- /dev/null
+++ b/man/compare_polis_snapshots.Rd
@@ -0,0 +1,50 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/validate_data.R
+\name{compare_polis_snapshots}
+\alias{compare_polis_snapshots}
+\title{Compare POLIS Snapshots}
+\usage{
+compare_polis_snapshots(data1, data2, type)
+}
+\arguments{
+\item{data1}{First POLIS dataset (data frame)}
+
+\item{data2}{Second POLIS dataset (data frame)}
+
+\item{type}{Type of data to compare: "AFP" or "ES"}
+}
+\value{
+A list containing:
+\itemize{
+\item results: Detailed validation results
+\item summary: A summary data frame of key changes
+\item gt_tab: A formatted GT table for easy visualization
+}
+}
+\description{
+This function performs a detailed comparison between two POLIS snapshots,
+focusing on either Acute Flaccid Paralysis (AFP) cases or Environmental
+Surveillance (ES) samples. It conducts various validations and analyses
+to identify differences and changes between the two snapshots.
+}
+\details{
+Key operations include:
+\enumerate{
+\item Checking for removed columns
+\item Identifying new blank columns
+\item Detecting removed EPIDs/SampleIds
+\item Finding lost detections
+\item Analyzing changes in detections, comparing various fields
+}
+
+The function outputs informative CLI messages throughout the process,
+providing insights into the differences between the datasets.
+}
+\examples{
+\dontrun{
+results_afp <- compare_polis_snapshots(old_data_afp, new_data_afp, "AFP")
+results_es <- compare_polis_snapshots(old_data_es, new_data_es, "ES")
+print(results_afp$gt_tab)
+print(results_es$gt_tab)
+}
+}