knitr::opts_chunk$set(echo = TRUE)
library("rnaturalearth")
library("rnaturalearthdata")
library("RColorBrewer")
library("here")
library("rgdal")
library("sf")
library("tmap")
library("tmaptools")
library("sp")
library("rgdal")
library(tidyverse)
library(magrittr)
library(readxl)
library(readr)
library(readxl)
updated_vac <- read_excel("updated_vac.xls")
df_2 <- updated_vac %>%
filter(district!="1 Test District") %>%
#separate(district, c("district","dst"),sep = " ",remove = T) %>%
separate(period, c("epi_wk","yr"),sep = " ",remove = T) %>%
rowwise() %>%
mutate(booster = as.integer(booster),
first_dose=as.integer(first_dose),
second_dose=as.integer(second_dose),
jj=as.integer(jj),
p_vax=(first_dose),
f_vax=sum(second_dose,jj, na.rm=TRUE),
wk = as.integer(substring(epi_wk,2))) %>%
select(district, wk, yr, p_vax, f_vax, booster) %>%
group_by(district, wk, yr) %>%
summarise(p_vax=sum(p_vax),
f_vax=sum(f_vax),
booster=sum(booster))
df_3 <- df_2 %>%
mutate_at(4, ~replace_na(.,0)) %>%
mutate_at(5, ~replace_na(.,0)) %>%
mutate_at(6, ~replace_na(.,0)) %>%
group_by(district) %>%
summarise(p_vax=sum(p_vax),
f_vax=sum(f_vax),
booster=sum(booster))
ds <- readOGR("C:/Users/User/Desktop/EPIVAC/District", "District")
lk <- readOGR( "C:/Users/User/Desktop/EPIVAC/shape", "lk")
dist_shp <- merge(x=ds,y= df_3, by.x= "name", by.y ="district", all = T)
tm_shape(dist_shp)+
tm_borders()+
tm_fill( col=c("p_vax"),
title=c("counts"),
style="fixed",
breaks=c(0, 90000, 360000, 500000, 1000000,Inf),
palette = "RdYlGn")+
sf::sf_use_s2(FALSE)+
tm_shape(lk) +
tm_fill("lightblue")+
tm_polygons("#a6cee3") +
tm_layout(bg.color="white")+
tm_legend(legend.outside = TRUE)+
tm_layout(bg.color="white",
main.title = "Partial Vaccination (National)",
main.title.position = "left")+
tm_compass(type = 'arrow', position = c(0.05, 0.8))+
tm_scale_bar(position = c("RIGHT", "BOTTOM"))+
tm_scale_bar(position = c("RIGHT", "BOTTOM"))+
tm_credits("Data from 2021 to date",
position = c("LEFT", "TOP"))
tm_shape(dist_shp)+
tm_borders()+
tm_fill( col=c("f_vax"),
title=c("counts"),
style="fixed",
breaks=c(0, 3500, 5000, 15000, 30000,Inf),
palette = "RdYlGn")+
sf::sf_use_s2(FALSE)+
tm_shape(lk) +
tm_fill("lightblue")+
tm_polygons("#a6cee3") +
tm_layout(bg.color="white")+
tm_legend(legend.outside = TRUE)+
tm_layout(bg.color="white",
main.title = "Full Vaccination (National)",
main.title.position = "left")+
tm_compass(type = 'arrow', position = c(0.05, 0.8))+
tm_scale_bar(position = c("RIGHT", "BOTTOM"))+
tm_scale_bar(position = c("RIGHT", "BOTTOM"))+
tm_credits("Data from 2021 to date",
position = c("LEFT", "TOP"))
tm_shape(dist_shp)+
tm_borders()+
tm_fill( col=c("booster"),
title=c("counts"),
style="fixed",
breaks=c(0, 200, 500, 1000, 1500, 2000, Inf),
palette = "RdYlGn")+
sf::sf_use_s2(FALSE)+
tm_shape(lk) +
tm_fill("lightblue")+
tm_polygons("#a6cee3") +
tm_layout(bg.color="white")+
tm_legend(legend.outside = TRUE)+
tm_layout(bg.color="white",
main.title = "Booster Vaccination (National)",
main.title.position = "left")+
tm_compass(type = 'arrow', position = c(0.05, 0.8))+
tm_scale_bar(position = c("RIGHT", "BOTTOM"))+
tm_scale_bar(position = c("RIGHT", "BOTTOM"))+
tm_credits("Data from 2021 to date",
position = c("LEFT", "TOP"))
region_data <- read_excel("region_data.xls")
reg_df <- region_data %>%
filter(region!="Armed forces") %>%
#separate(district, c("district","dst"),sep = " ",remove = T) %>%
separate(period, c("epi_wk","yr"),sep = " ",remove = T) %>%
rowwise() %>%
mutate(booster = as.integer(booster),
first_dose=as.integer(first_dose),
second_dose=as.integer(`2nd_dose`),
jj=as.integer(jj),
p_vax=(first_dose),
f_vax=sum(second_dose,jj, na.rm=TRUE),
wk = as.integer(substring(epi_wk,2))) %>%
select(region, wk, yr, p_vax, f_vax, booster) %>%
group_by(region, wk, yr) %>%
summarise(p_vax=sum(p_vax),
f_vax=sum(f_vax),
booster=sum(booster))
regions <- reg_df %>%
mutate_at(4, ~replace_na(.,0)) %>%
mutate_at(5, ~replace_na(.,0)) %>%
mutate_at(6, ~replace_na(.,0)) %>%
group_by(region) %>%
summarise(p_vax=sum(p_vax),
f_vax=sum(f_vax),
booster=sum(booster))
regn_shp <- readOGR("C:/Users/User/Desktop/EPIVAC/Regions/Region", "UDHS Regions 2019")
reg_shp <- merge(x=regn_shp,y= regions, by.x= "Name", by.y ="region", all = T)
tm_shape(reg_shp)+
tm_borders()+
tm_fill( col=c("p_vax"),
title=c("Counts"),
style="fixed",
breaks=c(0, 400000, 500000, 1000000,Inf),
palette = "RdYlGn")+
sf::sf_use_s2(FALSE)+
tm_shape(lk) +
tm_fill("lightblue")+
tm_polygons("#a6cee3") +
tm_layout(bg.color="white")+
tm_legend(legend.outside = TRUE)+
tm_layout(bg.color="white",
main.title = "Partial Vaccination (Regional)",
main.title.position = "left")+
tm_compass(type = 'arrow', position = c(0.05, 0.8))+
tm_scale_bar(position = c("RIGHT", "BOTTOM"))+
tm_scale_bar(position = c("RIGHT", "BOTTOM"))+
tm_credits("Data from 2021 to date",
position = c("LEFT", "TOP"))
tm_shape(reg_shp)+
tm_borders()+
tm_fill( col=c("f_vax"),
title=c("Counts"),
style="fixed",
breaks=c(0, 100000, 400000, 800000, Inf),
palette = "RdYlGn")+
sf::sf_use_s2(FALSE)+
tm_shape(lk) +
tm_fill("lightblue")+
tm_polygons("#a6cee3") +
tm_layout(bg.color="white")+
tm_legend(legend.outside = TRUE)+
tm_layout(bg.color="white",
main.title = "Full Vaccination (Regional)",
main.title.position = "left")+
tm_compass(type = 'arrow', position = c(0.05, 0.8))+
tm_scale_bar(position = c("RIGHT", "BOTTOM"))+
tm_scale_bar(position = c("RIGHT", "BOTTOM"))+
tm_credits("Data from 2021 to date",
position = c("LEFT", "TOP"))
tm_shape(reg_shp)+
tm_borders()+
tm_fill( col=c("booster"),
title=c("Counts"),
style="fixed",
breaks=c(0,50000, 600000, Inf),
palette = "RdYlGn")+
sf::sf_use_s2(FALSE)+
tm_shape(lk) +
tm_fill("lightblue")+
tm_polygons("#a6cee3") +
tm_layout(bg.color="white")+
tm_legend(legend.outside = TRUE)+
tm_layout(bg.color="white",
main.title = "Booster Vaccination (Regional)",
main.title.position = "left")+
tm_compass(type = 'arrow', position = c(0.05, 0.8))+
tm_scale_bar(position = c("RIGHT", "BOTTOM"))+
tm_credits("Data from 2021 to date",
position = c("LEFT", "TOP"))
##Faceting
tm_shape(reg_shp)+
tm_borders()+
tm_fill( col=c("p_vax"),
title=c("Counts"),
textNA = "missing",
style="fixed",
breaks=c(0, 400000,500000,1000000,Inf),
palette = "RdYlGn")+
tm_facets('F15Regions')+
tm_shape(lk) +
tm_polygons("#a6cee3" ) +
tm_layout(bg.color="white")+
tm_legend(legend.outside = TRUE)+
tm_layout(bg.color="white",
main.title = "Partial Vaccination by Region",
main.title.position = "left")
tm_shape(reg_shp)+
tm_borders()+
tm_fill( col=c("f_vax"),
title=c("Counts"),
textNA = "missing",
style="fixed",
breaks=c(0, 100000, 400000, 800000, Inf),
palette = "RdYlGn")+
tm_facets('F15Regions')+
tm_shape(lk) +
tm_polygons("#a6cee3" ) +
tm_layout(bg.color="white")+
tm_legend(legend.outside = TRUE)+
tm_layout(bg.color="white",
main.title = "Full Vaccination by Region",
main.title.position = "left")
tm_shape(reg_shp)+
tm_borders()+
tm_fill( col=c("booster"),
title=c("Counts"),
textNA = "missing",
style="fixed",
breaks=c(0,50000, 600000, Inf),
palette = "RdYlGn")+
tm_facets('F15Regions')+
tm_shape(lk) +
tm_polygons("#a6cee3" ) +
tm_layout(bg.color="white")+
tm_legend(legend.outside = TRUE)+
tm_layout(bg.color="white",
main.title = "Booster Vaccination by Region",
main.title.position = "left")
sub_county_data <- read_excel("sub_county_data.xls", guess_max = 100000)
sub_data <- sub_county_data %>%
separate(period, c("month","yr"),sep = " ",remove = T) %>%
mutate(booster = as.integer(boosetr),
first_dose=as.integer(first_dose),
second_dose=as.integer(second_dose),
jj=as.integer(jj))
sub_data %<>%
rowwise() %>%
mutate(p_vax=(first_dose),
f_vax=sum(second_dose,jj, na.rm=TRUE)) %>%
select(sub_county, p_vax, f_vax, booster) %>%
mutate_at(2, ~replace_na(.,0)) %>%
mutate_at(3, ~replace_na(.,0)) %>%
mutate_at(4, ~replace_na(.,0))
#
sub_data %<>%
group_by(sub_county) %>%
summarise(p_vax=sum(p_vax),
full_vax=sum(f_vax),
booster_vax=sum(booster))
#fitting in the sub-county shapefile
sub_shp <- readOGR("C:/Users/User/Desktop/EPIVAC/Subcounties", "Subcounties")
sub_mg <- merge(x=sub_shp,y= sub_data, by.x= "name", by.y ="sub_county", all = T)
tm_shape(sub_mg)+
tm_borders()+
tm_fill( col=c("p_vax"),
title=c("Counts"),
textNA = "missing",
style="fixed",
breaks=c(0, 1000, 3000, 4000, 5000, 10000,Inf),
palette = "RdYlGn")+
tm_shape(lk) +
tm_polygons("#a6cee3" ) +
tm_layout(bg.color="white")+
tm_legend(legend.outside = TRUE)+
tm_layout(bg.color="white",
main.title = "Partial Vaccination at sub-county level",
main.title.position = "left")
tm_shape(sub_mg)+
tm_borders()+
tm_fill( col=c("full_vax"),
title=c("Counts"),
textNA = "missing",
style="fixed",
breaks=c(0, 1000, 3000, 4000, 5000, 10000,Inf),
palette = "RdYlGn")+
tm_shape(lk) +
tm_polygons("#a6cee3" ) +
tm_layout(bg.color="white")+
tm_legend(legend.outside = TRUE)+
tm_layout(bg.color="white",
main.title = "Full Vaccination at sub-county level",
main.title.position = "left")