Adding map tab

BDI-pathogens · Jan 1, 2021 · fba6017 · fba6017
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diff --git a/data/engwales.dbf b/data/engwales.dbf
diff --git a/data/engwales.prj b/data/engwales.prj
@@ -0,0 +1 @@
+PROJCS["British_National_Grid",GEOGCS["GCS_OSGB_1936",DATUM["D_OSGB_1936",SPHEROID["Airy_1830",6377563.396,299.3249646]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",400000.0],PARAMETER["False_Northing",-100000.0],PARAMETER["Central_Meridian",-2.0],PARAMETER["Scale_Factor",0.9996012717],PARAMETER["Latitude_Of_Origin",49.0],UNIT["Meter",1.0]]
diff --git a/data/engwales.shp b/data/engwales.shp
diff --git a/data/engwales.shx b/data/engwales.shx
diff --git a/data/latest_df.for.plotting.incidence.ltlas.RData b/data/latest_df.for.plotting.incidence.ltlas.RData
diff --git a/data/latest_projected.cases.ltlas.RData b/data/latest_projected.cases.ltlas.RData
diff --git a/data/population_by_region.csv b/data/population_by_region.csv
@@ -427,4 +427,5 @@ Mid Ulster,Local Government District,148528
 "Newry, Mourne and Down",Local Government District,181368
 Aylesbury Vale,Not sure,199448
 South Bucks,Not sure,70043
-Wycombe,Not sure,174641
+Wycombe,Not sure,174641
+Chiltern,Not sure,95927
diff --git a/global.R b/global.R
@@ -12,6 +12,9 @@ library(data.table) # for cases by age
 library(stringr) # for cases by age
 library(stringi) # for cases by age
 library(viridis)
+library(leaflet) # for maps
+library(sf) # for maps
+library(adegenet) # for colouring maps
 # library(httr) # for accessing latest data; needed this when updates were done within the app but don't need it whilst running "prepping_the_data.R" manually
 # options(shiny.trace = TRUE)
 # options(shiny.trace = FALSE)
@@ -21,6 +24,9 @@ bs <- 24 # base font size for plots
 source("prep/daily_tracker_setup.R") # load data and plotting scripts for daily tracker tab
 source("prep/cases_by_age_setup.R") # get plotting script for cases by age tab
 
+engwalesmap <- st_read("data/engwales.shp") # load shapefile for maps
+mapcounter <- 1
+
 # load synthetic control analysis
 for (i in 1:8) {
   tmp <- read.csv(glue("data/sc_dataset_scenario_{i}.csv"))

diff --git a/markdown/about.Rmd b/markdown/about.Rmd
@@ -19,14 +19,16 @@ The tabs "March-June Pillar 1 tracker" and "March-June Pillar 1 synthetic contro
 
 The "Daily tracker" tab which is updated daily builds upon our published analysis, using a shorter waiting time between infection and swab date to reflect shorter times to Pillar 2 testing.
 
+The "Map tracker" tab presents the same results as the "Daily tracker" but visualised using maps. We thank Will Probert for providing shapefiles and code towards this.
+
 The "Cases by age" tab presents an analysis developed by Robert Hinch and Michelle Kendall and is also updated daily.
 
 The source code is available on [GitHub](https://github.com/BDI-pathogens/LocalCovidTracker). 
 Please let us know of any issues or requests via the [Issues](https://github.com/BDI-pathogens/LocalCovidTracker/issues) page.
 
 <br>
 
-[1] Michelle Kendall, Luke Milsom, Lucie Abeler-Dörner, Chris Wymant, Luca Ferretti, Mark Briers, Chris Holmes, David Bonsall, Johannes Abeler, Christophe Fraser. <a href="http://www.thelancet.com/journals/landig/article/PIIS2589-7500(20)30241-7/fulltext" target="_blank">  Epidemiological changes on the Isle of Wight after the launch of the NHS Test and Trace programme: a preliminary analysis</a>, <i>The Lancet Digital Health</i>, published online October 14, 2020.
+[1] Michelle Kendall, Luke Milsom, Lucie Abeler-Dörner, Chris Wymant, Luca Ferretti, Mark Briers, Chris Holmes, David Bonsall, Johannes Abeler, Christophe Fraser. <a href="http://www.thelancet.com/journals/landig/article/PIIS2589-7500(20)30241-7/fulltext" target="_blank">  Epidemiological changes on the Isle of Wight after the launch of the NHS Test and Trace programme: a preliminary analysis</a>, <i>The Lancet Digital Health</i>,  Volume 2, Issue 12, E658-E666, December 01, 2020.
 
 
 

diff --git a/markdown/about.md b/markdown/about.md
@@ -19,14 +19,16 @@ The tabs "March-June Pillar 1 tracker" and "March-June Pillar 1 synthetic contro
 
 The "Daily tracker" tab which is updated daily builds upon our published analysis, using a shorter waiting time between infection and swab date to reflect shorter times to Pillar 2 testing.
 
+The "Map tracker" tab presents the same results as the "Daily tracker" but visualised using maps. We thank Will Probert for providing shapefiles and code towards this.
+
 The "Cases by age" tab presents an analysis developed by Robert Hinch and Michelle Kendall and is also updated daily.
 
 The source code is available on [GitHub](https://github.com/BDI-pathogens/LocalCovidTracker). 
 Please let us know of any issues or requests via the [Issues](https://github.com/BDI-pathogens/LocalCovidTracker/issues) page.
 
 <br>
 
-[1] Michelle Kendall, Luke Milsom, Lucie Abeler-Dörner, Chris Wymant, Luca Ferretti, Mark Briers, Chris Holmes, David Bonsall, Johannes Abeler, Christophe Fraser. <a href="http://www.thelancet.com/journals/landig/article/PIIS2589-7500(20)30241-7/fulltext" target="_blank">  Epidemiological changes on the Isle of Wight after the launch of the NHS Test and Trace programme: a preliminary analysis</a>, <i>The Lancet Digital Health</i>, published online October 14, 2020.
+[1] Michelle Kendall, Luke Milsom, Lucie Abeler-Dörner, Chris Wymant, Luca Ferretti, Mark Briers, Chris Holmes, David Bonsall, Johannes Abeler, Christophe Fraser. <a href="http://www.thelancet.com/journals/landig/article/PIIS2589-7500(20)30241-7/fulltext" target="_blank">  Epidemiological changes on the Isle of Wight after the launch of the NHS Test and Trace programme: a preliminary analysis</a>, <i>The Lancet Digital Health</i>,  Volume 2, Issue 12, E658-E666, December 01, 2020.
 
 
 

diff --git a/server.R b/server.R
@@ -552,6 +552,252 @@ server <- function(input, output, session) {
       )
   })
 
+  ### MAPS
+
+  getDateMaps <- reactive({
+    as.Date(input$date.slider.maps, format="%d %b %y")
+  })
+
+  output$mapDate <- renderUI({
+    nice.date <- format(getDateMaps(), format="%d %B %Y")
+    HTML(glue("<h2><b>{nice.date}</b></h2>"))
+  })
+
+  output$NowcastMap <- renderLeaflet({
+    this.date.nowcast <- projected.cases.ltlas %>% filter(Dates == last.date - 31 - R.trim) 
+    this.date.nowcast$lad19cd <- this.date.nowcast$AreaCode
+    this.date.nowcast$fill <- num2col(this.date.nowcast$scaled_per_capita, col.pal=colorRampPalette(c('#fff5f0','#fee0d2','#fcbba1','#fc9272','#fb6a4a','#ef3b2c','#cb181d','#a50f15','#67000d')), x.max=60)
+
+    # combine shape and epi data
+    # using "right_join" removes the places for which we don't have data (Scotland etc.)
+    engwales <- right_join(engwalesmap, subset(this.date.nowcast, select = c("scaled_per_capita","lad19cd","fill")), by = "lad19cd")
+
+    engwales <- engwales %>% st_transform('+proj=longlat +datum=WGS84') # convert the shapefile coordinates into longitudes and latitudes, ready for the leaflet package
+
+    NowcastHoverInfo <- sprintf(
+      "<strong>%s</strong><br/>Projected %g new<br/>infections per 100,000<br/>in the near future",
+      engwales$lad19nm, round(engwales$scaled_per_capita,1)
+    ) %>% lapply(htmltools::HTML)
+
+    leaflet(engwales) %>%
+      addPolygons(layerId =  paste0("nowcast.",mapcounter,".",1:337),
+                  fillColor = ~fill,
+                  weight = 1,
+                  opacity = 1,
+                  color = "white",
+                  dashArray = "3",
+                  fillOpacity = 1,
+                  highlight = highlightOptions(
+                    weight = 5,
+                    color = "#666",
+                    dashArray = "",
+                    fillOpacity = 0.7,
+                    bringToFront = TRUE),
+                  label = NowcastHoverInfo,
+                  labelOptions = labelOptions(
+                    style = list("font-weight" = "normal", padding = "3px 8px"),
+                    textsize = "15px",
+                    direction = "auto")) %>%
+      addLegend("topright",
+                colors = colorRampPalette(c('#fff5f0','#fee0d2','#fcbba1','#fc9272','#fb6a4a','#ef3b2c','#cb181d','#a50f15','#67000d'))(7),
+                labels = c(seq(0,50,by=10),"60+"),
+                title = "per 100,000")
+
+  })
+
+  output$InfectionsMap <- renderLeaflet({
+    this.date.inf <- df.for.plotting.incidence.ltlas %>% filter(Dates == last.date - 31 - R.trim)
+    this.date.inf$lad19cd <- this.date.inf$AreaCode
+    this.date.inf$fill <- num2col(this.date.inf$scaled_per_capita, col.pal=colorRampPalette(c('#fff5f0','#fee0d2','#fcbba1','#fc9272','#fb6a4a','#ef3b2c','#cb181d','#a50f15','#67000d')), x.max=60)
+
+    # combine shape and epi data
+    # using "right_join" removes the places for which we don't have data (Scotland etc.)
+    engwales <- right_join(engwalesmap, subset(this.date.inf, select = c("scaled_per_capita","lad19cd", "fill")), by = "lad19cd")
+
+    engwales <- engwales %>% st_transform('+proj=longlat +datum=WGS84') # convert the shapefile coordinates into longitudes and latitudes, ready for the leaflet package 
+
+    InfHoverInfo <- sprintf(
+      "<strong>%s</strong><br/>%g new infections per 100,000",
+      engwales$lad19nm, round(engwales$scaled_per_capita,1)
+    ) %>% lapply(htmltools::HTML)
+
+    leaflet(engwales) %>%
+      addPolygons(layerId = paste0("infections.",mapcounter,".",1:337),
+                  fillColor = ~fill,
+                  weight = 1,
+                  opacity = 1,
+                  color = "white",
+                  dashArray = "3",
+                  fillOpacity = 1,
+                  highlight = highlightOptions(
+                    weight = 5,
+                    color = "#666",
+                    dashArray = "",
+                    fillOpacity = 0.7,
+                    bringToFront = TRUE),
+                  label = InfHoverInfo,
+                  labelOptions = labelOptions(
+                    style = list("font-weight" = "normal", padding = "3px 8px"),
+                    textsize = "15px",
+                    direction = "auto")) %>%
+      addLegend("topright",
+                colors = colorRampPalette(c('#fff5f0','#fee0d2','#fcbba1','#fc9272','#fb6a4a','#ef3b2c','#cb181d','#a50f15','#67000d'))(7),
+                labels = c(seq(0,50,by=10),"60+"),
+                title = "per 100,000")
+  })
+
+  output$RMap <- renderLeaflet({
+    this.date.R <- df.for.plotting.R.ltlas %>% filter(Dates == last.date - 31 - R.trim)
+    this.date.R$lad19cd <- this.date.R$AreaCode
+    this.date.R$fill <- num2col(this.date.R$R, col.pal=colorRampPalette(c('#313695','#4575b4','#74add1','#abd9e9','#e0f3f8','#ffffbf','#fee090','#fdae61','#f46d43','#d73027','#a50026')), x.min=0, x.max=2)
+
+    # combine shape and epi data
+    # using "right_join" removes the places for which we don't have data (Scotland etc.)
+    engwales <- right_join(engwalesmap, subset(this.date.R, select = c("R", "lad19cd", "fill")), by = "lad19cd")
+
+    engwales <- engwales %>% st_transform('+proj=longlat +datum=WGS84') # convert the shapefile coordinates into longitudes and latitudes, ready for the leaflet package 
+
+    RHoverInfo <- sprintf(
+      "<strong>%s</strong><br/>R = %g",
+      engwales$lad19nm, round(engwales$R,2)
+    ) %>% lapply(htmltools::HTML)
+
+    leaflet(engwales) %>%
+      addPolygons(layerId = paste0("R.",mapcounter,".",1:337),
+                  fillColor = ~fill,
+                  weight = 1,
+                  opacity = 1,
+                  color = "white",
+                  dashArray = "3",
+                  fillOpacity = 1,
+                  highlight = highlightOptions(
+                    weight = 5,
+                    color = "#666",
+                    dashArray = "",
+                    fillOpacity = 0.7,
+                    bringToFront = TRUE),
+                  label = RHoverInfo,
+                  labelOptions = labelOptions(
+                    style = list("font-weight" = "normal", padding = "3px 8px"),
+                    textsize = "15px",
+                    direction = "auto")) %>%
+      addLegend("topright",
+                colors = colorRampPalette(c('#313695','#4575b4','#74add1','#abd9e9','#e0f3f8','#ffffbf','#fee090','#fdae61','#f46d43','#d73027','#a50026'))(5),
+                labels = c("0.0","0.5","1.0","1.5","2.0+"),
+                title = "R")
+
+  })
+
+  observeEvent(input$date.slider.maps, {
+    this.date <-  getDateMaps()
+
+    this.date.nowcast <- projected.cases.ltlas %>% filter(Dates == this.date)
+    this.date.nowcast$lad19cd <- this.date.nowcast$AreaCode
+    this.date.nowcast$fill <- num2col(this.date.nowcast$scaled_per_capita, col.pal=colorRampPalette(c('#fff5f0','#fee0d2','#fcbba1','#fc9272','#fb6a4a','#ef3b2c','#cb181d','#a50f15','#67000d')), x.max=60)
+
+    this.date.inf <- df.for.plotting.incidence.ltlas %>% filter(Dates == this.date)
+    this.date.inf$lad19cd <- this.date.inf$AreaCode
+    this.date.inf$fill <- num2col(this.date.inf$scaled_per_capita, col.pal=colorRampPalette(c('#fff5f0','#fee0d2','#fcbba1','#fc9272','#fb6a4a','#ef3b2c','#cb181d','#a50f15','#67000d')), x.max=60)
+
+    this.date.R <- df.for.plotting.R.ltlas %>% filter(Dates == this.date)
+    this.date.R$lad19cd <- this.date.R$AreaCode
+    this.date.R$fill <- num2col(this.date.R$R, col.pal=colorRampPalette(c('#313695','#4575b4','#74add1','#abd9e9','#e0f3f8','#ffffbf','#fee090','#fdae61','#f46d43','#d73027','#a50026')), x.min=0, x.max=2)
+
+    # combine shape and epi data
+    # using "right_join" removes the places for which we don't have data (Scotland etc.)
+    this.date.nowcast <- right_join(engwalesmap, subset(this.date.nowcast, select = c("scaled_per_capita","lad19cd","fill")), by = "lad19cd")
+    this.date.nowcast <- this.date.nowcast %>% st_transform('+proj=longlat +datum=WGS84') # convert the shapefile coordinates into longitudes and latitudes, ready for the leaflet package
+
+    this.date.inf <- right_join(engwalesmap, subset(this.date.inf, select = c("scaled_per_capita","lad19cd", "fill")), by = "lad19cd")
+    this.date.inf <- this.date.inf %>% st_transform('+proj=longlat +datum=WGS84') # convert the shapefile coordinates into longitudes and latitudes, ready for the leaflet package 
+
+    this.date.R <- right_join(engwalesmap, subset(this.date.R, select = c("R", "lad19cd", "fill")), by = "lad19cd")
+    this.date.R <- this.date.R %>% st_transform('+proj=longlat +datum=WGS84') # convert the shapefile coordinates into longitudes and latitudes, ready for the leaflet package 
+
+    NowcastHoverInfo <- sprintf(
+      "<strong>%s</strong><br/>Projected %g new<br/>infections per 100,000<br/>in the near future",
+      this.date.nowcast$lad19nm, round(this.date.nowcast$scaled_per_capita,1)
+    ) %>% lapply(htmltools::HTML)
+
+    InfHoverInfo <- sprintf(
+      "<strong>%s</strong><br/>%g new infections per 100,000",
+      this.date.inf$lad19nm, round(this.date.inf$scaled_per_capita,1)
+    ) %>% lapply(htmltools::HTML)
+
+    RHoverInfo <- sprintf(
+      "<strong>%s</strong><br/>R = %g",
+      this.date.R$lad19nm, round(this.date.R$R,2)
+    ) %>% lapply(htmltools::HTML)
+
+    leafletProxy("NowcastMap", data=this.date.nowcast) %>%
+      addPolygons(layerId = paste0("nowcast.",mapcounter+1,".",1:337), # assigning layerIds is supposed to mean that the previous ones get deleted (otherwise there's a big slow-down as more dates are viewed)
+        fillColor = ~fill,
+                  weight = 1,
+                  opacity = 1,
+                  color = "white",
+                  dashArray = "3",
+                  fillOpacity = 1,
+                  highlight = highlightOptions(
+                    weight = 5,
+                    color = "#666",
+                    dashArray = "",
+                    fillOpacity = 0.7,
+                    bringToFront = TRUE),
+                  label = NowcastHoverInfo,
+                  labelOptions = labelOptions(
+                    style = list("font-weight" = "normal", padding = "3px 8px"),
+                    textsize = "15px",
+                    direction = "auto")) %>%
+      removeShape(layerId = paste0("nowcast.",mapcounter,".",1:337)) # remove the _underneath_ layer so that we don't get jumpiness or slowdown
+
+    leafletProxy("InfectionsMap", data=this.date.inf) %>%
+      addPolygons(layerId = paste0("infections.",mapcounter+1,".",1:337),
+                  fillColor = ~fill,
+                  weight = 1,
+                  opacity = 1,
+                  color = "white",
+                  dashArray = "3",
+                  fillOpacity = 1,
+                  highlight = highlightOptions(
+                    weight = 5,
+                    color = "#666",
+                    dashArray = "",
+                    fillOpacity = 0.7,
+                    bringToFront = TRUE),
+                  label = InfHoverInfo,
+                  labelOptions = labelOptions(
+                    style = list("font-weight" = "normal", padding = "3px 8px"),
+                    textsize = "15px",
+                    direction = "auto")) %>%
+      removeShape(layerId = paste0("infections.",mapcounter,".",1:337))
+
+    leafletProxy("RMap", data=this.date.R) %>%
+      addPolygons(layerId = paste0("R.",mapcounter+1,".",1:337),
+                  fillColor = ~fill,
+                  weight = 1,
+                  opacity = 1,
+                  color = "white",
+                  dashArray = "3",
+                  fillOpacity = 1,
+                  highlight = highlightOptions(
+                    weight = 5,
+                    color = "#666",
+                    dashArray = "",
+                    fillOpacity = 0.7,
+                    bringToFront = TRUE),
+                  label = RHoverInfo,
+                  labelOptions = labelOptions(
+                    style = list("font-weight" = "normal", padding = "3px 8px"),
+                    textsize = "15px",
+                    direction = "auto")) %>%
+      removeShape(layerId = paste0("R.",mapcounter,".",1:337))
+
+    mapcounter <- mapcounter + 1
+  })
+
+  # output$MapTitle <- renderUI({
+  #   h3(format(getDateMaps(), "%d %B %Y"))
+  # })
 
   ### Cases by age
 
@@ -985,6 +1231,13 @@ server <- function(input, output, session) {
     HTML(glue("<h5>Last updated {last.datestamp} <br>using data up to {last.date.of.data}.</h5>"))
   })
 
+
+  output$updatedInfoMaps <- renderUI({
+    last.datestamp <- getLastDatestamp()
+    last.date.of.data <- getLastDateOfData()
+    HTML(glue("<h5>Last updated {last.datestamp} <br>using data up to {last.date.of.data}.</h5>"))
+  })
+
   output$updatedInfoAges <- renderUI({
     last.datestamp <- getLastDatestamp()
     last.date.of.data <- getLastDateOfData()
Original file line number	Diff line number	Diff line change
		@@ -0,0 +1 @@
		PROJCS["British_National_Grid",GEOGCS["GCS_OSGB_1936",DATUM["D_OSGB_1936",SPHEROID["Airy_1830",6377563.396,299.3249646]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Transverse_Mercator"],PARAMETER["False_Easting",400000.0],PARAMETER["False_Northing",-100000.0],PARAMETER["Central_Meridian",-2.0],PARAMETER["Scale_Factor",0.9996012717],PARAMETER["Latitude_Of_Origin",49.0],UNIT["Meter",1.0]]