Review components to add into the dashboard

[yohannesHL]

https://public.tableau.com/profile/mahletkonjitsolomon#!/vizhome/EthiopiaCOVID-19Cases/AfricaCOVID19Cases

[yohane55]

@yohannesHL can you take this assignment?
@abelhbeyene and @dotmike can you please make the full range stats api available?

[yohannesHL]

Goal: Determine a good collection of dashboard items that are deemed useful and actionable for end users - Learn from current examples available. (ie: UK, Singapore). And colab with relavant ppl incl Mahlet )

Taking some inspiration from Mahlets work
And some best ideas from this review (Mainly Singapore & UK): https://www.technologyreview.com/s/615330/best-worst-coronavirus-dashboards/

I've highlighted the following items which i think are needed (separate sub tasks are/will be linked).

1. Update case cards (:heavy_check_mark: , #38 ):
   1. will need to review wording to ensure clarity on what each statistic means (ie: Total confirmed cases, Daily cases)
   2. Update Styling(UI/UX) in accordance with best practices (some ideas taken from UK ONS guidelines
      • Remove background colors and only keep text colors
      • Make font size of card labels slightly larger
      • Group deaths onto categories so that important information is visible first (or at first glance):
        

Grouped example (POC):

Total cases	Hospitalised	Recovered	Quarantine
21 Cases	17 Stable	1 Recovered	25 Quarantined
0 Deaths	3 Critical

2. Replace radial + pie charts (same data) with bar chart. (:heavy_check_mark:, https://github.com/
   /issues/31,)

3. Total Cases discharged vs active line cart (Replace daily chart?) (WIP, #45)
   

4. Cases table/bar chart per region (:heavy_check_mark:, https://github.com/
   /issues/31, )
   

5. Cases by age range and gender (TODO)
   

6. Case List table + Detail (TBC)
   
   
   

7. Update Hourly chart (WIP, #47)

   • Rename to Cases by hour of day
   • Move below Map

8. Update Map viz (hot spots?) ( ✔️ )

9. Include estimated cases (optionally hide-able) (TODO)

   • There's is a good amount of evidence to suggest that reported/confirmed cases are not accurate in determining the actual cases currently on the ground. I've found some info regarding this and think this would be useful for health practitioners and officials in their efforts.
   • We can include an additional data point Estimated daily cases using the formula/model sourced from https://covid19dashboards.com/covid-infected/ https://systems.jhu.edu/research/public-health/ncov-model-2/

Dashboard Examples:

Mahlet - https://public.tableau.com/profile/mahletkonjitsolomon#!/vizhome/EthiopiaCOVID-19Cases/AfricaCOVID19Cases
UK - https://www.arcgis.com/apps/opsdashboard/index.html#/f94c3c90da5b4e9f9a0b19484dd4bb14
Singapore - https://experience.arcgis.com/experience/7e30edc490a5441a874f9efe67bd8b89 https://www.againstcovid19.com/singapore/dashboard