Generalized Immunity change

batchRuns/ODESGeneralizedImmunity.R

@@ -767,7 +767,7 @@ SEAI_wildOnly<-function(t,y,p){
   })
 }
 
-allPara<-read.csv("MalariaResistance/batchRuns/ParamListGen.csv",sep=",",header=T)
+allPara<-read.csv(paramFile,sep=",",header=T)
 
 currentPara<-allPara[allPara$No==No,]
 

batchRuns/analyze_codes.r

@@ -1,8 +1,9 @@
-setwd("~/Dropbox/research/current/resistance/MalariaResistance/batchRuns/")
+setwd("~/MalariaResistance/batchRuns/")
 library(tidyverse)
 library(cowplot)
-oneLR<-read.csv("v4_param_results.csv")
-#oneLR<-read.csv("v5_param_results.csv")
+library(dplyr)
+#oneLR<-read.csv("v4_param_results.csv")
+oneLR<-read.csv("v5_param_results.csv")
 straRef<-data.frame(nstrains=ceiling(10^(seq(0.7,2.3,0.15))),rawStrains = 10^(seq(0.7,2.3,0.15)))
 oneLR<-oneLR%>%left_join(straRef,by="nstrains")
 oneLR<-oneLR%>%mutate(resistP = PR/P,
@@ -12,7 +13,7 @@ oneLR<-oneLR%>%mutate(resistP = PR/P,
                       rSU = (PW_SU+PR_SU)/(SU+1),
                       rSD = (PW_SD+PR_SD)/(SD+1),
                       rAU = (PW_AU+PR_AU)/(AU+1),
-                      rAD = (PW_AD+PW_AD)/(AD+1),
+                      rAD = (PW_AD+PR_AD)/(AD+1),
                       I_NU = 1-exp(-rNU),
                       I_ND = 1-exp(-rND),
                       I_SU = 1-exp(-rSU),
@@ -29,6 +30,34 @@ ggplot(oneLR%>%filter(wildOnly==0,d1>0), aes(log10(adjB),log10(rawStrains)))+
   geom_raster(aes(fill=resistP))+scale_fill_viridis_c()+
   facet_wrap(d1~seasonality, labeller="label_both")
 
+# host populations
+ggplot(oneLR%>%filter(wildOnly==0,d1>0), aes(log10(adjB),log10(rawStrains)))+
+  geom_raster(aes(fill=N))+scale_fill_viridis_c()+
+  facet_wrap(d1~seasonality, labeller="label_both")
+
+ggplot(oneLR%>%filter(wildOnly==0,d1>0), aes(log10(adjB),N)) + geom_point() + geom_line(aes(color=as.factor(log10(rawStrains))))
+
+ggplot(oneLR%>%filter(wildOnly==0,d1>0), aes(log10(adjB),(NU+ND)/N)) + geom_point()+geom_line(aes(color=as.factor(log10(rawStrains))))
+
+ggplot(oneLR%>%filter(wildOnly==0,d1>0), aes(log10(adjB),(NU+ND)/N)) + geom_point()+geom_line(aes(color=as.factor(seasonality)))
+
+
+ggplot(oneLR%>%filter(wildOnly==0,d1>0), aes(log10(adjB),(SU+SD)/N)) + geom_point()+geom_line(aes(color=as.factor(log10(rawStrains))))
+
+ggplot(oneLR%>%filter(wildOnly==0,d1>0), aes(log10(adjB),(AU+AD)/N)) + geom_point()+geom_line(aes(color=as.factor(log10(rawStrains))))
+
+#host-specific prevalence
+
+ggplot(oneLR%>%filter(wildOnly==0,d1>0), aes(log10(adjB),(I_SU*SU+I_SD*SD)/(SU+SD))) + geom_point() + geom_line(aes(color=as.factor(log10(rawStrains))))
+
+ggplot(oneLR%>%filter(wildOnly==0,d1>0), aes(log10(adjB),(I_NU*NU+I_ND*ND)/(NU+ND))) + geom_point() + geom_line(aes(color=as.factor(log10(rawStrains))))
+
+ggplot(oneLR%>%filter(wildOnly==0,d1>0), aes(log10(adjB),(I_AU*AU+I_AD*AD)/(AU+AD))) + geom_point() + geom_line(aes(color=as.factor(log10(rawStrains))))
+
+ggplot(oneLR%>%filter(wildOnly==0,d1>0), aes(log10(adjB),(PR_AU+PR_AD)/(PR_AU+PR_AD+PW_AU+PW_AD))) + geom_point() + geom_line(aes(color=as.factor(log10(rawStrains))))
+
+
+
 # prevalence as a function of starting conditions
 ggplot(oneLR%>%drop_na()%>%filter(nstrains%in%c(10,20,80,159),d1==1), 
        aes(log10(adjB),adjPrev,
@@ -47,17 +76,51 @@ ggplot(oneLR%>%drop_na()%>%filter(wildOnly==0,d1>0), aes(log10(adjB*adjPrev*365)
 ggplot(oneLR%>%filter(wildOnly==0,d1>0),aes(I_AU,resistP))+
   geom_point(aes(color=log10(nstrains/adjB),shape=as.factor(seasonality)))+scale_color_viridis_c(option="plasma")+xlab("Prevalance in Asymptomatic")+ylab("percentage of resistance")+
   facet_grid(d1~.,labeller="label_both")+
+  theme_cowplot()+
+  geom_smooth()
+
+ggplot(oneLR%>%filter(wildOnly==0,d1>0),aes(resistP,I_NU))+
+  geom_point(aes(color=log10(nstrains/adjB),shape=as.factor(seasonality)))+scale_color_viridis_c(option="plasma")+xlab("Prevalance in Naive")+ylab("percentage of resistance")+
+  facet_grid(d1~.,labeller="label_both")+
+  theme_cowplot()+
+  geom_smooth()
+
+ggplot(oneLR%>%filter(wildOnly==0,d1>0),aes(I_SU,resistP))+
+  geom_point(aes(color=log10(nstrains/adjB),shape=as.factor(seasonality)))+scale_color_viridis_c(option="plasma")+xlab("Prevalance in Symptomatic")+ylab("percentage of resistance")+
+  facet_grid(d1~.,labeller="label_both")+
+  theme_cowplot()+
+  geom_smooth()
+
+ggplot(oneLR%>%filter(wildOnly==0,d1>0),aes(adjPrev,(1-(1/nstrains))^m_A))+
+  geom_point(aes(color=log10(nstrains/adjB),shape=as.factor(seasonality)))+scale_color_viridis_c(option="plasma")+xlab("adjPrev")+ylab("infectivity")+
+  facet_grid(d1~.,labeller="label_both")+
+  theme_cowplot()+
+  geom_smooth()
+
+ggplot(oneLR%>%filter(wildOnly==0,d1>0),aes(log10(adjB),adjPrev))+
+  scale_color_viridis_d(option="plasma")+geom_line(aes(color=as.factor(nstrains)))+
+  facet_grid(d1~seasonality,labeller="label_both")+
   theme_cowplot()
 
+
+ggplot(oneLR%>%filter(wildOnly==0,d1>0),aes(log10(adjB),(AU+AD)/N))+
+  geom_point(aes(color=log10(nstrains/adjB),shape=as.factor(seasonality)))+scale_color_viridis_c(option="plasma")+xlab("adjB")+ylab("proportion asymptomatic")+
+  facet_grid(d1~.,labeller="label_both")+
+  theme_cowplot()+
+  geom_smooth()
+
+
 # prevalence vs resistance
 ggplot(oneLR%>%filter(wildOnly==0,d1>0),aes(adjPrev,resistP))+
   geom_point(aes(color=log10(nstrains/adjB),shape=as.factor(seasonality)))+scale_color_viridis_c(option="plasma")+
   xlab("Prevalance")+ylab("percentage of resistance")+
   facet_grid(d1~.,labeller="label_both")+
-  theme_cowplot()
+  theme_cowplot()+
+  geom_smooth()
 
 
 
 
 
 
+require(ggplot2)