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master_utils.R
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master_utils.R
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# Utility functions that act as wrappers around
# the utilities from other utils files
source("import_utils.R")
source("dose_utils.R")
source("optim_utils.R")
source("final_size_utils.R")
source("NGM_utils.R")
calc_targets <- function(params,
targets = c("Infections", "Hospitalizations", "Deaths"),
strategies = c("Uniform", "Vulnerable", "Transmitters"),
target_coverages = seq(0, 1.0, 0.2),
vacc_program = list(
"vacc_types" = c("Pfizer", "Sinovac"),
"vacc_percs" = c(20, 80)
),
eligibility_cutoff = 15,
# include_children = FALSE,
uptake = 1.0,
cutoff = 60) {
out <- expand.grid(
Strategy = strategies,
Vaccine = list("any vacc" = c("any vacc")),
Coverage = target_coverages
)
out$Infections <- rep(NA, nrow(out))
out$Hospitalizations <- rep(NA, nrow(out))
out$Deaths <- rep(NA, nrow(out))
out_lower <- out
out_upper <- out
params_central <- params
params_lower <- params
params_upper <- params
for (i in 1:nrow(out)) {
# Calculate age-specific vaccination coverage
if (eligibility_cutoff == 15) {
vacc_prop <- calc_age_specific_coverage_over_15(
target_coverage = out$Coverage[i],
params = params,
strategy = out$Strategy[i],
uptake = uptake
)
} else if (eligibility_cutoff == 10) {
vacc_prop <- calc_age_specific_coverage_over_10(
target_coverage = out$Coverage[i],
params = params,
strategy = out$Strategy[i],
uptake = uptake
)
} else if (eligibility_cutoff == 5) {
vacc_prop <- calc_age_specific_coverage_over_5(
target_coverage = out$Coverage[i],
params = params,
strategy = out$Strategy[i],
uptake = uptake
)
}
# if (include_children) {
# vacc_prop = calc_age_specific_coverage_children_included(
# target_coverage = out$Coverage[i],
# params = params,
# strategy = out$Strategy[i],
# uptake = uptake
# )
# } else{
# vacc_prop = calc_age_specific_coverage(
# target_coverage = out$Coverage[i],
# params = params,
# strategy = out$Strategy[i],
# uptake = uptake
# )
# }
# Update the vaccine efficacy given the current vaccine combination
params_central$efficacy <- import_mixed_efficacy_data(
params$strain,
vacc_program
)
# if(vacc_comb[1] %in% c("Pfizer", "AstraZeneca") & vacc_comb[2] %in% c("Pfizer", "AstraZeneca")){
# params_lower$efficacy = import_efficacy_data(
# params$strain,
# vaccine_1 = paste(vacc_comb[1], "(lower)", sep =
# " "),
# vaccine_2 = paste(vacc_comb[2], "(lower)", sep =
# " ")
# )
#
# params_upper$efficacy = import_efficacy_data(
# params$strain,
# vaccine_1 = paste(vacc_comb[1], "(upper)", sep =
# " "),
# vaccine_2 = paste(vacc_comb[2], "(upper)", sep =
# " ")
# )
# } else {
# params_lower$efficacy = import_efficacy_data(params$strain,
# vaccine_1 = vacc_comb[1],
# vaccine_2 = vacc_comb[2])
# params_upper$efficacy = import_efficacy_data(params$strain,
# vaccine_1 = vacc_comb[1],
# vaccine_2 = vacc_comb[2])
# }
params_lower <- get_params(params$country,
R0 = params$R0 - 1,
vacc_program = vacc_program,
seropositivity = params$seropositivity,
strain = params$strain
)
params_upper <- get_params(params$country,
R0 = params$R0 + 1,
vacc_program = vacc_program,
seropositivity = params$seropositivity,
strain = params$strain
)
params_lower$efficacy <- params_central$efficacy
params_upper$efficacy <- params_central$efficacy
# Calculate the age-specific infections / hospitalizations / deaths
final_burden <- calc_final_burden(params_central, vacc_prop)
out$Infections[i] <- sum(final_burden$infections) * 1e5 / sum(params$population_size)
out$Hospitalizations[i] <- sum(final_burden$hospitalizations) * 1e5 / sum(params$population_size)
out$Deaths[i] <- sum(final_burden$deaths) * 1e5 / sum(params$population_size)
final_burden_lower <- calc_final_burden(params_lower, vacc_prop)
out_lower$Infections[i] <- sum(final_burden_lower$infections) * 1e5 / sum(params$population_size)
out_lower$Hospitalizations[i] <- sum(final_burden_lower$hospitalizations) * 1e5 / sum(params$population_size)
out_lower$Deaths[i] <- sum(final_burden_lower$deaths) * 1e5 / sum(params$population_size)
final_burden_upper <- calc_final_burden(params_upper, vacc_prop)
out_upper$Infections[i] <- sum(final_burden_upper$infections) * 1e5 / sum(params$population_size)
out_upper$Hospitalizations[i] <- sum(final_burden_upper$hospitalizations) * 1e5 / sum(params$population_size)
out_upper$Deaths[i] <- sum(final_burden_upper$deaths) * 1e5 / sum(params$population_size)
}
# Melt, and then stitch together lower, central and upper estimates
out <- out %>%
dplyr::select(-Hospitalizations) %>%
reshape2::melt(
id.vars = c("Strategy", "Vaccine", "Coverage"),
variable.name = "Target"
)
out_lower <- out_lower %>%
dplyr::select(-Hospitalizations) %>%
reshape2::melt(
id.vars = c("Strategy", "Vaccine", "Coverage"),
variable.name = "Target"
)
out_upper <- out_upper %>%
dplyr::select(-Hospitalizations) %>%
reshape2::melt(
id.vars = c("Strategy", "Vaccine", "Coverage"),
variable.name = "Target"
)
out$lower <- out_lower$value
out$upper <- out_upper$value
return(out)
}
calc_target_breakdown <- function(params,
target = "Deaths",
strategies = c("Uniform", "Vulnerable", "Transmitters"),
target_coverages = seq(0, 1.0, 0.2),
vaccine_combination = c("BNT162b2", "ChAdOx1"),
eligibility_cutoff = 15,
# include_children = FALSE,
uptake = 1.0,
cutoff = 60) {
out <- expand.grid(
Strategy = strategies,
Coverage = target_coverages
)
out$Unvaccinated <- rep(NA, nrow(out))
out$Vaccinated <- rep(NA, nrow(out))
for (i in 1:nrow(out)) {
# Calculate age-specific vaccination coverage
if (eligibility_cutoff == 15) {
vacc_prop <- calc_age_specific_coverage_over_15(
target_coverage = out$Coverage[i],
params = params,
strategy = out$Strategy[i],
uptake = uptake
)
} else if (eligibility_cutoff == 10) {
vacc_prop <- calc_age_specific_coverage_over_10(
target_coverage = out$Coverage[i],
params = params,
strategy = out$Strategy[i],
uptake = uptake
)
} else if (eligibility_cutoff == 5) {
vacc_prop <- calc_age_specific_coverage_over_5(
target_coverage = out$Coverage[i],
params = params,
strategy = out$Strategy[i],
uptake = uptake
)
}
# if (include_children) {
# vacc_prop = calc_age_specific_coverage_children_included(
# target_coverage = out$Coverage[i],
# params = params,
# strategy = out$Strategy[i],
# uptake = uptake
# )
# } else{
# vacc_prop = calc_age_specific_coverage(
# target_coverage = out$Coverage[i],
# params = params,
# strategy = out$Strategy[i],
# uptake = uptake
# )
# }
# Update the vaccine efficacy given the current vaccine combination
params$efficacy <- import_efficacy_data(params$strain,
vaccine_1 = vaccine_combination[1],
vaccine_2 = vaccine_combination[2],
cutoff = cutoff
)
# Calculate the age-specific infections / hospitalizations / deaths
final_burden <- calc_final_burden(params, vacc_prop)
out$Unvaccinated[i] <- sum(final_burden$deaths[1:16])
out$Vaccinated[i] <- sum(final_burden$deaths[17:32])
}
# Melt, and then stitch together lower, central and upper estimates
out <- out %>%
reshape2::melt(
id.vars = c("Strategy", "Coverage"),
variable.name = "Group"
)
return(out)
}
plot_targets <- function(out, l1 = NA, l2 = NA) {
plt <- out %>%
mutate(
value = if_else(value < 0, 0, value),
lower = if_else(lower < 0, 0, lower),
upper = if_else(upper < 0, 0, upper)
) %>%
ggplot2::ggplot(aes(
x = Coverage,
y = value,
col = Strategy,
fill = Strategy
)) +
geom_line(lwd = 1) +
geom_ribbon(aes(ymin = lower, ymax = upper),
alpha = 0.1,
colour = NA
) +
# facet_grid(Target ~ Vaccine, scales = "free") +
facet_grid(Target ~ ., scales = "free") +
ylab("Cases per 100,000 population") +
xlab("Target Coverage") +
scale_x_continuous(
label = scales::percent,
breaks = seq(0, 1, by = 0.2),
limits = c(0, 1)
) +
theme_bw(base_size = 18) +
theme(axis.text.x = element_text(angle = -90, vjust = 0.5)) +
geom_vline(col = "red", xintercept = l1, lty = "dashed") +
geom_vline(col = "red", xintercept = l2, lty = "dashed") +
expand_limits(y = c(0, 100))
print(plt)
}
plot_breakdown <- function(out, target = "Deaths") {
out$Coverage <- factor(paste(as.integer(out$Coverage * 100), "%", sep = ""),
levels = c("0%", "20%", "40%", "60%", "80%", "100%")
)
plt <- ggplot2::ggplot(out, aes(x = Coverage, y = value, fill = Group)) +
geom_col() +
ylab(paste("Total", target)) +
xlab("Target Coverage") +
facet_grid(. ~ Strategy) +
scale_fill_manual(values = c("darkred", "red")) +
# scale_x_continuous(
# label = scales::percent,
# breaks = seq(0, 1, by = 0.2),
# limits = c(0, 1)
# ) +
theme(
panel.background = element_rect(fill = "white", colour = "white"),
panel.grid.major = element_line(colour = "grey90"),
panel.grid.minor = element_line(colour = "grey90"),
panel.grid.major.x = element_blank(),
axis.line = element_line(size = 0.4, colour = "grey10"),
text = element_text(size = 12, family = "serif"),
legend.key = element_rect(fill = "white", colour = "white"),
strip.background = element_rect(fill = "white"),
strip.text = element_text(size = 12, colour = "black"),
panel.spacing = unit(1, "lines")
)
print(plt)
}
calc_targets_ages <- function(params,
targets = c("Infections", "Hospitalizations", "Deaths"),
strategies = c("Uniform", "Vulnerable", "Transmitters"),
target_coverages = seq(0, 1.0, 0.2),
vacc_program = list(
"vacc_types" = c("Pfizer", "Sinovac"),
"vacc_percs" = c(20, 80)
),
eligibility_cutoff = 15,
# include_children = FALSE,
uptake = 1.0,
cutoff = 60) {
out <- expand.grid(
Strategy = strategies,
Vaccine = list("any vacc" = c("any vacc")),
Coverage = target_coverages
)
out$Infections <- rep(NA, nrow(out))
out$Hospitalizations <- rep(NA, nrow(out))
out$Deaths <- rep(NA, nrow(out))
out_lower <- out
out_upper <- out
params_central <- params
params_lower <- params
params_upper <- params
everything <- map(
1:nrow(out),
function(x) {
# for (i in 1:nrow(out)) {
# Calculate age-specific vaccination coverage
if (eligibility_cutoff == 15) {
vacc_prop <- calc_age_specific_coverage_over_15(
target_coverage = out$Coverage[x],
params = params,
strategy = out$Strategy[x],
uptake = uptake
)
} else if (eligibility_cutoff == 10) {
vacc_prop <- calc_age_specific_coverage_over_10(
target_coverage = out$Coverage[x],
params = params,
strategy = out$Strategy[x],
uptake = uptake
)
} else if (eligibility_cutoff == 5) {
vacc_prop <- calc_age_specific_coverage_over_5(
target_coverage = out$Coverage[x],
params = params,
strategy = out$Strategy[x],
uptake = uptake
)
}
# if (include_children) {
# vacc_prop = calc_age_specific_coverage_children_included(
# target_coverage = out$Coverage[x],
# params = params,
# strategy = out$Strategy[x],
# uptake = uptake
# )
# } else{
# vacc_prop = calc_age_specific_coverage(
# target_coverage = out$Coverage[x],
# params = params,
# strategy = out$Strategy[x],
# uptake = uptake
# )
# }
# Update the vaccine efficacy given the current vaccine combination
params_central$efficacy <- import_mixed_efficacy_data(params$strain,
vacc_program = vacc_program
)
# if(vacc_comb[1] %in% c("Pfizer", "AstraZeneca") & vacc_comb[2] %in% c("Pfizer", "AstraZeneca")){
# params_lower$efficacy = import_efficacy_data(
# params$strain,
# vaccine_1 = paste(vacc_comb[1], "(lower)", sep =
# " "),
# vaccine_2 = paste(vacc_comb[2], "(lower)", sep =
# " ")
# )
#
# params_upper$efficacy = import_efficacy_data(
# params$strain,
# vaccine_1 = paste(vacc_comb[1], "(upper)", sep =
# " "),
# vaccine_2 = paste(vacc_comb[2], "(upper)", sep =
# " ")
# )
# } else {
# params_lower$efficacy = import_efficacy_data(params$strain,
# vaccine_1 = vacc_comb[1],
# vaccine_2 = vacc_comb[2])
# params_upper$efficacy = import_efficacy_data(params$strain,
# vaccine_1 = vacc_comb[1],
# vaccine_2 = vacc_comb[2])
# }
# params_central = get_params(params$country,R0 = params$R0,
# vaccine_1 = vacc_comb[1],
# vaccine_2 = vacc_comb[2],
# seropositivity = params$seropositivity,
# strain = params$strain)
#
params_lower <- get_params(params$country,
R0 = params$R0 - 1,
vacc_program = vacc_program,
seropositivity = params$seropositivity,
strain = params$strain
)
params_upper <- get_params(params$country,
R0 = params$R0 + 1,
vacc_program = vacc_program,
seropositivity = params$seropositivity,
strain = params$strain
)
params_lower$efficacy <- params_central$efficacy
params_upper$efficacy <- params_central$efficacy
# Calculate the age-specific infections / hospitalizations / deaths
final_burden <- calc_final_burden_tibble(params_central, vacc_prop)
#
# out$Infections[i] = sum(final_burden$infections) * 1e5 / sum(params$population_size)
# out$Hospitalizations[i] = sum(final_burden$hospitalizations) * 1e5 / sum(params$population_size)
# out$Deaths[i] = sum(final_burden$deaths) * 1e5 / sum(params$population_size)
#
final_burden_lower <- calc_final_burden_tibble(params_lower, vacc_prop)
#
# out_lower$Infections[i] = sum(final_burden_lower$infections) * 1e5 / sum(params$population_size)
# out_lower$Hospitalizations[i] = sum(final_burden_lower$hospitalizations) * 1e5 / sum(params$population_size)
# out_lower$Deaths[i] = sum(final_burden_lower$deaths) * 1e5 / sum(params$population_size)
#
final_burden_upper <- calc_final_burden_tibble(params_upper, vacc_prop)
#
# out_upper$Infections[i] = sum(final_burden_upper$infections) * 1e5 / sum(params$population_size)
# out_upper$Hospitalizations[i] = sum(final_burden_upper$hospitalizations) * 1e5 / sum(params$population_size)
# out_upper$Deaths[i] = sum(final_burden_upper$deaths) * 1e5 / sum(params$population_size)
#
final_burden$interval <- "mean"
final_burden_lower$interval <- "lower"
final_burden_upper$interval <- "upper"
fb_comb <- bind_rows(
final_burden,
final_burden_lower,
final_burden_upper
)
fb_comb$coverage <- out$Coverage[x]
fb_comb$strategy <- out$Strategy[x]
fb_comb$vaccine <- out$Vaccine[x]
return(fb_comb)
}
)
#
# # Melt, and then stitch together lower, central and upper estimates
# out = out %>%
# dplyr::select(-Hospitalizations) %>%
# reshape2::melt(id.vars = c("Strategy", "Vaccine", "Coverage"),
# variable.name = "Target")
# out_lower = out_lower %>%
# dplyr::select(-Hospitalizations) %>%
# reshape2::melt(id.vars = c("Strategy", "Vaccine", "Coverage"),
# variable.name = "Target")
# out_upper = out_upper %>%
# dplyr::select(-Hospitalizations) %>%
# reshape2::melt(id.vars = c("Strategy", "Vaccine", "Coverage"),
# variable.name = "Target")
#
# out$lower = out_lower$value
# out$upper = out_upper$value
#
# return(out)
return(do.call(bind_rows, everything))
}
facet_labeller <- function(variable, value) {
if (variable == "coverage") {
return(paste(value * 100, "% coverage", sep = ""))
} else {
return(as.character(value))
}
}
get_default_vacc_perc <- function(n, i) {
round_share <- floor(100. / n)
if (i > 1) {
return(round_share)
} else {
return(100 - round_share * (n - 1))
}
}
make_info_button <- function(name) {
text_path <- paste0("./info_buttons/", name, ".Rmd")
dropdownButton(
includeMarkdown(text_path),
# tags$h3("Text here"),
size = "xs",
circle = TRUE, status = "primary",
icon = icon("info"),
width = "25vw"
)
}