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Copy pathS6 Africa Admin 1 Unit Plotting (Fig 3A).R
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S6 Africa Admin 1 Unit Plotting (Fig 3A).R
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# Access and load various required packages for the analyses
library(rjags); library(ssa); library(binom); library(raster); library(sf); library(maptools); library(countrycode);
library(dplyr)
# Loading In the Dataset
data_frame <- read.csv("Data/SI_Systematic_Review_Results_R_Import.csv")
data_frame <- data_frame[data_frame$Full_Or_Age_Disagg_Data == 2 & !is.na(data_frame$Transmission_Setting_15), ]
plotting_df <- data_frame[, c("Country", "Admin_1", "Transmission_Setting_15")]
countries <- unique(as.character(data_frame$Country))
admin_ones <- as.character(data_frame$Admin_1)
unique_admin_ones <- unique(as.character(data_frame$Admin_1))
indices <- seq(1:21)
countries[indices]
indices <- indices[-c(4, 5)] # removing Kenya and Malawi as I'll have to process those manually
countries[indices]
par(mfrow = c(1, 1))
polygons_list <- list()
transmission_archetype <- c()
country <- c()
counter <- 1
for (i in indices) {
country_specific_admin_ones <- getData('GADM', country = countries[i], level = 1)
country_specific_dataset <- data_frame[data_frame$Country == countries[i], ]
survey_present_admin_ones <- unique(as.character(country_specific_dataset$Admin_1))
for (j in 1:length(survey_present_admin_ones)) {
index <- grep(paste0("^", survey_present_admin_ones[j], "$"), country_specific_admin_ones$NAME_1)
if (i == 1 & j == 1) {
admin_one_spatial_polygons_dataframe <- country_specific_admin_ones[index, ]
admin_unit_specific_dataset <- country_specific_dataset[country_specific_dataset$Admin_1 == survey_present_admin_ones[j], ]
transmission_archetype[counter] <- as.character(admin_unit_specific_dataset$Transmission_Setting_15[1])
country[counter] <- countries[i]
print(counter)
counter <- counter + 1
}
else {
admin_one_spatial_polygons_dataframe <- rbind(admin_one_spatial_polygons_dataframe, country_specific_admin_ones[index, ])
admin_unit_specific_dataset <- country_specific_dataset[country_specific_dataset$Admin_1 == survey_present_admin_ones[j], ]
transmission_archetype[counter] <- as.character(admin_unit_specific_dataset$Transmission_Setting_15[1])
country[counter] <- countries[i]
counter <- counter + 1
}
}
print(c(i, countries[i]))
}
plot(admin_one_spatial_polygons_dataframe[28, ])
transmission_archetype
country
BF <- which(country == "Burkina Faso")
transmission_archetype[BF]
which(country == "Burkina Faso")
which(admin_one_spatial_polygons_dataframe$GID_0 == "BFA")
unique(country)
unique(admin_one_spatial_polygons_dataframe$GID_0)
# sorting Kenya
Kenya_admin_units <- c("Mombasa", "Kwale", "Kilifi", "Tana River", "Lamu", "Taita Taveta", "Siaya", "Kisumu",
"Migori", "Homa Bay", "Kisii", "Nyamira", "Kakamega", "Vihiga", "Bungoma", "Busia",
"Turkana", "West Pokot", "Samburu", "Trans Nzoia", "Uasin Gishu", "Elgeyo-Marakwet",
"Nandi", "Baringo", "Laikipia", "Nakuru", "Narok", "Kajiado", "Kericho", "Bomet")
Kenya_admin_shapefiles <- getData('GADM', country = "Kenya", level = 1)
for (i in 1:length(Kenya_admin_units)){
country_specific_dataset <- data_frame[data_frame$Country == "Kenya", ]
index <- grep(paste0("^", Kenya_admin_units[i], "$"), Kenya_admin_shapefiles$NAME_1)
admin_one_spatial_polygons_dataframe <- rbind(admin_one_spatial_polygons_dataframe, Kenya_admin_shapefiles[index, ])
if (i <= 6) {
admin_unit_specific_dataset <- country_specific_dataset[country_specific_dataset$Admin_1 == "Coast", ]
transmission_archetype[counter] <- as.character(admin_unit_specific_dataset$Transmission_Setting_15[1])
country[counter] <- "Kenya"
counter <- counter + 1
}
else if (i > 6 & i <= 12) {
admin_unit_specific_dataset <- country_specific_dataset[country_specific_dataset$Admin_1 == "Nyanza", ]
transmission_archetype[counter] <- as.character(admin_unit_specific_dataset$Transmission_Setting_15[1])
country[counter] <- "Kenya"
counter <- counter + 1
}
else if (i > 12 & i <= 16) {
admin_unit_specific_dataset <- country_specific_dataset[country_specific_dataset$Admin_1 == "Western", ]
transmission_archetype[counter] <- as.character(admin_unit_specific_dataset$Transmission_Setting_15[1])
country[counter] <- "Kenya"
counter <- counter + 1
}
else if (i > 16) {
admin_unit_specific_dataset <- country_specific_dataset[country_specific_dataset$Admin_1 == "Rift Valley", ]
transmission_archetype[counter] <- as.character(admin_unit_specific_dataset$Transmission_Setting_15[1])
country[counter] <- "Kenya"
counter <- counter + 1
}
}
admin_one_spatial_polygons_dataframe
# sorting Malawi
Malawi_admin_units <- c("Dedza", "Dowa", "Kasungu", "Lilongwe", "Mchinji", "Nkhotakota", "Ntcheu", "Ntchisi", "Salima",
"Balaka", "Blantyre", "Chikwawa", "Chiradzulu", "Machinga", "Mangochi", "Mulanje", "Mwanza", "Nsanje", "Thyolo", "Phalombe", "Zomba", "Neno")
Malawi_admin_shapefiles <- getData('GADM', country = "Malawi", level = 1)
for (i in 1:length(Malawi_admin_units)){
country_specific_dataset <- data_frame[data_frame$Country == "Malawi", ]
index <- grep(paste0("^", Malawi_admin_units[i], "$"), Malawi_admin_shapefiles$NAME_1)
admin_one_spatial_polygons_dataframe <- rbind(admin_one_spatial_polygons_dataframe, Malawi_admin_shapefiles[index, ])
if (i <= 9) {
admin_unit_specific_dataset <- country_specific_dataset[country_specific_dataset$Admin_1 == "Central Region", ]
transmission_archetype[counter] <- as.character(admin_unit_specific_dataset$Transmission_Setting_15[1])
country[counter] <- "Malawi"
counter <- counter + 1
}
else if (i > 10) {
admin_unit_specific_dataset <- country_specific_dataset[country_specific_dataset$Admin_1 == "Southern Region", ]
transmission_archetype[counter] <- as.character(admin_unit_specific_dataset$Transmission_Setting_15[1])
country[counter] <- "Malawi"
counter <- counter + 1
}
}
admin_one_spatial_polygons_dataframe$NAME_1
transmission_archetype
country
BF <- which(country == "Burkina Faso")
transmission_archetype[BF]
list1 <- countrycode::codelist_panel %>%
filter(continent == "Africa")
country_codes <- unique(list1[, "wb"])
country_codes <- c(country_codes[-44], "EH")
for (i in 1:length(country_codes)) {
if (i == 1) {
country_shapefile <- getData('GADM', country = country_codes[i], level = 0)
}
else {
new_country_shapefile <- getData('GADM', country = country_codes[i], level = 0)
country_shapefile <- rbind(country_shapefile, new_country_shapefile)
}
print(i)
}
pdf("Figures/Figure 3 - Transmission Archetype/Figure_3A_Admin_1_Mapping.pdf", width = 12.5, height = 12.5)
palette(c("#00A600FF", "#ECB176FF", "darkgrey"))
plot(country_shapefile)
trans_arch <- as.factor(transmission_archetype)
for (i in 1:length(admin_one_spatial_polygons_dataframe)) {
plot(admin_one_spatial_polygons_dataframe[i, ], lwd = 2, add = TRUE, col = trans_arch[i])
}
dev.off()