R/infectiousnessprofiles_paper.R

In IOM-Research/CEMRA: COVID Exposure Model and Risk Application

library(ggplot2)
library(tidyr)
library(dplyr)
library(ggpubr)

donotruninapp3<-function(x){
  
numberinfectedgraph<-function(output, infectiousness, type){
    
    output<-output[(grepl(infectiousness, output$ID)),]
    
    output$ID<-gsub('(.*)_\\w+', '\\1', output$ID)
    output$ID<-gsub('CEMRA_', '', output$ID)
    output$ID<-gsub('ADM_', '', output$ID)
    output$ID<-gsub('BASELINE_', '', output$ID)
    output$ID<-gsub('ENG_', '', output$ID)
    output$ID<-gsub('PPE_', '', output$ID)
    
    output$ID[output$ID=="noint"]<-"No Intervention"
    output$ID[output$ID=="surgicalmask"]<-"Surgical Mask"
    output$ID[output$ID=="surgicalmask_surfacedis"]<-"Surgical mask + Surface disinfection"
    output$ID[output$ID=="surgicalmask_surfacedishandhygiene"]<-"Surgical mask + Surface disinfection + Hand hygiene"
    output$ID[output$ID=="surgicalmask_freshair"]<-"Surgical Mask + Natural ventilation"
    output$ID[output$ID=="surgicalmask_UVC_bcs"]<-"Surgical Mask + UVC air purification (best efficacy)"
    output$ID[output$ID=="surgicalmask_UVC_irl"]<-"Surgical Mask + UVC air purification (sub-optimal efficacy)"
    output$ID[output$ID=="surgicalmask_VentHead"]<-"Surgical Mask + Ventilated Headboard"
    
    output$ID<-factor(output$ID, levels=c("No Intervention",
                                          "Surgical Mask",
                                          "Surgical mask + Surface disinfection",
                                          "Surgical mask + Surface disinfection + Hand hygiene",
                                          "Surgical Mask + Natural ventilation",
                                          "Surgical Mask + UVC air purification (best efficacy)",
                                          "Surgical Mask + UVC air purification (sub-optimal efficacy)",
                                          "Surgical Mask + Ventilated Headboard",
                                          "FFP2",
                                          "FFP3",
                                          "Airhood"))
    
    if(type=="loginfrisk"){
      
      ##### Output 1: Log infection risk 
      output %>% 
        group_by(ID) %>%
        select(ID, rFACE, rLUNGNF, rLUNGFF, rSPRAY) %>%
        mutate_at(., c("rFACE", "rLUNGNF", "rLUNGFF", "rSPRAY"), ~as.numeric(.))%>%
        pivot_longer(!ID, names_to="cat", values_to="value") %>%
        mutate(cat=factor(cat, levels=c("rFACE","rLUNGNF","rLUNGFF","rSPRAY"))) %>%
        mutate(value=log(value))%>%
        ggplot(., aes(x=cat, y=value, colour=ID)) + 
        geom_boxplot()+
        xlab("Route")+
        ylab("Log Infection")+ scale_x_discrete(labels=c("rFACE" = "Contact", "rLUNGNF" = "Inhalation Near Field",
                                                         "rLUNGFF" = "Inhalation Far Field",
                                                         "rSPRAY" = "Cough Spray")) + 
        theme(axis.text.x=element_text(angle=15, hjust=1),
              text = element_text(size = 18),
              legend.position = "none")+
        scale_colour_grey()
    } else if(type=="percentagedecrease"){
      
      test<-output %>% 
        group_by(ID) %>%
        select(ID, rOVERALL) %>%
        mutate_at(., c("rOVERALL"), ~as.numeric(.))%>%
        summarise(medianval=median(rOVERALL))
      
      baseline<-test[1,2]
      
      test <-test %>%
        mutate(percentagechange=round(medianval/as.numeric(baseline)*100))
      
    }else if(type=="predictedairconc"){
      test<-output %>% 
        filter(ID=="No Intervention")
      test
    }
  }
  
g<-numberinfectedgraph(output, "extremelylow", "predictedairconc")
h<-numberinfectedgraph(output, "verylow", "predictedairconc")
i<-numberinfectedgraph(output, "low", "predictedairconc")
j<-numberinfectedgraph(output, "average", "predictedairconc")
k<-numberinfectedgraph(output, "high", "predictedairconc")
l<-numberinfectedgraph(output, "veryhigh", "predictedairconc")
m<-numberinfectedgraph(output, "extremelyhigh", "predictedairconc")

g$ID<-"Extremely Low"
h$ID<-"Very Low"
i$ID<-"Low"
j$ID<-"Moderate"
k$ID<-"High"
l$ID<-"Very High"
m$ID<-"Extremely High"

gh<-rbind(g,h)
ghi<-rbind(gh,i)
ghij<-rbind(ghi,j)
ghijk<-rbind(ghij, k)
ghijkl<-rbind(ghijk, l)
ghijklm<-rbind(ghijkl, m)

ghijklm$ID<-factor(ghijklm$ID, levels=c("Extremely Low",
                                        "Very Low",
                                        "Low",
                                        "Moderate",
                                        "High",
                                        "Very High",
                                        "Extremely High"))

ghijklm %>%
  mutate(loggenecopies=log(Nair))%>%
  ggplot(., aes(x=ID, y=loggenecopies)) + 
  geom_boxplot()+
  xlab("Infectiousness profile")+
  ylab("Log Gene copies per m3")+
  geom_hline(yintercept=log(0.014),linetype=2)+
  annotate("rect", xmin=-Inf, xmax=Inf, ymin=log(0.0034), ymax=log(0.047), alpha=0.4, fill="grey")+
  theme(axis.text.x=element_text(angle=15, hjust=1),
        text = element_text(size = 18),
        legend.position = "none")+
  scale_colour_grey()
}