---
title: "COVID-19 in the Greater Caribbean Islands Region"
output:
  flexdashboard::flex_dashboard:
    orientation: rows
    vertical_layout: fill
    theme: flatly
    source_code: embed
css: styles.css
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = FALSE, warning = TRUE, message = TRUE)

suppressPackageStartupMessages({
  library(tidyverse)
  library(lubridate)
  library(crosstalk)
  library(DT)
  library(plotly)
  library(rpivotTable)
  library(scales)
 library(ggsci)
  # library(flexdashboard) # not required since we namespace valueBox
})


# Lancet-inspired palettes
lancet_pal <- ggsci::pal_lancet()(9)
# Sequential medical blues for heatmaps
lancet_heat <- c("#F7FBFF", "#DEEBF7", "#C6DBEF", "#9ECAE1", "#6BAED6", "#4292C6", "#2171B5", "#08519C")

# Read data (blanks -> 0, parse dates)
# Read data (blanks -> 0, parse dates)
cases_raw <- readr::read_csv(
  "00_data/coronatsCarib_F.csv",
  col_types = readr::cols(
    Country = readr::col_character(),
    date = readr::col_date(),
    New_Cases_N = readr::col_double(),
    New_Cases = readr::col_double()
  )
) %>% 
 filter (date < "2021-10-25")

# Aggregate to weekly cases by Country
weekly_data <- cases_raw %>%
  mutate(
    New_Cases = coalesce(New_Cases, 0),
    week_start = floor_date(date, unit = "week", week_start = 1),
    year_week = strftime(week_start, "%G-W%V"),
    year_month = format(week_start, "%Y-%m")
  ) %>%
  group_by(Country, week_start, year_week, year_month) %>%
  summarise(cases = sum(New_Cases, na.rm = TRUE), .groups = "drop") %>%
  arrange(desc(week_start))  # sort BEFORE wrapping in SharedData

# Crosstalk wrapper
weekly_shared <- SharedData$new(weekly_data)

# KPIs
latest_week <- suppressWarnings(max(weekly_data$week_start, na.rm = TRUE))
latest_total <- weekly_data %>%
  filter(week_start == latest_week) %>%
  summarise(total = sum(cases, na.rm = TRUE)) %>%
  pull(total) %>% { if (length(.) == 0 || is.na(.)) 0 else . }

top_country_latest <- weekly_data %>%
  filter(week_start == latest_week) %>%
  slice_max(cases, n = 1, with_ties = FALSE)

kpi_top_country <- if (nrow(top_country_latest)) top_country_latest$Country else NA_character_
kpi_top_country_cases <- if (nrow(top_country_latest)) top_country_latest$cases else 0
```

Overview
=======================================================================

Row {data-height=140}
-----------------------------------------------------------------------

### Latest week total

```{r}
flexdashboard::valueBox(
  value = scales::comma(latest_total),
  caption = paste0(
    "Total New Cases (week of ",
    ifelse(is.finite(latest_week), format(latest_week, "%Y-%m-%d"), "N/A"),
    ")"
  ),
  icon = "fa-line-chart",
  color = if (is.finite(latest_total) && latest_total > 0) "primary" else "success"
)
```

### Top country (latest week)

```{r}
flexdashboard::valueBox(
  value = ifelse(is.na(kpi_top_country), "N/A", kpi_top_country),
  caption = paste0("Highest weekly cases: ", scales::comma(kpi_top_country_cases)),
  icon = "fa-flag",
  color = "info"
)
```

### Countries covered

```{r}
flexdashboard::valueBox(
  value = dplyr::n_distinct(weekly_data$Country),
  caption = "Unique countries",
  icon = "fa-globe",
  color = "success"
)
```

Row {data-height=220}
-----------------------------------------------------------------------

### About this dashboard

This dashboard summarizes COVID-19 in the Greater caribbean Islands Region by aggregating daily New_Cases from coronatsCarib_F.csv into ISO weekly totals (weeks start Monday) for each country, making cross-country trends easier to compare.

What’s inside
- Overview: Latest-week total, top country, and number of countries.
- Weekly table: Filterable, exportable weekly counts by country and week.
- Pivot heatmap: Country × month view to spot periods of higher transmission.
- Trend chart: Stacked weekly time series showing each country’s contribution.

How to use
- Filter by country/month in the sidebar; hover bars for exact values; export tables as needed.

Notes
- Weekly values are sums of daily New_Cases (blanks treated as 0); recent weeks may be incomplete due to reporting lag.

Weekly New Cases by Country (Table)
=======================================================================

Inputs {.sidebar}
-----------------------------------------------------------------------

```{r}
filter_checkbox("cty", "Choose country", weekly_shared, ~Country)
filter_select("ym", "Choose month", weekly_shared, ~year_month)
filter_slider("wk_cases", "Filter weekly cases", weekly_shared, ~cases, width = "100%")
```

Row
-----------------------------------------------------------------------

### Weekly New Cases (table)

```{r}
DT::datatable(
  weekly_shared,
  class = "compact cell-border stripe",
  rownames = FALSE,
  extensions = c("Buttons", "Responsive"),
  options = list(
    dom = "Bfrtip",
    buttons = c("copy", "csv", "excel", "print"),
    pageLength = 20,
    autoWidth = TRUE
  )
)
```

Weekly New Cases by Country (Pivot)
=======================================================================

Row
-----------------------------------------------------------------------

### Interactive pivot (sum of weekly cases)

```{r}
rpivotTable(
  data = weekly_data,
  rows = "Country",
  cols = "year_month",
  vals = "cases",
  aggregatorName = "Sum",
  rendererName = "Heatmap",
  rendererOptions = list(
    colorScale = list(colors = lancet_heat)
  ),
  width = "100%", height = "600px"
)
```

Weekly New Cases by Country (Trend)
=======================================================================

Inputs {.sidebar}
-----------------------------------------------------------------------

```{r}
filter_checkbox("cty2", "Choose country", weekly_shared, ~Country)
filter_select("ym2", "Choose month", weekly_shared, ~year_month)
```

Row
-----------------------------------------------------------------------

### Weekly trend (stacked, Lancet palette)

```{r}
plot_ly(
  data = weekly_shared,
  x = ~week_start, y = ~cases,
  type = "bar",
  color = ~Country,
  colors = lancet_pal,
  hoverinfo = "text",
  text = ~paste0(
    "Country: ", Country,
    "<br>Week start: ", format(week_start, "%Y-%m-%d"),
    "<br>Cases: ", scales::comma(cases)
  )
) %>%
  layout(
    barmode = "stack",
    legend = list(orientation = "h"),
    xaxis = list(title = "Week start"),
    yaxis = list(title = "Weekly New Cases", rangemode = "tozero")
  )
```