server.R

library(maptools)
library(RColorBrewer)

ShehiaShp<-readShapeSpatial("Data/ZnzPolyIncWGS1984.shp",proj4string=CRS("+proj=longlat"))

# Import case numbers by Shehia using different travel assumptions
Shehia_Inc_Trav<-read.csv("Data/Shehia_Inc_Travel.csv")

# Generate cats for colors
cols <- brewer.pal(10, "RdBu")[10:1]

# Calculate incidence
# Merge case data to shapefile

# First rename some shehias in the Incidence file to match the shapefile
Shehia_Inc_Trav$Shehia<-as.character(Shehia_Inc_Trav$Shehia)
Shehia_Inc_Trav$Shehia[Shehia_Inc_Trav$Shehia=="Mbuzini"]<-"Mbuzini_West"
Shehia_Inc_Trav$Shehia[Shehia_Inc_Trav$Shehia=="Ng'ambwa"]<-"Ng'ambwa_C"

# Merge
ShehiaShp<-merge(ShehiaShp,Shehia_Inc_Trav,by.x="ResShehia",by.y="Shehia",all.x=T)
ShehiaShp$Incidence_Travel<-(ShehiaShp$Shehia_Inc_Travel / ShehiaShp$Populati_1)*1000
ShehiaShp$Incidence_Time_Kern<-(ShehiaShp$Shehia_Time_Kern / ShehiaShp$Populati_1)*1000
ShehiaShp$Incidence_Raw<-(ShehiaShp$Shehia_Raw / ShehiaShp$Populati_1)*1000

ShehiaShp$Incidence_Travel_Wet<-(ShehiaShp$Shehia_Inc_Travel_Wet / ShehiaShp$Populati_1)*1000
ShehiaShp$Incidence_Time_Kern_Wet<-(ShehiaShp$Shehia_Time_Kern_Wet / ShehiaShp$Populati_1)*1000
ShehiaShp$Incidence_Raw_Wet<-(ShehiaShp$Shehia_Raw_Wet / ShehiaShp$Populati_1)*1000

ShehiaShp$Incidence_Travel_Dry<-(ShehiaShp$Shehia_Inc_Travel_Dry / ShehiaShp$Populati_1)*1000
ShehiaShp$Incidence_Time_Kern_Dry<-(ShehiaShp$Shehia_Time_Kern_Dry / ShehiaShp$Populati_1)*1000
ShehiaShp$Incidence_Raw_Dry<-(ShehiaShp$Shehia_Raw_Dry / ShehiaShp$Populati_1)*1000

# Generate colors according to incidence
Cuts<-quantile(ShehiaShp$Incidence_Travel,prob=seq(0,1,0.1),na.rm=T)
Cuts_Wet<-quantile(ShehiaShp$Incidence_Travel_Wet,prob=seq(0,1,0.1),na.rm=T)
Cuts_Dry<-quantile(ShehiaShp$Incidence_Travel_Dry,prob=seq(0,1,0.1),na.rm=T)

Incidence_Travel_Col<-as.numeric(cut(ShehiaShp$Incidence_Travel, Cuts))
Incidence_TimeKern_Col<-as.numeric(cut(ShehiaShp$Incidence_Time_Kern, Cuts))
Incidence_Raw_Col<-as.numeric(cut(ShehiaShp$Incidence_Raw,Cuts))

Incidence_Travel_Col_Wet<-as.numeric(cut(ShehiaShp$Incidence_Travel_Wet, Cuts_Wet))
Incidence_TimeKern_Col_Wet<-as.numeric(cut(ShehiaShp$Incidence_Time_Kern_Wet, Cuts_Wet))
Incidence_Raw_Col_Wet<-as.numeric(cut(ShehiaShp$Incidence_Raw_Wet,Cuts_Wet))

Incidence_Travel_Col_Dry<-as.numeric(cut(ShehiaShp$Incidence_Travel_Dry, Cuts_Dry))
Incidence_TimeKern_Col_Dry<-as.numeric(cut(ShehiaShp$Incidence_Time_Kern_Dry, Cuts_Dry))
Incidence_Raw_Col_Dry<-as.numeric(cut(ShehiaShp$Incidence_Raw_Dry,Cuts_Dry))

# Bind results
Colors<-rbind(Incidence_Travel_Col,Incidence_TimeKern_Col,Incidence_Raw_Col,
              Incidence_Travel_Col_Wet,Incidence_TimeKern_Col_Wet,Incidence_Raw_Col_Wet,
              Incidence_Travel_Col_Dry,Incidence_TimeKern_Col_Dry,Incidence_Raw_Col_Dry)

shinyServer(function(input, output) {
  output$map <- renderPlot({
    
    # select wet or dry season
    Season <- switch(input$season,
                    "Both" = 1,
                    "Wet" = 2,
                    "Dry" = 3)
    
    Travel <- switch(input$travel,
                     "Travel history" = 1,
                     "Time kernal" = 2,
                     "No time" = 3)
    
    Color <- Colors[Season*Travel,]
    
    par(bg = "gray95")
    plot(ShehiaShp,xlim=c(39,39.75),ylim=c(-6.5,-5.7),
         col=cols[Color],border="gray60",lwd=1,asp=1)
  
  },height=700,res=100)
})