If you're just joining the #HackEbola series, check out the introduction, and see the other posts by clicking on the Ebola category. All this data is available at github.com/cmrivers/ebola.
Let's skip over to Sierra Leone for a bit. Although there are fewer cases in Sierra Leone, it's still suffering widespread transmission. Kailahun and Kenema counties in particular are hard hit, with 601 and 438 cases respectively, as of Sept 17. However, these counties are relatively populous. Comparing the number of cases in each county to population reveals that both counties are leading in both in relative and absolute terms.
I don't have detailed data on case counts in Sierra Leone going back more than six weeks, but we can still see that cases are growing steadily. You can see a few spikes followed by drops. These are revisions to suspected and probable cases. In other words, some people were thought to have Ebola but it turned out later that they did not.
This speaks to one major issue in identifying cases - early symptoms of Ebola infection look a lot like other diseases. A fever could also be malaria, or a hundred other things. Isolating suspected and probable Ebola cases is critical for preventing transmission. But if you isolate a suspected case that turns out to have had malaria, and that person is isolated with true Ebola cases, that's a big problem.
Moving on, when we look at deaths over time though, we see something strange. Despite these four counties having hundreds of cases, they are reporting almost no deaths. You can see the National tally climbing, but the county tallies remain relatively static.
And indeed, when we compare deaths reported by the Sierra Leone Ministry of Health with the deaths the WHO reports in Sierra Leone, we see a discrepancy.
This could be due to several things. It may simply be an accounting error on the part of whoever puts out the daily spreadsheets for Sierra Leone. It could be that the WHO is compiling deaths from different sources (e.g. Medecins Sans Frontiers), and the Ministry of Health is not. Collecting and disseminating data during outbreaks is surely tricky business. There's a lot to coordinate, conflicting reports, uncertainty, etc. It's not uncommon to see data issues like these. It doesn't mean that the MoH is doing a poor job, or hiding something. It's probably just a clerical error of some kind. However, it is important to identify these issues early so that they don't mess up your analysis.
If this epidemiology wizardy isn't fancy enough for you, hang tight. I've got some neat things up my sleeve.
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