###########################################################
### Supplemental Figure 0 - all pairwaise scatter plots ###
###########################################################
# cutoff = 10, annual vs no vaccination
###########################################################
setwd("C:/Users/kainslie/Dropbox/Kylie/Projects/Morevac/data/sim_data/cutoff10/sim1000/")
mean_diff_10 <- vroom(file = "mean_diff_10_sim1000.csv", delim = ",", col_names = TRUE) %>%
mutate(Diff_Color = ifelse(Upper < 0, '<0',ifelse(Lower <=0 & Upper >=0, '0',ifelse(Lower >0, '>0', 'something else'))))
mean_diff_10_an <- mean_diff_10 %>%
filter(Type == "Diff_AN", Diff_Color != '0') %>%
mutate(Abs_Val = abs(Mean_Diff))
p_epsilon_ve0 <- ggplot(data = mean_diff_10_an, aes(x = exposure_penalty, y = vac_protect, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38"), name = 'Difference in Childhood Infections') +
xlab('Exposure Penalty') + ylab('Vaccine Effectiveness') +
theme(legend.position = 'none', panel.grid.major = element_blank(), panel.grid.minor = element_blank(), panel.background = element_blank())
p_epsilon_waning0 <- ggplot(data = mean_diff_10_an, aes(x = exposure_penalty, y = wane, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Exposure Penalty') + ylab('Waning') +
theme(legend.position = 'none', panel.grid.major = element_blank(), panel.grid.minor = element_blank(), panel.background = element_blank())
p_epsilon_take0 <- ggplot(data = mean_diff_10_an, aes(x = exposure_penalty, y = take, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Exposure Penalty') + ylab('Take') +
theme(legend.position = 'none', panel.grid.major = element_blank(), panel.grid.minor = element_blank(), panel.background = element_blank())
p_epsilon_rho0 <- ggplot(data = mean_diff_10_an, aes(x = exposure_penalty, y = rho, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Exposure Penalty') + ylab("Correlation of Vaccination") +
theme(legend.position = 'none', panel.grid.major = element_blank(), panel.grid.minor = element_blank(), panel.background = element_blank())
p_epsilon_vaccov0 <- ggplot(data = mean_diff_10_an, aes(x = exposure_penalty, y = vac_cov, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Exposure Penalty') + ylab("Vaccination Coverage") +
theme(legend.position = 'none', panel.grid.major = element_blank(), panel.grid.minor = element_blank(), panel.background = element_blank())
p_ve_waning0 <- ggplot(data = mean_diff_10_an, aes(x = vac_protect, y = wane, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Vaccine Effectiveness') + ylab('Waning') +
theme(legend.position = 'none', panel.grid.major = element_blank(), panel.grid.minor = element_blank(), panel.background = element_blank())
p_ve_take0 <- ggplot(data = mean_diff_10_an, aes(x = vac_protect, y = take, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Vaccine Effectiveness') + ylab('Take') +
theme(legend.position = 'none', panel.grid.major = element_blank(), panel.grid.minor = element_blank(), panel.background = element_blank())
p_ve_rho0 <- ggplot(data = mean_diff_10_an, aes(x = vac_protect, y = rho, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Vaccine Effectiveness') + ylab('Correlation of Vaccination') +
theme(legend.position = 'none', panel.grid.major = element_blank(), panel.grid.minor = element_blank(), panel.background = element_blank())
p_ve_vaccov0 <- ggplot(data = mean_diff_10_an, aes(x = vac_protect, y = vac_cov, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Vaccine Effectiveness') + ylab('Vaccination Coverage') +
theme(legend.position = 'none', panel.grid.major = element_blank(), panel.grid.minor = element_blank(), panel.background = element_blank())
p_waning_take0 <- ggplot(data = mean_diff_10_an, aes(x = wane, y = take, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Waning') + ylab('Vaccination Coverage') +
theme(legend.position = 'none', panel.grid.major = element_blank(), panel.grid.minor = element_blank(), panel.background = element_blank())
p_waning_rho0 <- ggplot(data = mean_diff_10_an, aes(x = wane, y = rho, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Waning') + ylab("Correlation of Vaccination") +
theme(legend.position = 'none', panel.grid.major = element_blank(), panel.grid.minor = element_blank(), panel.background = element_blank())
p_waning_vaccov0 <- ggplot(data = mean_diff_10_an, aes(x = wane, y = vac_cov, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Waning') + ylab("Vaccination Coverage") +
theme(legend.position = 'none', panel.grid.major = element_blank(), panel.grid.minor = element_blank(), panel.background = element_blank())
p_take_rho0 <- ggplot(data = mean_diff_10_an, aes(x = take, y = rho, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Take') + ylab("Correlation of Vaccination") +
theme(legend.position = 'none', panel.grid.major = element_blank(), panel.grid.minor = element_blank(), panel.background = element_blank())
p_take_vaccov0 <- ggplot(data = mean_diff_10_an, aes(x = take, y = vac_cov, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Take') + ylab("Vaccination Coverage") +
theme(legend.position = 'none', panel.grid.major = element_blank(), panel.grid.minor = element_blank(), panel.background = element_blank())
p_rho_vaccov0 <- ggplot(data = mean_diff_10_an, aes(x = rho, y = vac_cov, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab("Correlation of Vaccination") + ylab("Vaccination Coverage") +
theme(legend.position = 'none', panel.grid.major = element_blank(), panel.grid.minor = element_blank(), panel.background = element_blank())
sm_figure0 <- plot_grid(p_epsilon_ve0, p_epsilon_waning0, p_epsilon_take0,p_epsilon_vaccov0, p_epsilon_rho0,
p_ve_waning0, p_ve_take0, p_ve_rho0, p_ve_vaccov0, p_waning_take0, p_waning_rho0,
p_waning_vaccov0, p_take_rho0, p_take_vaccov0, p_rho_vaccov0,
labels = "AUTO", ncol = 3, align = 'v', axis = 'l')
legend_b <- get_legend( p_epsilon_ve0 + guides(color = guide_legend(nrow = 1)) + theme(legend.position = "bottom"))
sm_figure0 <- plot_grid(sm_figure0, legend_b, ncol = 1, rel_heights = c(1, .1))
# filename <- "~/Dropbox/Kylie/Projects/Morevac/figures/"
filename <- "C:/Users/kainslie/Dropbox/Kylie/Projects/Morevac/figures/"
# filename <- "~/Dropbox/Kylie/Presentations/MRC Symposium/figures/"
png(file = paste0(filename,"SuppMatFig0_sim1000.png"), width = 12, height = 16,
units = "in", pointsize = 8, res = 300)
sm_figure0
dev.off()
###########################################################
### Supplemental Figure 1 - all pairwaise scatter plots ###
###########################################################
# cutoff = 10
###########################################################
setwd("C:/Users/kainslie/Dropbox/Kylie/Projects/Morevac/data/sim_data/cutoff10/sim1000/")
mean_diff_10 <- vroom(file = "mean_diff_10_sim1000.csv", delim = ",", col_names = TRUE) %>%
mutate(Diff_Color = ifelse(Upper < 0, '<0',ifelse(Lower <=0 & Upper >=0, '0',ifelse(Lower >0, '>0', 'something else'))))
mean_diff_10_ab <- mean_diff_10 %>%
filter(Type == "Diff_AB", Diff_Color != '0') %>%
mutate(Abs_Val = abs(Mean_Diff))
p_epsilon_ve <- ggplot(data = mean_diff_10_ab, aes(x = exposure_penalty, y = vac_protect, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38"), name = 'Difference in Childhood Infections') +
xlab('Exposure Penalty') + ylab('Vaccine Effectiveness') +
theme(legend.position = 'none',
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank()
)
p_epsilon_waning <- ggplot(data = mean_diff_10_ab, aes(x = exposure_penalty, y = wane, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Exposure Penalty') + ylab('Waning') +
theme(legend.position = 'none',
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank()
)
p_epsilon_take <- ggplot(data = mean_diff_10_ab, aes(x = exposure_penalty, y = take, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Exposure Penalty') + ylab('Take') +
theme(legend.position = 'none',
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank()
)
p_epsilon_rho <- ggplot(data = mean_diff_10_ab, aes(x = exposure_penalty, y = rho, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Exposure Penalty') + ylab("Correlation of Vaccination") +
theme(legend.position = 'none',
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank()
)
p_epsilon_vaccov <- ggplot(data = mean_diff_10_ab, aes(x = exposure_penalty, y = vac_cov, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Exposure Penalty') + ylab("Vaccination Coverage") +
theme(legend.position = 'none',
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank()
)
p_ve_waning <- ggplot(data = mean_diff_10_ab, aes(x = vac_protect, y = wane, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Vaccine Effectiveness') + ylab('Waning') +
theme(legend.position = 'none',
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank()
)
p_ve_take <- ggplot(data = mean_diff_10_ab, aes(x = vac_protect, y = take, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Vaccine Effectiveness') + ylab('Take') +
theme(legend.position = 'none',
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank()
)
p_ve_rho <- ggplot(data = mean_diff_10_ab, aes(x = vac_protect, y = rho, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Vaccine Effectiveness') + ylab('Correlation of Vaccination') +
theme(legend.position = 'none',
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank()
)
p_ve_vaccov <- ggplot(data = mean_diff_10_ab, aes(x = vac_protect, y = vac_cov, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Vaccine Effectiveness') + ylab('Vaccination Coverage') +
theme(legend.position = 'none',
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank()
)
p_waning_take <- ggplot(data = mean_diff_10_ab, aes(x = wane, y = take, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Waning') + ylab('Vaccination Coverage') +
theme(legend.position = 'none',
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank()
)
p_waning_rho <- ggplot(data = mean_diff_10_ab, aes(x = wane, y = rho, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Waning') + ylab("Correlation of Vaccination") +
theme(legend.position = 'none',
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank()
)
p_waning_vaccov <- ggplot(data = mean_diff_10_ab, aes(x = wane, y = vac_cov, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Waning') + ylab("Vaccination Coverage") +
theme(legend.position = 'none',
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank()
)
p_take_rho <- ggplot(data = mean_diff_10_ab, aes(x = take, y = rho, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Take') + ylab("Correlation of Vaccination") +
theme(legend.position = 'none',
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank()
)
p_take_vaccov <- ggplot(data = mean_diff_10_ab, aes(x = take, y = vac_cov, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Take') + ylab("Vaccination Coverage") +
theme(legend.position = 'none',
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank()
)
p_rho_vaccov <- ggplot(data = mean_diff_10_ab, aes(x = rho, y = vac_cov, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab("Correlation of Vaccination") + ylab("Vaccination Coverage") +
theme(legend.position = 'none',
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank()
)
sm_figure1 <- plot_grid(p_epsilon_ve, p_epsilon_waning, p_epsilon_take,p_epsilon_vaccov, p_epsilon_rho,
p_ve_waning, p_ve_take, p_ve_rho, p_ve_vaccov, p_waning_take, p_waning_rho,
p_waning_vaccov, p_take_rho, p_take_vaccov, p_rho_vaccov,
labels = "AUTO", ncol = 3, align = 'v', axis = 'l')
legend_b <- get_legend(
p_epsilon_ve +
guides(color = guide_legend(nrow = 1)) +
theme(legend.position = "bottom")
)
sm_figure1 <- plot_grid(sm_figure1, legend_b, ncol = 1, rel_heights = c(1, .1))
#filename <- "~/Dropbox/Kylie/Projects/Morevac/figures/"
filename <- "C:/Users/kainslie/Dropbox/Kylie/Projects/Morevac/figures/"
#filename <- "~/Dropbox/Kylie/Presentations/MRC Symposium/figures/"
png(file = paste0(filename,"SuppMatFig1_sim1000.png"), width = 12, height = 16,
units = "in", pointsize = 8, res = 300)
sm_figure1
dev.off()
###########################################################
### Supplemental Figure 2 - all pairwaise scatter plots ###
###########################################################
# cutoff = 16
###########################################################
#banana_cream_16 <- banana_cream_pie_16 %>% filter(Type == "Diff_AB") %>% mutate(Abs_Val = abs(Mean_Diff))
setwd("C:/Users/kainslie/Dropbox/Kylie/Projects/Morevac/data/sim_data/cutoff16/sim1000/")
mean_diff_16 <- vroom(file = "mean_diff_16_sim1000.csv", delim = ",", col_names = TRUE) %>%
mutate(Diff_Color = ifelse(Upper < 0, '<0',ifelse(Lower <=0 & Upper >=0, '0',ifelse(Lower >0, '>0', 'something else'))))
# a) Scatter plot of difference between annual and no vaccination
mean_diff_16_ab <- mean_diff_16 %>%
filter(Type == "Diff_AB", Diff_Color != '0') %>%
mutate(Abs_Val = abs(Mean_Diff))
p_epsilon_ve2 <- ggplot(data = mean_diff_16_ab, aes(x = exposure_penalty, y = vac_protect, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38"), name = 'Difference in Childhood Infections') +
xlab('Exposure Penalty') + ylab('Vaccine Effectiveness') +
theme(legend.position = 'none',
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank()
)
p_epsilon_waning2 <- ggplot(data = mean_diff_16_ab, aes(x = exposure_penalty, y = wane, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Exposure Penalty') + ylab('Waning') +
theme(legend.position = 'none',
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank()
)
p_epsilon_take2 <- ggplot(data = mean_diff_16_ab, aes(x = exposure_penalty, y = take, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Exposure Penalty') + ylab('Take') +
theme(legend.position = 'none',
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank()
)
p_epsilon_rho2 <- ggplot(data = mean_diff_16_ab, aes(x = exposure_penalty, y = rho, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Exposure Penalty') + ylab("Correlation of Vaccination") +
theme(legend.position = 'none',
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank()
)
p_epsilon_vaccov2 <- ggplot(data = mean_diff_16_ab, aes(x = exposure_penalty, y = vac_cov, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Exposure Penalty') + ylab("Vaccination Coverage") +
theme(legend.position = 'none',
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank()
)
p_ve_waning2 <- ggplot(data = mean_diff_16_ab, aes(x = vac_protect, y = wane, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Vaccine Effectiveness') + ylab('Waning') +
theme(legend.position = 'none',
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank()
)
p_ve_take2 <- ggplot(data = mean_diff_16_ab, aes(x = vac_protect, y = take, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Vaccine Effectiveness') + ylab('Take') +
theme(legend.position = 'none',
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank()
)
p_ve_rho2 <- ggplot(data = mean_diff_16_ab, aes(x = vac_protect, y = rho, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Vaccine Effectiveness') + ylab('Correlation of Vaccination') +
theme(legend.position = 'none',
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank()
)
p_ve_vaccov2 <- ggplot(data = mean_diff_16_ab, aes(x = vac_protect, y = vac_cov, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Vaccine Effectiveness') + ylab('Vaccination Coverage') +
theme(legend.position = 'none',
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank()
)
p_waning_take2 <- ggplot(data = mean_diff_16_ab, aes(x = wane, y = take, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Waning') + ylab('Vaccination Coverage') +
theme(legend.position = 'none',
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank()
)
p_waning_rho2 <- ggplot(data = mean_diff_16_ab, aes(x = wane, y = rho, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Waning') + ylab("Correlation of Vaccination") +
theme(legend.position = 'none',
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank()
)
p_waning_vaccov2 <- ggplot(data = mean_diff_16_ab, aes(x = wane, y = vac_cov, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Waning') + ylab("Vaccination Coverage") +
theme(legend.position = 'none',
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank()
)
p_take_rho2 <- ggplot(data = mean_diff_16_ab, aes(x = take, y = rho, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Take') + ylab("Correlation of Vaccination") +
theme(legend.position = 'none',
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank()
)
p_take_vaccov2 <- ggplot(data = mean_diff_16_ab, aes(x = take, y = vac_cov, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab('Take') + ylab("Vaccination Coverage") +
theme(legend.position = 'none',
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank()
)
p_rho_vaccov2 <- ggplot(data = mean_diff_16_ab, aes(x = rho, y = vac_cov, color = Diff_Color)) +
geom_point(aes(size = Abs_Val), alpha = 0.7) +
scale_size_continuous(name = "|Difference|") +
scale_color_manual(values = c("#F8766D","#00BA38")) +
xlab("Correlation of Vaccination") + ylab("Vaccination Coverage") +
theme(legend.position = 'none',
panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank()
)
sm_figure2 <- plot_grid(p_epsilon_ve2, p_epsilon_waning2, p_epsilon_take2,p_epsilon_vaccov2, p_epsilon_rho2,
p_ve_waning2, p_ve_take2, p_ve_rho2, p_ve_vaccov2, p_waning_take2, p_waning_rho2,
p_waning_vaccov2, p_take_rho2, p_take_vaccov2, p_rho_vaccov2,
labels = "AUTO", ncol = 3, align = 'v', axis = 'l')
legend_b <- get_legend(
p_epsilon_ve2 +
guides(color = guide_legend(nrow = 1)) +
theme(legend.position = "bottom")
)
sm_figure2 <- plot_grid(sm_figure2, legend_b, ncol = 1, rel_heights = c(1, .1))
filename <- "C:/Users/kainslie/Dropbox/Kylie/Projects/Morevac/figures/"
png(file = paste0(filename,"SuppMatFig2_sim1000.png"), width = 12, height = 16,
units = "in", pointsize = 8, res = 300)
sm_figure2
dev.off()
###############################################################
### Supplemental Figure 3 - attack rates for time-varying beta
###############################################################
setwd("C:/Users/kainslie/Dropbox/Kylie/Projects/Morevac/data/sim_data/baseline/sim1000/time-varying_beta/")
mean_ar_baseline_tvb <- vroom(file = "mean_ar_baseline2_sim1000.csv", delim = ",", col_names = TRUE)
### AR for different values of epsilon
mean_ar_baseline_tvb2 <- mean_ar_baseline_tvb %>%
select(-c(n_sim, n_indiv, max_age, start_year, end_year, pandemic_beta, epidemic_beta)) %>%
filter(exposure_penalty %in% c(0, 0.01, 0.03, 0.05, 0.08, 0.1) & vac_protect == 0.7 & Param_Index != 18)
figure_s3 <- ggplot(data = mean_ar_baseline_tvb2, aes(x = Age, y = Mean_AR, colour= Vac_Strategy)) +
geom_line() +
geom_ribbon(aes(x=Age,ymin=Lower,ymax=Upper,linetype=NA, fill = Vac_Strategy),alpha=0.2) +
scale_y_continuous(limits = c(0, 0.2)) +
#scale_fill_discrete(breaks = c("Annual", "Biennial", "No Vaccination")) +
xlab("Age (years)") + ylab("Attack Rate") +
theme(panel.grid.major = element_blank(),
panel.grid.minor = element_blank(),
panel.background = element_blank(),
axis.line = element_line(colour = "black"),
legend.position = "bottom",
legend.title = element_blank(),
#legend.margin = margin(6, 6, 6, 6),
#legend.key = element_rect(fill = "white")
) +
facet_wrap(~exposure_penalty, nrow=2)
figure_s3
filename <- "C:/Users/kainslie/Dropbox/Kylie/Projects/Morevac/figures/"
png(file = paste0(filename,"figure_s3_sim1000.png"), width = 12, height = 8,
units = "in", pointsize = 8, res = 300)
figure_s3
dev.off()
###############################################################
### Supplemental Figure 4 - scatter plots for time-varying beta
###############################################################
### may not need these! ###
# a) annual vs. no vac
# b) annual vs. biennial
###################################
# banana_cream_pie <- vroom(file = "banana_cream_pie_baseline2.csv", delim = ",", col_names = TRUE) %>%
# mutate(Diff_Color = ifelse(Upper < 0, '<0',ifelse(Lower <=0 & Upper >=0, '0',ifelse(Lower >0, '>0', 'something else'))))
#
# # a) Scatter plot of difference between annual and no vaccination
# banana_hammock_an <- banana_cream_pie %>%
# filter(Type == "Diff_AN", Diff_Color != '0') %>%
# mutate(Abs_Val = abs(Mean_Diff))
#
# figure_s4a <- ggplot(data = banana_hammock_an, aes(x = exposure_penalty, y = vac_protect, color = Diff_Color)) +
# geom_point(aes(size = Abs_Val), alpha = 0.7) +
# scale_size_continuous(name = "|Difference|") +
# scale_color_manual(name = "Difference", values = c("#F8766D","#00BA38")) +
# xlab('Exposure Penalty') +
# ylab('Vaccine Effectiveness') +
# theme(legend.position = "bottom",
# panel.grid.major = element_blank(),
# panel.grid.minor = element_blank(),
# panel.background = element_blank(),
# axis.text=element_text(size=12),
# axis.title=element_text(size=14),
# legend.text = element_text(size=12),
# legend.title = element_text(size=12))
#
#
# # b) Scatter plot of difference between annual and biennial
# banana_hammock_ab <- banana_cream_pie %>%
# filter(Type == "Diff_AB", Diff_Color != '0') %>%
# mutate(Abs_Val = abs(Mean_Diff))
#
# figure_s4b <- ggplot(data = banana_hammock_ab, aes(x = exposure_penalty, y = vac_protect, color = Diff_Color)) +
# geom_point(aes(size = Abs_Val), alpha = 0.7) +
# scale_size_continuous(name = "|Difference|") +
# scale_color_manual(name = "Difference", values = c("#F8766D","#00BA38")) +
# xlab('Exposure Penalty') +
# ylab('Vaccine Effectiveness') +
# theme(legend.position = "bottom",
# panel.grid.major = element_blank(),
# panel.grid.minor = element_blank(),
# panel.background = element_blank(),
# axis.text=element_text(size=12),
# axis.title=element_text(size=14),
# legend.text = element_text(size=12),
# legend.title = element_text(size=12))
#
# figure_s4 <- plot_grid(figure_s4a, figure_s4b, labels = "AUTO", nrow = 1) # rel_heights = c(1,1.5)
#
# filename <- "C:/Users/kainslie/Dropbox/Kylie/Projects/Morevac/figures/"
# png(file = paste0(filename,"figure_s4_sim1000.png"), width = 13, height = 6,
# units = "in", pointsize = 8, res = 300)
# figure_s4
# dev.off()
# #######################################################
# ### Supplemental Figure 3 - bivariate scatter plots ###
# #######################################################
# # cutoff = 16
# # VE x exposure penalty
# #######################################################
# # c) cutoff = 16: scatter plots of all mean diff by exposure_penalty & vac_protect
# p3c1 <- ggplot(banana_hammock_16, aes(x = exposure_penalty, y = Mean_Diff, color = Diff_Color)) +
# geom_point() +
# geom_errorbar(aes(ymin = Lower, ymax = Upper)) +
# geom_hline(yintercept = 0, color = "black") +
# scale_color_manual(name = 'Difference', values = c("#F8766D","#00BA38", "#619CFF")) +
# xlab("Exposure Penalty") +
# ylab('Difference') +
# theme(legend.position = "none",
# panel.grid.major = element_blank(),
# panel.grid.minor = element_blank(),
# panel.background = element_blank(),
# axis.text=element_text(size=12),
# axis.title=element_text(size=14)) +
# geom_point(data = banana_hammock_zero_16, aes(x = exposure_penalty, y = Mean_Diff), alpha = 0.4) +
# geom_errorbar(data = banana_hammock_zero_16, aes(ymin = Lower, ymax = Upper), alpha = 0.4)
#
# p3c2 <- ggplot(banana_hammock_16, aes(x = vac_protect, y = Mean_Diff, color = Diff_Color)) +
# geom_point() +
# geom_errorbar(aes(ymin = Lower, ymax = Upper)) +
# geom_hline(yintercept = 0, color = "black") +
# scale_color_manual(name = 'Difference', values = c("#F8766D","#00BA38", "#619CFF")) +
# xlab("Vaccine Effectiveness") +
# ylab('Difference') +
# theme(legend.position = "none",
# panel.grid.major = element_blank(),
# panel.grid.minor = element_blank(),
# panel.background = element_blank(),
# axis.text=element_text(size=12),
# axis.title=element_text(size=14)) +
# geom_point(data = banana_hammock_zero_16, aes(x = vac_protect, y = Mean_Diff), alpha = 0.4) +
# geom_errorbar(data = banana_hammock_zero_16, aes(ymin = Lower, ymax = Upper), alpha = 0.4)
#
# p3c <- plot_grid(p3c1, p3c2, ncol = 1, align = 'v', axis = 'l')
#
# # d) cutoff = 16: scatter plot of vac_protect x exposure_penalty with only sig diff points
# p3d <- ggplot(data = banana_hammock_16, aes(x = exposure_penalty, y = vac_protect, color = Diff_Color)) +
# geom_point(aes(size = Abs_Val), alpha = 0.7) +
# scale_size_continuous(name = "|Difference|") +
# scale_color_manual(name = "Difference", values = c("#F8766D","#00BA38")) +
# xlab('Exposure Penalty') +
# ylab('VaccineEffectiveness') +
# theme(legend.position = "bottom",
# panel.grid.major = element_blank(),
# panel.grid.minor = element_blank(),
# panel.background = element_blank(),
# axis.text=element_text(size=12),
# axis.title=element_text(size=14),
# legend.text = element_text(size=12),
# legend.title = element_text(size=12))
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