# Chapter 3 DENGUE DATA

## 3.1 Init

``````library(tidyverse)
library(lubridate)
library(rEDM)
library(ISOweek)
library(stringr)
library(cowplot)``````

## 3.2 Data

``````PER_district <- read.csv("./_data/dengue_20211008_2.csv")

## 3.3 Exploration

### 3.3.1 PERU

``````PER_district %>%
date_proto = paste0(Year,"-W", week_proto,"-1"),
date = ISOweek2date(date_proto),
yy = year(date),
mm = month(date)) %>%
group_by(yy, mm, Departamento) %>%
summarise(tot_casos = sum(Casos)) %>%
mutate(date = ymd(paste(yy,mm,"01", sep = "-"))) %>%
filter(date < ymd("2021-10-01")) %>%
ggplot(aes(x = date, y = tot_casos, col = log(tot_casos))) +
scale_color_viridis_c(option = "rocket", direction = -1, na.value = "gray") +
labs(title = "National data (DIC-2014 : SEP-2021)") +
geom_line() +
facet_wrap(.~Departamento, scales = "free", ncol = 4) +
theme_bw() +
theme(legend.position = "top")``````

### 3.3.2 LORETO

``````LOR_linelist %>%
#filter(tipo_dx != "D") %>%
mutate(date = ymd(fecha_not),
yy = year(date),
mm = month(date)) %>%
group_by(yy, mm, departam) %>%
summarise(tot_casos = n()) %>%
mutate(date = ymd(paste(yy,mm,"01", sep = "-"))) %>%
ggplot(aes(x = date, y = tot_casos, col = log(tot_casos))) +
scale_color_viridis_c(option = "rocket", direction = -1, na.value = "gray") +
labs(title = "Loreto Regional data (JAN-2000 : MAY-2021)") +
geom_line() +
theme_bw() +
theme(legend.position = "top")``````

``````LOR_linelist %>%
#filter(tipo_dx != "D") %>%
mutate(date = ymd(fecha_not),
yy = year(date),
mm = month(date)) %>%
group_by(yy, mm, provincia) %>%
summarise(tot_casos = n()) %>%
mutate(date = ymd(paste(yy,mm,"01", sep = "-"))) %>%
ggplot(aes(x = date, y = tot_casos, col = log(tot_casos))) +
scale_color_viridis_c(option = "rocket", direction = -1, na.value = "gray") +
labs(title = "Loreto Regional data by provinces (JAN-2000 : MAY-2021)") +
geom_line() +
facet_wrap(.~provincia, scales = "free", ncol = 4) +
theme_bw() +
theme(legend.position = "top")``````

### 3.3.3 COMPARISON

``````a <- LOR_linelist %>%
#filter(tipo_dx != "D") %>%
mutate(date = ymd(fecha_not),
yy = year(date),
mm = month(date)) %>%
group_by(yy, mm, departam) %>%
summarise(tot_casos = n()) %>%
mutate(date = ymd(paste(yy,mm,"01", sep = "-"))) %>%
filter(departam == "LORETO",
date > ymd("2014-11-01"),
date < ymd("2021-06-01")) %>%
ggplot(aes(x = date, y = tot_casos, col = log(tot_casos))) +
scale_color_viridis_c(option = "rocket", direction = -1, na.value = "gray",
limits = c(0,10)) +
labs(title = "Loreto Regional data (DIC-2014 : MAY-2021)") +
scale_y_continuous(limits = c(0,4000)) +
geom_line() +
theme_bw() +
theme(legend.position = "top")

b <- PER_district %>%
date_proto = paste0(Year,"-W", week_proto,"-1"),
date = ISOweek2date(date_proto),
yy = year(date),
mm = month(date)) %>%
group_by(yy, mm, Departamento) %>%
summarise(tot_casos = sum(Casos)) %>%
mutate(date = ymd(paste(yy,mm,"01", sep = "-"))) %>%
filter(Departamento == "LORETO",
date > ymd("2014-11-01"),
date < ymd("2021-06-01")) %>%
ggplot(aes(x = date, y = tot_casos, col = log(tot_casos))) +
scale_color_viridis_c(option = "rocket", direction = -1, na.value = "gray",
limits = c(0,10)) +
labs(title = "National data (DIC-2014 : MAY-2021)") +
scale_y_continuous(limits = c(0,4000)) +
geom_line() +
theme_bw() +
theme(legend.position = "top")

plot_grid(a,b)``````

## 3.4 Export

• Regional data at monthly level was selected for analysis
``````LOR_linelist %>%
mutate(date = ymd(fecha_not),
yy = year(date),
mm = month(date)) %>%
group_by(ubigeo, departam, provincia, distrito, yy, mm) %>%
summarise(tot_casos = n()) %>%
mutate(date = ymd(paste(yy,mm,"01", sep = "-"))) %>%
write_csv("_data/LOR_dengue.csv", na = "")``````