---
title: "Indigenous Australians - Life Expectancy v Government Health Funding"
output: 
  flexdashboard::flex_dashboard:
    storyboard: true
    social: menu
    source: embed
---

```{r setup, include=FALSE}

library(flexdashboard)
library(plotly)
library(dplyr)
library(readr)
library(rsconnect)
```

```{r import, include=FALSE}

# Import data files
df <- read.csv('C:/tmp/lifeexpectancy2.csv')
df1 <- read.csv('C:/tmp/population.csv')
df4 <- read.csv('C:/tmp/lifestate.csv')
df5 <- read.csv('C:/tmp/Lifeexpectancy_female.csv')
df6 <- read.csv('C:/tmp/Lifeexpectancy_male.csv')
data <- read_csv('C:/tmp/forecast.csv')

```

### Aboriginal and Torres Strait Islander and non-Indigenous Australians population is inceasing meaning closing the gap targets will become harder to achieve.

```{r}
library(leaflet)
leaflet() %>%
  addTiles() %>%
  addMarkers(lng=133.24854659011083, lat=-19.182988838507033, popup="NT: 4.9% of indigenous population, +2,867 in 2016-21") %>%
    addMarkers(lng=144.29454913948564, lat=-22.30712580042463, popup="Queensland: 27.3% of indigenous population, +50,821 in 2016-21") %>% 
      addMarkers(lng=146.6950494536986, lat=-32.051548451146715, popup="New South Wales: 28.6% of indigenous population, +61,876 in 2016-21") %>%
      addMarkers(lng=130.9134761, lat=-11.6850887, popup="Tiwi Islands: 2% of indigenous population (est) 2600") %>%
        addMarkers(lng=142.8285966, lat=-36.5559583, popup="Victoria: +37.4% of indigenous population, +37.4% in 2016-21") %>%
      addMarkers(lng=146.8246297, lat=-41.4340671, popup="Tasmania: +28.1% of indigenous population, +6,614 in 2016-21") %>%
      addMarkers(lng=129.7107677, lat=-31.9102222, popup="South Australia: 24.5% of indigenous population, +8,378 in 2016-21") %>%
      addMarkers(lng=121.8635231, lat=-24.8794641, popup="Western Australia: +16.7% of indigenous population, +12,715 in 2016-21")
      

```

------------------------------------------------------------------------

-   Overall there has been a 25.2% increase in Indigenous and Tiwi Islander persons between 2016-21

-   Health is a significant factor in life expectancy of Indigenous and Tiwi Islands Persons

-   Location of Indigenous Persons particularly for remote communities presents a major challenge for improving health and life expectancy

-   For example - life expectancy for Indigenous Males living in Remote jsestimated to be 6.2 years lower than that of Indigenous males living in major cities

-   Sources [Australian Bureau Statistics (ABS) Demographic Change](https://www.abs.gov.au/statistics/people/aboriginal-and-torres-strait-islander-peoples/understanding-change-counts-aboriginal-and-torres-strait-islander-australians-census/latest-release), [Closing the Gap Report, Australian Government](https://ctgreport.niaa.gov.au/life-expectancy)

### Health makes up 24.8% of total government spending and will have a large influence on whether on not the 2032 target is met.

```{r lifeexpect}

# Data
values <- c(29.7, 35.4, 34.8, 20.0) # Your data values
labels <- c("Health risk factors", "Social determinants", "Other factors", "Social & health")

# Plot
proportion <- plot_ly(labels = labels, values = values, type = 'pie',
               textinfo = 'label+percent',
               insidetextorientation = 'radial',
               textposition = 'inside',
               showlegend = FALSE)

proportion

```

------------------------------------------------------------------------

-   Health risk factors (24.8%) make up the majority of measure impacting Indigenous and Torres Straight Islander life expectancy

-   15.4% of the Aboriginal and Torres Strait Islander population lived in Remote (58,700 people or 6.0%) and Very Remote (92,100 people or 9.4%) Areas of Australia

-   Remote and Very Remote areas present challenges with location of health care centers and skilled employees

-   Source: [Australian Department of Health & Welfare](https://www.indigenoushpf.gov.au/Report-overview/Overview/Summary-Report/2-Demographic-and-social-context)

### The Australian Federal Government has set targets through its 'Closing the Gap' initiative to have a zero year difference in life expectancy between indigenous and non-indigenous Australians by 2032.

```{r}

# Create barchart
expectplot <- plot_ly(data = df4, x = ~States) %>%
    add_trace(y = ~Males, name = 'Males', type = 'bar', marker = list(color = 'blue'), 
              text = ~Males, textposition = 'outside') %>%
    add_trace(y = ~Females, name = 'Females', type = 'bar', marker = list(color = 'red'),
              text = ~Females, textposition = 'outside') %>%
    layout(yaxis = list(title = 'Life Expectancy'), barmode = 'group')

# Display plot
expectplot

```

------------------------------------------------------------------------

-   Life expectancy of Indigenous peoples living in Australia and Tiwi Islands is 71.9 (Males) and 75.6 (Females)

-   In all states, Female life expectancy is greater than Male life expectancy

-   Separate targets for Indigenous Males and Females have been established as part of 'Closing the Gap'

    Source: [Australian Institute of Health and Welfare](https://www.indigenoushpf.gov.au/Report-overview/Overview/Summary-Report/4-Tier-1-%E2%80%93-Health-status-and-outcomes/Life-expectancy)

### Health makes up 24.8% of total government spending and will have a large influence on whether on not the 2032 target is met.

```{r piechart}

# Plot
lifefemale <- plot_ly(data = df5, x = ~Year, type = 'scatter') %>% 
    add_trace(y = ~Actual, name = 'Actual', mode = 'lines+markers', 
              line = list(color = 'blue')) %>%
    add_trace(y = ~Trajectory, name = 'Trajectory', mode = 'lines+markers', 
              line = list(color = 'red', dash = 'dot')) %>%
    layout(title = 'Life Expectancy Over Time (Female)',
           xaxis = list(title = 'Year'),
           yaxis = list(title = 'Life Expectancy'))


#Plot
lifemale <- plot_ly(data = df6, x = ~Year, type = 'scatter') %>% 
    add_trace(y = ~Actual, name = 'Actual', mode = 'lines+markers', 
              line = list(color = 'blue')) %>%
    add_trace(y = ~Trajectory, name = 'Trajectory', mode = 'lines+markers', 
              line = list(color = 'red', dash = 'dot')) %>%
    layout(title = 'Life Expectancy Over Time (Male)',
           xaxis = list(title = 'Year'),
           yaxis = list(title = 'Life Expectancy'))

#Combine
combine <- subplot(lifefemale, lifemale, nrows = 2) %>% 
  layout(title = 'Indigenous Life Expectancy Target - Female (a) Male (b)')
combine

```

------------------------------------------------------------------------

-   In 2016, 649,171 people identified as Aboriginal and/or Torres Strait Islander in 2021, 812,728 as Aboriginal or Torres Strait Islander - an increase of 25%

-   Government funding will need to increase to account for the above two factors - skill shortages in health will also be a consideration

-   Sources [Australian Bureau Statistics (ABS) Demographic Change](https://www.abs.gov.au/statistics/people/aboriginal-and-torres-strait-islander-peoples/understanding-change-counts-aboriginal-and-torres-strait-islander-australians-census/latest-release), [Closing the Gap - Targets](https://www.pc.gov.au/closing-the-gap-data/dashboard/se/outcome-area1)

### Based on actual results achieved to date, increasing indigenous population, expected funding and trends - closing the gap targets will continue to be off target.

```{r}

# plot
gap <- plot_ly(data, x = ~Year) %>%
  add_trace(y = ~Value, name = 'Actual Values', mode = 'lines+markers', line = list(color = 'blue')) %>%
  add_trace(y = ~Forecast, name = 'Forecast', mode = 'lines+markers', line = list(color = 'red')) %>%
  add_trace(y = ~Lower, name = 'Lower Confidence', mode = 'lines+markers', line = list(color = 'orange', dash = 'dot')) %>%
  add_trace(y = ~Upper, name = 'Upper Confidence', mode = 'lines+markers', line = list(color = 'orange', dash = 'dot')) %>%
  layout(title = 'Forecast Indigenous Health Spending Per Person',
         xaxis = list(title = 'Year'),
         yaxis = list(title = 'Value'))

# Print the plot to view it
gap
```

------------------------------------------------------------------------

-   In 2021, there were 983,700 Aboriginal and Torres Strait Islander people in Australia which represents 3.8% of the Australian population

-   Based on actual spending on Indigenous and Torres Straight Islander people between 2017-2020 (per person); forecasts show a steep increase in funding required to meet the 2032 target

-   Factors such as increasing population, remote location of Indigenous and Torres Straight Islanders and unfunded increase in cost per person for health concludes that the 'Closing the Gap' targets will not be met by 2032.

Source: <https://www.abs.gov.au/statistics/people/aboriginal-and-torres-strait-islander-peoples/aboriginal-and-torres-strait-islander-life-expectancy/latest-release>