The 2014 Ebola epidemic is one of the largest we've seen, affecting mostly countries clustered in West Africa (though a smaller outbreak has occurred as well in other African countries such as the Democratic Republic of the Congo despite an inappropriate Washington Post fantasy). For all the earlier domestic panic, in the United States (U.S.) there has been one associated death -in Texas- on October 8. Also in the U.S., there have since been three additional cases, but none with an associated death.
In this article we will take a quick focused look at the progression of Ebola in three interconnected West African countries at this epicenter: Guinea to the north, Liberia to the south, and sandwiched between to the west is Sierra Leone. Given the location of the respective populations, we might expect the cumulative cases and death statistics in Sierra Leone to be a blend of those for the other countries. However due to inexplicable reporting biases within each country for cases versus follow-up deaths, and the infrastructure proximity -at the connection of Guinea and Liberia- we see that these two countries instead are most similar at present.
We look at this statistical visualization below, showing the progress of all Ebola cases (horizontal axis) and deaths (vertical axis). The time series begins on August 29 on the lower left of the chart, and all the cumulative statistics then progress in the upper right direction. Terminating on October 31. Given the unique and time-varying reporting frequencies, each country data was manually aligned into the same semi-weekly format. The chart also uses logarithmic axis scaling to better contrast the three country's data (e.g., Liberia has a couple times the size of outbreak versus Guinea.)
What immediately stands out from the painful statistics, visualized above, are three things. The first couple things are that the Ebola cases in Sierra Leone has grown at a much faster rate, while simultaneously at an insoluble lower reported death rate versus those in the other two countries. The third thing is that still, in Sierra Leone, the outbreak has only picked up in the past month (this can be seen as a convergence with the 1:1 green line). Relative not only to what we've seen thusfar in the U.S., but relative to the other two West African countries in this article. The October 8 data has been conveniently colored solid, as opposed to the other hollowed and colored data. We also see the impact of the regional government revising untrustworthy initial classifications, particularly in the past couple weeks.
On an unrelated topic, it is worth noting a couple recent accolades for our statistics work. The first thing is that the Statistics Topics book, covering broad statistics applications, is now #1 in mathematical research on Amazon and was top-ranked in sales three months straight on this prominent list. The second thing is that the research we published in a recent CFA article has generated considerable LinkedIn buzz, and it is an important topic for financial market participants. Lastly, given that it's Election Day on Tuesday, take a chance to turn off your computer for a short while, and swing by your local voting booth to express your views.
In this article we will take a quick focused look at the progression of Ebola in three interconnected West African countries at this epicenter: Guinea to the north, Liberia to the south, and sandwiched between to the west is Sierra Leone. Given the location of the respective populations, we might expect the cumulative cases and death statistics in Sierra Leone to be a blend of those for the other countries. However due to inexplicable reporting biases within each country for cases versus follow-up deaths, and the infrastructure proximity -at the connection of Guinea and Liberia- we see that these two countries instead are most similar at present.
We look at this statistical visualization below, showing the progress of all Ebola cases (horizontal axis) and deaths (vertical axis). The time series begins on August 29 on the lower left of the chart, and all the cumulative statistics then progress in the upper right direction. Terminating on October 31. Given the unique and time-varying reporting frequencies, each country data was manually aligned into the same semi-weekly format. The chart also uses logarithmic axis scaling to better contrast the three country's data (e.g., Liberia has a couple times the size of outbreak versus Guinea.)
What immediately stands out from the painful statistics, visualized above, are three things. The first couple things are that the Ebola cases in Sierra Leone has grown at a much faster rate, while simultaneously at an insoluble lower reported death rate versus those in the other two countries. The third thing is that still, in Sierra Leone, the outbreak has only picked up in the past month (this can be seen as a convergence with the 1:1 green line). Relative not only to what we've seen thusfar in the U.S., but relative to the other two West African countries in this article. The October 8 data has been conveniently colored solid, as opposed to the other hollowed and colored data. We also see the impact of the regional government revising untrustworthy initial classifications, particularly in the past couple weeks.
On an unrelated topic, it is worth noting a couple recent accolades for our statistics work. The first thing is that the Statistics Topics book, covering broad statistics applications, is now #1 in mathematical research on Amazon and was top-ranked in sales three months straight on this prominent list. The second thing is that the research we published in a recent CFA article has generated considerable LinkedIn buzz, and it is an important topic for financial market participants. Lastly, given that it's Election Day on Tuesday, take a chance to turn off your computer for a short while, and swing by your local voting booth to express your views.
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