R/den_epichannel.R
In fdzul/boldenr: boldenr: a package designed to generate of Dengue Bulletin of Veracruz state
Defines functions
den_epichannel
Documented in
den_epichannel
#' dengue epidemiological channel
#'
#' den_epichannel generate the dengue epidemiological channel at level state, jurisdiction, municipality and locality.
#'
#' @param x is de dataset with dengue cases percentil.
#' @param y is the dengue dataset the current and last year.
#' @param edo is string indicating the state name.
#' @param jur is string indicating the jurisdiction name.
#' @param mpo is string indicating the municipality name.
#' @param loc is string indicating the locality name.
#' @param current_year is current year dengue dataset.
#' @param last_year is current year dengue dataset.
#' @param x_epi is the x position of the epidemic text.
#' @param y_epi is the y position of the epidemic text.
#' @param x_alerta is the x position of the alert text.
#' @param y_alerta is the y position of the alert text.
#' @param x_seg is the x position of the security text.
#' @param y_seg is the x position of the security text.
#' @param x_exito is the x position of the success text.
#' @param y_exito is the x position of the success text.
#'
#' @author Felipe Antonio Dzul Manzanilla \email{felipe.dzul.m@gmail.com}
#'
#' @return a ggplot object.
#' @export
#'
#'@details if both jur and loc is NULL the function generate the dengue epidemiological channel of state, else only loc is NULL and jur provide the name of jurisdiction then generate the epidemiological channel at level jurisdiction.
#'
#' @examples
den_epichannel <- function(x, y,
edo, jur, mpo, loc,
current_year, last_year,
x_epi, y_epi,
x_alerta,y_alerta,
x_seg, y_seg,
x_exito, y_exito
){
if(is.null(jur)){
x <- x %>%
dplyr::mutate(DES_EDO_RES = stringr::str_replace_all(string = DES_EDO_RES,
pattern = " ",
repl = " ")) %>%
dplyr::filter(DES_EDO_RES %in% c(edo))
z1 <- y %>%
dplyr::filter(!DES_EDO_RES %in% c("OTROS PAISES",
"OTROS PAISES DE LATINOAMERICA",
"ESTADOS UNIDOS DE NORTEAMERICA")) %>%
dplyr::filter(DES_DIAG_FINAL %in% c("DENGUE CON SIGNOS DE ALARMA",
"DENGUE GRAVE",
"DENGUE NO GRAVE",
"FIEBRE HEMORRAGICA POR DENGUE",
"FIEBRE POR DENGUE")) %>%
dplyr::mutate(DES_EDO_RES = stringr::str_replace_all(string = DES_EDO_RES,
pattern = " ",
repl = " ")) %>%
dplyr::filter(DES_EDO_RES == edo) %>%
dplyr::filter(ANO == current_year) %>%
dplyr::group_by(SEM) %>%
dplyr::summarise(n = dplyr::n(), .groups = "drop")
z2 <- y %>%
dplyr::filter(!DES_EDO_RES %in% c("OTROS PAISES",
"OTROS PAISES DE LATINOAMERICA",
"ESTADOS UNIDOS DE NORTEAMERICA")) %>%
dplyr::filter(DES_DIAG_FINAL %in% c("DENGUE CON SIGNOS DE ALARMA",
"DENGUE GRAVE",
"DENGUE NO GRAVE",
"FIEBRE HEMORRAGICA POR DENGUE",
"FIEBRE POR DENGUE")) %>%
dplyr::mutate(DES_EDO_RES = stringr::str_replace_all(string = DES_EDO_RES,
pattern = " ",
repl = " ")) %>%
dplyr::filter(DES_EDO_RES == edo) %>%
dplyr::filter(ANO == last_year) %>%
dplyr::group_by(SEM) %>%
dplyr::summarise(n = dplyr::n(), .groups = "drop")
ggplot2::ggplot(data = x,
ggplot2::aes(x = SEM)) +
ggplot2::geom_area(ggplot2::aes(y = q75),
col = "black",
size = 0.8,
fill = "#F44B1FFF",
alpha = 1) +
ggplot2::theme_classic() +
ggplot2::geom_area(ggplot2::aes(y = q50),
col = "white",
size = 0.8,
fill = "#FF9000FF",
alpha = 1) +
ggplot2::geom_area(ggplot2::aes(y = q25),
col = "white",
size = .8,
fill = "#00F293FF",
alpha = .8) +
ggplot2::ylab("Casos") +
ggplot2::xlab("Semanas epidemiológicas") +
ggplot2::annotate("text",
label = "Epidémico",
x = x_epi,
y = y_epi,
size = 6,
colour = "black") +
ggplot2::annotate("text",
label = "Alerta",
x = x_alerta,
y = y_alerta,
size = 6,
colour = "black") +
ggplot2::annotate("text",
label = "Seguridad",
x = x_seg,
y = y_seg,
size = 6,
colour = "black") +
ggplot2::annotate("text",
label = "Éxito",
x = x_exito,
y = y_exito,
size = 6,
colour = "black") +
ggplot2::scale_x_continuous(breaks = seq(from = 1,
to = 52,
by = 5),
limits = c(1,52)) +
ggplot2::geom_line(data = z1,
ggplot2::aes(x = SEM, y = n),
alpha = 0.5,
size = 1.5,
colour = "grey") +
ggplot2::geom_point(data = z1,
ggplot2::aes(x = SEM, y = n),
colour = "red",
shape = 21,
alpha = 0.5,
fill = "black",
stroke = 2) +
ggplot2::geom_line(data = z2,
ggplot2::aes(x = SEM, y = n),
#alpha = 0.5,s
size = 1.5,
colour = "black") +
ggplot2::geom_point(data = z2,
ggplot2::aes(x = SEM, y = n),
colour = "white",
shape = 21,
alpha = 0.5,
fill = "red",
stroke = 2)
} else{
if(is.null(mpo)){
x <- x %>%
dplyr::mutate(DES_EDO_RES = stringr::str_replace_all(string = DES_EDO_RES,
pattern = " ",
repl = " "),
DES_JUR_RES = stringr::str_replace_all(string = DES_JUR_RES,
pattern = " ",
repl = " ")) %>%
dplyr::filter(DES_EDO_RES %in% c(edo) &
DES_JUR_RES %in% c(jur))
z1 <- y %>%
dplyr::filter(!DES_EDO_RES %in% c("OTROS PAISES",
"OTROS PAISES DE LATINOAMERICA",
"ESTADOS UNIDOS DE NORTEAMERICA")) %>%
dplyr::filter(DES_DIAG_FINAL %in% c("DENGUE CON SIGNOS DE ALARMA",
"DENGUE GRAVE",
"DENGUE NO GRAVE",
"FIEBRE HEMORRAGICA POR DENGUE",
"FIEBRE POR DENGUE")) %>%
dplyr::mutate(DES_EDO_RES = stringr::str_replace_all(string = DES_EDO_RES,
pattern = " ",
repl = " "),
DES_JUR_RES = stringr::str_replace_all(string = DES_JUR_RES,
pattern = " ",
repl = " ")) %>%
dplyr::filter(DES_EDO_RES %in% edo &
DES_JUR_RES %in% c(jur)) %>%
dplyr::filter(ANO == current_year) %>%
dplyr::group_by(SEM) %>%
dplyr::summarise(n = dplyr::n(), .groups = "drop")
z2 <- y %>%
dplyr::filter(!DES_EDO_RES %in% c("OTROS PAISES",
"OTROS PAISES DE LATINOAMERICA",
"ESTADOS UNIDOS DE NORTEAMERICA")) %>%
dplyr::filter(DES_DIAG_FINAL %in% c("DENGUE CON SIGNOS DE ALARMA",
"DENGUE GRAVE",
"DENGUE NO GRAVE",
"FIEBRE HEMORRAGICA POR DENGUE",
"FIEBRE POR DENGUE")) %>%
dplyr::mutate(DES_EDO_RES = stringr::str_replace_all(string = DES_EDO_RES,
pattern = " ",
repl = " "),
DES_JUR_RES = stringr::str_replace_all(string = DES_JUR_RES,
pattern = " ",
repl = " ")) %>%
dplyr::filter(DES_EDO_RES %in% edo &
DES_JUR_RES %in% c(jur)) %>%
dplyr::filter(ANO == last_year) %>%
dplyr::group_by(SEM) %>%
dplyr::summarise(n = dplyr::n(), .groups = "drop")
} else {
if(is.null(loc)){
x <- x %>%
dplyr::mutate(DES_EDO_RES = stringr::str_replace_all(string = DES_EDO_RES,
pattern = " ",
repl = " "),
DES_MPO_RES = stringr::str_replace_all(string = DES_MPO_RES,
pattern = " ",
repl = " ")) %>%
dplyr::filter(DES_EDO_RES %in% c(edo) &
DES_MPO_RES %in% c(mpo))
z1 <- y %>%
dplyr::filter(!DES_EDO_RES %in% c("OTROS PAISES",
"OTROS PAISES DE LATINOAMERICA",
"ESTADOS UNIDOS DE NORTEAMERICA")) %>%
dplyr::filter(DES_DIAG_FINAL %in% c("DENGUE CON SIGNOS DE ALARMA",
"DENGUE GRAVE",
"DENGUE NO GRAVE",
"FIEBRE HEMORRAGICA POR DENGUE",
"FIEBRE POR DENGUE")) %>%
dplyr::mutate(DES_EDO_RES = stringr::str_replace_all(string = DES_EDO_RES,
pattern = " ",
repl = " "),
DES_MPO_RES = stringr::str_replace_all(string = DES_MPO_RES,
pattern = " ",
repl = " ")) %>%
dplyr::filter(DES_EDO_RES %in% edo &
DES_MPO_RES %in% c(mpo)) %>%
dplyr::filter(ANO == current_year) %>%
dplyr::group_by(SEM) %>%
dplyr::summarise(n = dplyr::n(), .groups = "drop")
z2 <- y %>%
dplyr::filter(!DES_EDO_RES %in% c("OTROS PAISES",
"OTROS PAISES DE LATINOAMERICA",
"ESTADOS UNIDOS DE NORTEAMERICA")) %>%
dplyr::filter(DES_DIAG_FINAL %in% c("DENGUE CON SIGNOS DE ALARMA",
"DENGUE GRAVE",
"DENGUE NO GRAVE",
"FIEBRE HEMORRAGICA POR DENGUE",
"FIEBRE POR DENGUE")) %>%
dplyr::mutate(DES_EDO_RES = stringr::str_replace_all(string = DES_EDO_RES,
pattern = " ",
repl = " "),
DES_MPO_RES = stringr::str_replace_all(string = DES_MPO_RES,
pattern = " ",
repl = " ")) %>%
dplyr::filter(DES_EDO_RES %in% edo &
DES_MPO_RES %in% c(mpo)) %>%
dplyr::filter(ANO == last_year) %>%
dplyr::group_by(SEM) %>%
dplyr::summarise(n = dplyr::n(), .groups = "drop")
} else {
x <- x %>%
dplyr::mutate(DES_EDO_RES = stringr::str_replace_all(string = DES_EDO_RES,
pattern = " ",
repl = " "),
DES_LOC_RES = stringr::str_replace_all(string = DES_LOC_RES,
pattern = " ",
repl = " ")) %>%
dplyr::filter(DES_EDO_RES %in% c(edo) &
DES_LOC_RES %in% c(loc))
z1 <- y %>%
dplyr::filter(!DES_EDO_RES %in% c("OTROS PAISES",
"OTROS PAISES DE LATINOAMERICA",
"ESTADOS UNIDOS DE NORTEAMERICA")) %>%
dplyr::filter(DES_DIAG_FINAL %in% c("DENGUE CON SIGNOS DE ALARMA",
"DENGUE GRAVE",
"DENGUE NO GRAVE",
"FIEBRE HEMORRAGICA POR DENGUE",
"FIEBRE POR DENGUE")) %>%
dplyr::mutate(DES_EDO_RES = stringr::str_replace_all(string = DES_EDO_RES,
pattern = " ",
repl = " "),
DES_LOC_RES = stringr::str_replace_all(string = DES_LOC_RES,
pattern = " ",
repl = " ")) %>%
dplyr::filter(DES_EDO_RES %in% edo &
DES_LOC_RES %in% c(loc)) %>%
dplyr::filter(ANO == current_year) %>%
dplyr::group_by(SEM) %>%
dplyr::summarise(n = dplyr::n(), .groups = "drop")
z2 <- y %>%
dplyr::filter(!DES_EDO_RES %in% c("OTROS PAISES",
"OTROS PAISES DE LATINOAMERICA",
"ESTADOS UNIDOS DE NORTEAMERICA")) %>%
dplyr::filter(DES_DIAG_FINAL %in% c("DENGUE CON SIGNOS DE ALARMA",
"DENGUE GRAVE",
"DENGUE NO GRAVE",
"FIEBRE HEMORRAGICA POR DENGUE",
"FIEBRE POR DENGUE")) %>%
dplyr::mutate(DES_EDO_RES = stringr::str_replace_all(string = DES_EDO_RES,
pattern = " ",
repl = " "),
DES_LOC_RES = stringr::str_replace_all(string = DES_LOC_RES,
pattern = " ",
repl = " ")) %>%
dplyr::filter(DES_EDO_RES %in% edo &
DES_LOC_RES %in% c(loc)) %>%
dplyr::filter(ANO == last_year) %>%
dplyr::group_by(SEM) %>%
dplyr::summarise(n = dplyr::n(), .groups = "drop")
}
}
}
ggplot2::ggplot(data = x,
ggplot2::aes(x = SEM)) +
ggplot2::geom_area(ggplot2::aes(y = q75),
col = "black",
size = 0.8,
fill = "#F44B1FFF",
alpha = 1) +
ggplot2::theme_classic() +
ggplot2::geom_area(ggplot2::aes(y = q50),
col = "white",
size = 0.8,
fill = "#FF9000FF",
alpha = 1) +
ggplot2::geom_area(ggplot2::aes(y = q25),
col = "white",
size = .8,
fill = "#00F293FF",
alpha = .8) +
ggplot2::ylab("Casos") +
ggplot2::xlab("Semanas epidemiológicas") +
ggplot2::annotate("text",
label = "Epidémico",
x = x_epi,
y = y_epi,
size = 6,
colour = "black") +
ggplot2::annotate("text",
label = "Alerta",
x = x_alerta,
y = y_alerta,
size = 6,
colour = "black") +
ggplot2::annotate("text",
label = "Seguridad",
x = x_seg,
y = y_seg,
size = 6,
colour = "black") +
ggplot2::annotate("text",
label = "Éxito",
x = x_exito,
y = y_exito,
size = 6,
colour = "black") +
ggplot2::scale_x_continuous(breaks = seq(from = 1,
to = 52,
by = 5),
limits = c(1,52)) +
ggplot2::geom_line(data = z1,
ggplot2::aes(x = SEM, y = n),
alpha = 0.5,
size = 1.5,
colour = "grey") +
ggplot2::geom_point(data = z1,
ggplot2::aes(x = SEM, y = n),
colour = "red",
shape = 21,
alpha = 0.5,
fill = "black",
stroke = 2) +
ggplot2::geom_line(data = z2,
ggplot2::aes(x = SEM, y = n),
#alpha = 0.5,s
size = 1.5,
colour = "black") +
ggplot2::geom_point(data = z2,
ggplot2::aes(x = SEM, y = n),
colour = "white",
shape = 21,
alpha = 0.5,
fill = "red",
stroke = 2)
}
fdzul/boldenr documentation built on April 15, 2024, 10:22 p.m.
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Defines functions den_epichannel
Documented in den_epichannel
#' dengue epidemiological channel
#'
#' den_epichannel generate the dengue epidemiological channel at level state, jurisdiction, municipality and locality.
#'
#' @param x is de dataset with dengue cases percentil.
#' @param y is the dengue dataset the current and last year.
#' @param edo is string indicating the state name.
#' @param jur is string indicating the jurisdiction name.
#' @param mpo is string indicating the municipality name.
#' @param loc is string indicating the locality name.
#' @param current_year is current year dengue dataset.
#' @param last_year is current year dengue dataset.
#' @param x_epi is the x position of the epidemic text.
#' @param y_epi is the y position of the epidemic text.
#' @param x_alerta is the x position of the alert text.
#' @param y_alerta is the y position of the alert text.
#' @param x_seg is the x position of the security text.
#' @param y_seg is the x position of the security text.
#' @param x_exito is the x position of the success text.
#' @param y_exito is the x position of the success text.
#'
#' @author Felipe Antonio Dzul Manzanilla \email{felipe.dzul.m@gmail.com}
#'
#' @return a ggplot object.
#' @export
#'
#'@details if both jur and loc is NULL the function generate the dengue epidemiological channel of state, else only loc is NULL and jur provide the name of jurisdiction then generate the epidemiological channel at level jurisdiction.
#'
#' @examples
den_epichannel <- function(x, y,
edo, jur, mpo, loc,
current_year, last_year,
x_epi, y_epi,
x_alerta,y_alerta,
x_seg, y_seg,
x_exito, y_exito
){
if(is.null(jur)){
x <- x %>%
dplyr::mutate(DES_EDO_RES = stringr::str_replace_all(string = DES_EDO_RES,
pattern = " ",
repl = " ")) %>%
dplyr::filter(DES_EDO_RES %in% c(edo))
z1 <- y %>%
dplyr::filter(!DES_EDO_RES %in% c("OTROS PAISES",
"OTROS PAISES DE LATINOAMERICA",
"ESTADOS UNIDOS DE NORTEAMERICA")) %>%
dplyr::filter(DES_DIAG_FINAL %in% c("DENGUE CON SIGNOS DE ALARMA",
"DENGUE GRAVE",
"DENGUE NO GRAVE",
"FIEBRE HEMORRAGICA POR DENGUE",
"FIEBRE POR DENGUE")) %>%
dplyr::mutate(DES_EDO_RES = stringr::str_replace_all(string = DES_EDO_RES,
pattern = " ",
repl = " ")) %>%
dplyr::filter(DES_EDO_RES == edo) %>%
dplyr::filter(ANO == current_year) %>%
dplyr::group_by(SEM) %>%
dplyr::summarise(n = dplyr::n(), .groups = "drop")
z2 <- y %>%
dplyr::filter(!DES_EDO_RES %in% c("OTROS PAISES",
"OTROS PAISES DE LATINOAMERICA",
"ESTADOS UNIDOS DE NORTEAMERICA")) %>%
dplyr::filter(DES_DIAG_FINAL %in% c("DENGUE CON SIGNOS DE ALARMA",
"DENGUE GRAVE",
"DENGUE NO GRAVE",
"FIEBRE HEMORRAGICA POR DENGUE",
"FIEBRE POR DENGUE")) %>%
dplyr::mutate(DES_EDO_RES = stringr::str_replace_all(string = DES_EDO_RES,
pattern = " ",
repl = " ")) %>%
dplyr::filter(DES_EDO_RES == edo) %>%
dplyr::filter(ANO == last_year) %>%
dplyr::group_by(SEM) %>%
dplyr::summarise(n = dplyr::n(), .groups = "drop")
ggplot2::ggplot(data = x,
ggplot2::aes(x = SEM)) +
ggplot2::geom_area(ggplot2::aes(y = q75),
col = "black",
size = 0.8,
fill = "#F44B1FFF",
alpha = 1) +
ggplot2::theme_classic() +
ggplot2::geom_area(ggplot2::aes(y = q50),
col = "white",
size = 0.8,
fill = "#FF9000FF",
alpha = 1) +
ggplot2::geom_area(ggplot2::aes(y = q25),
col = "white",
size = .8,
fill = "#00F293FF",
alpha = .8) +
ggplot2::ylab("Casos") +
ggplot2::xlab("Semanas epidemiológicas") +
ggplot2::annotate("text",
label = "Epidémico",
x = x_epi,
y = y_epi,
size = 6,
colour = "black") +
ggplot2::annotate("text",
label = "Alerta",
x = x_alerta,
y = y_alerta,
size = 6,
colour = "black") +
ggplot2::annotate("text",
label = "Seguridad",
x = x_seg,
y = y_seg,
size = 6,
colour = "black") +
ggplot2::annotate("text",
label = "Éxito",
x = x_exito,
y = y_exito,
size = 6,
colour = "black") +
ggplot2::scale_x_continuous(breaks = seq(from = 1,
to = 52,
by = 5),
limits = c(1,52)) +
ggplot2::geom_line(data = z1,
ggplot2::aes(x = SEM, y = n),
alpha = 0.5,
size = 1.5,
colour = "grey") +
ggplot2::geom_point(data = z1,
ggplot2::aes(x = SEM, y = n),
colour = "red",
shape = 21,
alpha = 0.5,
fill = "black",
stroke = 2) +
ggplot2::geom_line(data = z2,
ggplot2::aes(x = SEM, y = n),
#alpha = 0.5,s
size = 1.5,
colour = "black") +
ggplot2::geom_point(data = z2,
ggplot2::aes(x = SEM, y = n),
colour = "white",
shape = 21,
alpha = 0.5,
fill = "red",
stroke = 2)
} else{
if(is.null(mpo)){
x <- x %>%
dplyr::mutate(DES_EDO_RES = stringr::str_replace_all(string = DES_EDO_RES,
pattern = " ",
repl = " "),
DES_JUR_RES = stringr::str_replace_all(string = DES_JUR_RES,
pattern = " ",
repl = " ")) %>%
dplyr::filter(DES_EDO_RES %in% c(edo) &
DES_JUR_RES %in% c(jur))
z1 <- y %>%
dplyr::filter(!DES_EDO_RES %in% c("OTROS PAISES",
"OTROS PAISES DE LATINOAMERICA",
"ESTADOS UNIDOS DE NORTEAMERICA")) %>%
dplyr::filter(DES_DIAG_FINAL %in% c("DENGUE CON SIGNOS DE ALARMA",
"DENGUE GRAVE",
"DENGUE NO GRAVE",
"FIEBRE HEMORRAGICA POR DENGUE",
"FIEBRE POR DENGUE")) %>%
dplyr::mutate(DES_EDO_RES = stringr::str_replace_all(string = DES_EDO_RES,
pattern = " ",
repl = " "),
DES_JUR_RES = stringr::str_replace_all(string = DES_JUR_RES,
pattern = " ",
repl = " ")) %>%
dplyr::filter(DES_EDO_RES %in% edo &
DES_JUR_RES %in% c(jur)) %>%
dplyr::filter(ANO == current_year) %>%
dplyr::group_by(SEM) %>%
dplyr::summarise(n = dplyr::n(), .groups = "drop")
z2 <- y %>%
dplyr::filter(!DES_EDO_RES %in% c("OTROS PAISES",
"OTROS PAISES DE LATINOAMERICA",
"ESTADOS UNIDOS DE NORTEAMERICA")) %>%
dplyr::filter(DES_DIAG_FINAL %in% c("DENGUE CON SIGNOS DE ALARMA",
"DENGUE GRAVE",
"DENGUE NO GRAVE",
"FIEBRE HEMORRAGICA POR DENGUE",
"FIEBRE POR DENGUE")) %>%
dplyr::mutate(DES_EDO_RES = stringr::str_replace_all(string = DES_EDO_RES,
pattern = " ",
repl = " "),
DES_JUR_RES = stringr::str_replace_all(string = DES_JUR_RES,
pattern = " ",
repl = " ")) %>%
dplyr::filter(DES_EDO_RES %in% edo &
DES_JUR_RES %in% c(jur)) %>%
dplyr::filter(ANO == last_year) %>%
dplyr::group_by(SEM) %>%
dplyr::summarise(n = dplyr::n(), .groups = "drop")
} else {
if(is.null(loc)){
x <- x %>%
dplyr::mutate(DES_EDO_RES = stringr::str_replace_all(string = DES_EDO_RES,
pattern = " ",
repl = " "),
DES_MPO_RES = stringr::str_replace_all(string = DES_MPO_RES,
pattern = " ",
repl = " ")) %>%
dplyr::filter(DES_EDO_RES %in% c(edo) &
DES_MPO_RES %in% c(mpo))
z1 <- y %>%
dplyr::filter(!DES_EDO_RES %in% c("OTROS PAISES",
"OTROS PAISES DE LATINOAMERICA",
"ESTADOS UNIDOS DE NORTEAMERICA")) %>%
dplyr::filter(DES_DIAG_FINAL %in% c("DENGUE CON SIGNOS DE ALARMA",
"DENGUE GRAVE",
"DENGUE NO GRAVE",
"FIEBRE HEMORRAGICA POR DENGUE",
"FIEBRE POR DENGUE")) %>%
dplyr::mutate(DES_EDO_RES = stringr::str_replace_all(string = DES_EDO_RES,
pattern = " ",
repl = " "),
DES_MPO_RES = stringr::str_replace_all(string = DES_MPO_RES,
pattern = " ",
repl = " ")) %>%
dplyr::filter(DES_EDO_RES %in% edo &
DES_MPO_RES %in% c(mpo)) %>%
dplyr::filter(ANO == current_year) %>%
dplyr::group_by(SEM) %>%
dplyr::summarise(n = dplyr::n(), .groups = "drop")
z2 <- y %>%
dplyr::filter(!DES_EDO_RES %in% c("OTROS PAISES",
"OTROS PAISES DE LATINOAMERICA",
"ESTADOS UNIDOS DE NORTEAMERICA")) %>%
dplyr::filter(DES_DIAG_FINAL %in% c("DENGUE CON SIGNOS DE ALARMA",
"DENGUE GRAVE",
"DENGUE NO GRAVE",
"FIEBRE HEMORRAGICA POR DENGUE",
"FIEBRE POR DENGUE")) %>%
dplyr::mutate(DES_EDO_RES = stringr::str_replace_all(string = DES_EDO_RES,
pattern = " ",
repl = " "),
DES_MPO_RES = stringr::str_replace_all(string = DES_MPO_RES,
pattern = " ",
repl = " ")) %>%
dplyr::filter(DES_EDO_RES %in% edo &
DES_MPO_RES %in% c(mpo)) %>%
dplyr::filter(ANO == last_year) %>%
dplyr::group_by(SEM) %>%
dplyr::summarise(n = dplyr::n(), .groups = "drop")
} else {
x <- x %>%
dplyr::mutate(DES_EDO_RES = stringr::str_replace_all(string = DES_EDO_RES,
pattern = " ",
repl = " "),
DES_LOC_RES = stringr::str_replace_all(string = DES_LOC_RES,
pattern = " ",
repl = " ")) %>%
dplyr::filter(DES_EDO_RES %in% c(edo) &
DES_LOC_RES %in% c(loc))
z1 <- y %>%
dplyr::filter(!DES_EDO_RES %in% c("OTROS PAISES",
"OTROS PAISES DE LATINOAMERICA",
"ESTADOS UNIDOS DE NORTEAMERICA")) %>%
dplyr::filter(DES_DIAG_FINAL %in% c("DENGUE CON SIGNOS DE ALARMA",
"DENGUE GRAVE",
"DENGUE NO GRAVE",
"FIEBRE HEMORRAGICA POR DENGUE",
"FIEBRE POR DENGUE")) %>%
dplyr::mutate(DES_EDO_RES = stringr::str_replace_all(string = DES_EDO_RES,
pattern = " ",
repl = " "),
DES_LOC_RES = stringr::str_replace_all(string = DES_LOC_RES,
pattern = " ",
repl = " ")) %>%
dplyr::filter(DES_EDO_RES %in% edo &
DES_LOC_RES %in% c(loc)) %>%
dplyr::filter(ANO == current_year) %>%
dplyr::group_by(SEM) %>%
dplyr::summarise(n = dplyr::n(), .groups = "drop")
z2 <- y %>%
dplyr::filter(!DES_EDO_RES %in% c("OTROS PAISES",
"OTROS PAISES DE LATINOAMERICA",
"ESTADOS UNIDOS DE NORTEAMERICA")) %>%
dplyr::filter(DES_DIAG_FINAL %in% c("DENGUE CON SIGNOS DE ALARMA",
"DENGUE GRAVE",
"DENGUE NO GRAVE",
"FIEBRE HEMORRAGICA POR DENGUE",
"FIEBRE POR DENGUE")) %>%
dplyr::mutate(DES_EDO_RES = stringr::str_replace_all(string = DES_EDO_RES,
pattern = " ",
repl = " "),
DES_LOC_RES = stringr::str_replace_all(string = DES_LOC_RES,
pattern = " ",
repl = " ")) %>%
dplyr::filter(DES_EDO_RES %in% edo &
DES_LOC_RES %in% c(loc)) %>%
dplyr::filter(ANO == last_year) %>%
dplyr::group_by(SEM) %>%
dplyr::summarise(n = dplyr::n(), .groups = "drop")
}
}
}
ggplot2::ggplot(data = x,
ggplot2::aes(x = SEM)) +
ggplot2::geom_area(ggplot2::aes(y = q75),
col = "black",
size = 0.8,
fill = "#F44B1FFF",
alpha = 1) +
ggplot2::theme_classic() +
ggplot2::geom_area(ggplot2::aes(y = q50),
col = "white",
size = 0.8,
fill = "#FF9000FF",
alpha = 1) +
ggplot2::geom_area(ggplot2::aes(y = q25),
col = "white",
size = .8,
fill = "#00F293FF",
alpha = .8) +
ggplot2::ylab("Casos") +
ggplot2::xlab("Semanas epidemiológicas") +
ggplot2::annotate("text",
label = "Epidémico",
x = x_epi,
y = y_epi,
size = 6,
colour = "black") +
ggplot2::annotate("text",
label = "Alerta",
x = x_alerta,
y = y_alerta,
size = 6,
colour = "black") +
ggplot2::annotate("text",
label = "Seguridad",
x = x_seg,
y = y_seg,
size = 6,
colour = "black") +
ggplot2::annotate("text",
label = "Éxito",
x = x_exito,
y = y_exito,
size = 6,
colour = "black") +
ggplot2::scale_x_continuous(breaks = seq(from = 1,
to = 52,
by = 5),
limits = c(1,52)) +
ggplot2::geom_line(data = z1,
ggplot2::aes(x = SEM, y = n),
alpha = 0.5,
size = 1.5,
colour = "grey") +
ggplot2::geom_point(data = z1,
ggplot2::aes(x = SEM, y = n),
colour = "red",
shape = 21,
alpha = 0.5,
fill = "black",
stroke = 2) +
ggplot2::geom_line(data = z2,
ggplot2::aes(x = SEM, y = n),
#alpha = 0.5,s
size = 1.5,
colour = "black") +
ggplot2::geom_point(data = z2,
ggplot2::aes(x = SEM, y = n),
colour = "white",
shape = 21,
alpha = 0.5,
fill = "red",
stroke = 2)
}
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