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plot_coberturas.R
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plot_coberturas.R
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require(tidyverse)
require(geofacet)
###########################
end.of.epiweek <- function(x, end = 6) {
offset <- (end - 4) %% 7
num.x <- as.numeric(x)
return(x - (num.x %% 7) + offset + ifelse(num.x %% 7 > offset, 7, 0))
}
###########################
data_corte = as.Date("2021-09-01")
data_base = as.Date("2022-02-01")
data_base_texto <- format(data_base, format = "%d de %B de %Y")
distribuicao_etaria <- read.csv("dados/DistrEtaria2020.csv")
colnames(distribuicao_etaria)[1] <- "Idade"
distribuicao_etaria <- distribuicao_etaria[-1,]
rownames(distribuicao_etaria) <- NULL
distribuicao_etaria[2,-1] <- as.integer(distribuicao_etaria[2,-1] + distribuicao_etaria[3,-1]*2/5) # 5-11
distribuicao_etaria[3,-1] <- as.integer(distribuicao_etaria[3,-1]*3/5 + distribuicao_etaria[4,-1]*3/5) # 12-17
distribuicao_etaria[4,-1] <- as.integer(distribuicao_etaria[4,-1]*2/5) # 18-19
distribuicao_etaria$agegroup <- factor(c(1,2,3,4,4,4,rep(5:10, each = 2), 11))
de2 <- distribuicao_etaria %>%
select(-Idade) %>%
group_by(agegroup) %>%
summarise(across(everything(), sum)) %>%
gather(key = "UF", value = "total", -agegroup)
###
files <- list.files("output/doses_aplicadas")[!grepl("[1-9].csv", list.files("output/doses_aplicadas"))]
da <- data.frame()
for(i in files) {
state = substr(i,17,18)
print(state)
df <- data.frame(read.csv(paste0("output/doses_aplicadas/",i)), UF = state)
da <- rbind(da, df)
}
da$agegroup <- factor(da$agegroup)
da$doses <- factor(da$doses)
da$UF <- factor(da$UF)
da$data <- as.Date(da$data)
da2 <- da %>% left_join(de2, by = c("agegroup", "UF"))
### Total por Estado, vacina e dose
final = da %>%
as_tibble() %>%
drop_na(agegroup) %>%
group_by(UF, vacina, doses, agegroup) %>%
#group_by(agegroup, vacina, doses, n, UF) %>%
summarise(nn = sum(n, na.rm = T)) %>%
arrange(UF, vacina, doses, agegroup)
write_csv(final, file = "total_vacinas.csv")
### DOSE 1
d1 = da2 %>%
as_tibble() %>%
filter(doses == "D1") %>%
drop_na(agegroup) %>%
group_by(data, agegroup, n, UF) %>%
summarise(nn = sum(n, na.rm = T)/total) %>%
group_by(agegroup, UF) %>%
mutate(m = cumsum(nn)*100) %>%
arrange(UF, agegroup, data)
gd1 <- d1 %>%
ggplot(aes(x = data, y = m, color = agegroup)) +
geom_line() +
geom_hline(yintercept = 100, linetype = "dashed") +
facet_wrap(~UF, scale = "free_y") +
# facet_geo(~UF, grid = "br_states_grid1", scale = "free_y") +
theme_minimal() +
xlab("") + ylab("Cobertura (%)") +
scale_color_discrete("Faixa etária",
labels = c("0-4","5-11","12-17","18-29",
"30-39","40-49","50-59",
"60-69","70-79","80-89","90+")) +
scale_x_date(date_labels = "%b-%y", date_breaks = "2 months") +
theme(axis.text.x = element_text(angle = 270, hjust = 1)) +
labs(title = "Cobertura de Dose 1",
caption = paste0("Fonte: SI-PNI em ", data_base_texto, ".\nEstimativas populacionais das faixas etárias de 5 a 29 anos são aproximadas"))
#gd1
ggsave(gd1, file = "figuras/dose_1.png", width = 15, height = 10, dpi = 200)
###
gd1b <- d1 %>%
filter(data >= data_corte) %>%
mutate(week = end.of.epiweek(data)) %>%
ggplot(aes(x = week, y = n)) + #, color = agegroup)) + #, fill = agegroup)) +
geom_col() +
geom_hline(yintercept = 100, linetype = "dashed") +
facet_wrap(~UF, scale = "free_y") +
# facet_geo(~UF, grid = "br_states_grid1", scale = "free_y") +
theme_minimal() +
xlab("") + ylab("Cobertura (%)") +
#scale_fill_discrete("Faixa etária",
# labels = c("0-4","5-11","12-17","18-29",
# "30-39","40-49","50-59",
# "60-69","70-79","80-89","90+")) +
# scale_color_discrete(show.legend = FALSE) +
scale_x_date(date_labels = "%b-%y", date_breaks = "2 months") +
theme(axis.text.x = element_text(angle = 270, hjust = 1)) +
labs(title = "Novas aplicações de Dose 1 (semanal)",
caption = paste0("Fonte: SI-PNI em ", data_base_texto))
#gd1
ggsave(gd1b, file = "figuras/dose_1_diario.png", width = 15, height = 10, dpi = 200)
### DOSE 2
d2 = da2 %>%
as_tibble() %>%
filter(doses == "D2") %>%
drop_na(agegroup) %>%
group_by(data, agegroup, n, UF) %>%
summarise(nn = sum(n, na.rm = T)/total) %>%
group_by(agegroup, UF) %>%
mutate(m = cumsum(nn)*100) %>%
arrange(UF, agegroup, data)
gd2 <- d2 %>%
ggplot(aes(x = data, y = m, color = agegroup)) +
geom_line() +
geom_hline(yintercept = 100, linetype = "dashed") +
facet_wrap(~UF, scale = "free_y") +
# facet_geo(~UF, grid = "br_states_grid1", scale = "free_y") +
theme_minimal() +
xlab("") + ylab("Cobertura (%)") +
scale_color_discrete("Faixa etária",
labels = c("0-4","5-11","12-17","18-29",
"30-39","40-49","50-59",
"60-69","70-79","80-89","90+")) +
scale_x_date(date_labels = "%b-%y", date_breaks = "2 months") +
theme(axis.text.x = element_text(angle = 270, hjust = 1)) +
labs(title = "Cobertura de Dose 2",
caption = paste0("Fonte: SI-PNI em ", data_base_texto, ".\nEstimativas populacionais das faixas etárias de 5 a 29 anos são aproximadas"))
#gd2
ggsave(gd2, file = "figuras/dose_2.png", width = 15, height = 10, dpi = 200)
###
gd2b <- d2 %>%
filter(data >= data_corte) %>%
mutate(week = end.of.epiweek(data)) %>%
ggplot(aes(x = week, y = n)) + #, color = agegroup)) + #, fill = agegroup)) +
geom_col() +
geom_hline(yintercept = 100, linetype = "dashed") +
facet_wrap(~UF, scale = "free_y") +
# facet_geo(~UF, grid = "br_states_grid1", scale = "free_y") +
theme_minimal() +
xlab("") + ylab("Cobertura (%)") +
#scale_fill_discrete("Faixa etária",
# labels = c("0-4","5-11","12-17","18-29",
# "30-39","40-49","50-59",
# "60-69","70-79","80-89","90+")) +
# scale_color_discrete(show.legend = FALSE) +
scale_x_date(date_labels = "%b-%y", date_breaks = "2 months") +
theme(axis.text.x = element_text(angle = 270, hjust = 1)) +
labs(title = "Novas aplicações de Dose 2 (semanal)",
caption = paste0("Fonte: SI-PNI em ", data_base_texto))
#gd1
ggsave(gd2b, file = "figuras/dose_2_diario.png", width = 15, height = 10, dpi = 200)
### DOSE REFORÇO
dr = da2 %>%
as_tibble() %>%
filter(doses == "R") %>%
drop_na(agegroup) %>%
group_by(data, agegroup, n, UF) %>%
summarise(nn = sum(n, na.rm = T)/total) %>%
group_by(agegroup, UF) %>%
mutate(m = cumsum(nn)*100) %>%
arrange(UF, agegroup, data)
gdr <- dr %>%
ggplot(aes(x = data, y = m, color = agegroup)) +
geom_line() +
geom_hline(yintercept = 100, linetype = "dashed") +
facet_wrap(~UF, scale = "free_y") +
# facet_geo(~UF, grid = "br_states_grid1", scale = "free_y") +
theme_minimal() +
xlab("") + ylab("Cobertura (%)") +
scale_color_discrete("Faixa etária",
labels = c("0-4","5-11","12-17","18-29",
"30-39","40-49","50-59",
"60-69","70-79","80-89","90+")) +
scale_x_date(date_labels = "%b-%y", date_breaks = "2 months") +
theme(axis.text.x = element_text(angle = 270, hjust = 1)) +
labs(title = "Cobertura de doses de reforço",
caption = paste0("Fonte: SI-PNI em ", data_base_texto))
#gdr
ggsave(gdr, file = "figuras/dose_reforco.png", width = 15, height = 10, dpi = 200)
###
grb <- dr %>%
filter(data >= data_corte) %>%
mutate(week = end.of.epiweek(data)) %>%
ggplot(aes(x = week, y = n)) + #, color = agegroup)) + #, fill = agegroup)) +
geom_col() +
geom_hline(yintercept = 100, linetype = "dashed") +
facet_wrap(~UF, scale = "free_y") +
# facet_geo(~UF, grid = "br_states_grid1", scale = "free_y") +
theme_minimal() +
xlab("") + ylab("Cobertura (%)") +
#scale_fill_discrete("Faixa etária",
# labels = c("0-4","5-11","12-17","18-29",
# "30-39","40-49","50-59",
# "60-69","70-79","80-89","90+")) +
# scale_color_discrete(show.legend = FALSE) +
scale_x_date(date_labels = "%b-%y", date_breaks = "2 months") +
theme(axis.text.x = element_text(angle = 270, hjust = 1)) +
labs(title = "Novas aplicações de doses de reforço (semanal)",
caption = paste0("Fonte: SI-PNI em ", data_base_texto, ".\nEstimativas populacionais das faixas etárias de 5 a 29 anos são aproximadas"))
#gd1
ggsave(grb, file = "figuras/dose_reforci_diario.png", width = 15, height = 10, dpi = 200)