DataGeek III Challenge: 2014 Ebola outbreak Analysis

[former_member18062]

This blog was created as a part of Data Geek Challenge III in the category "House of Healers - Science and Health"

When I accepted the Datageek challenge, I decided that creating a Lumira Storyboard or Infographic which covers the Ebola 2014 outbreak would be very interesting to see.  Data can be an extremely powerful tool in preventing wider disease outbreaks and providing critical information.  Using Data along with Analytics, we can track a virus down to its source and also monitor infection rate and spread.

Datasource:

My first challenge was to find a sample data-set to play with.  So, I did some google-ing and came across some data on github which is maintained by Caitlin Rivers (@cmyeaton) | Twitter.  Caitlin's done a great job in tracking this data and putting together this cache of information.  For my use, I had to play with the data a bit, so don't hold me to the data's accuracy :wink:   The data snapshot is taken up until October 22nd 2014.

Analysis of confirmed Cases:

In the past 6 or 7 months that we've been dealing with this current Ebola outbreak, there are some serious questions that can be answered by analyzing historical data:

• When was the largest increase in spread of infection?
• Which country has the most people dealing with Ebola?
• Where is the source of the current Ebola outbreak?

Although I don't have all those answers, we can look at this Lumira Storyboard on Case Analysis and see some interesting facts:

Analysis of Deaths:

In the recent news, you've heard of the virus spreading to USA and Spain, but originated in West Africa.

• But just how many deaths have occurred due to Ebola?
• Which country has the highest number of deaths?

Lumira Infographic:

This infographic provides an overview of the data found on the last two storyboards:

• Which country was hardest hit by Ebola outbreak?
• How many deaths globally?
• How much money has been donated to the cause?

There are still many unknowns about the Ebola virus, most importantly how to cure and vaccinate against it.  While this data may not ever tell us how to cure it, we can better manage and contain an outbreak so that it does not spread.  This type of data could also help researchers discover the source where humans first contracted the virus.

Thanks DataGeek Challenge III I certainly had fun using SAP Lumira for the first time.