People wonder just how bad the Ebola outbreak could get. Well, with a bit of understanding of the relevant mechanisms, knowledge of the math involved, and a spreadsheet, putting together a \u201cquick and dirty\u201d approximate model for the spread of that disease is relatively easy.<\/p>\n
What it shows may be somewhat hard to swallow. And it is a simplified model; reality will be somewhat more complex. But for the early stages of an epidemic \u2013 and we\u2019re still in the relatively early stages of this one \u2013 I think this should be relatively close.<\/p>\n
First, a few known facts and\/or best estimates for the current outbreak and about Ebola itself<\/span>.<\/p>\n How epidemics work.<\/span><\/p>\n An epidemic in an immunologically na\u00efve population (e.g., one that has no previous exposure, and thus no natural resistance to the disease) works and can be modeled at a somewhat simplistic level as follows.<\/p>\n That\u2019s it. Until the numbers of persons with some type of immunity to the disease (either through survival or vaccination) in the affected population becomes significant, the above is a reasonably accurate \u2013 though somewhat crude \u2013 description of how an infectious disease propagates through a susceptible population.\u00a0 It will hold until something (deaths, developed immunity, behavioral changes, whatever) changes the transmission cycle of the disease – usually by changing the reproduction number.<\/p>\n Those familiar with calculus might be wondering if this is a process exhibiting exponential growth. The answer, unfortunately, is yes. Epidemics in fully susceptible populations are indeed exponential growth scenarios until \u201cherd immunity\u201d (the fraction of the population immune due to prior exposure or vaccination) becomes significant \u2013 or until the population dies out, or something else intervenes to reduce the reproduction number below 1.<\/p>\n The Model<\/span>.<\/p>\n Here is a simplified spreadsheet model<\/a> I\u2019ve come up with for the current West Africa Ebola outbreak. As noted, it\u2019s a rather crude, “quick and dirty” model. But it gives a reasonable idea of what may be in store; I don’t think it’s grossly in error.\u00a0 Format is Excel 97-2003.\u00a0 If anyone with more knowledge of the subject or the parameters in question has criticism or comment, I’m all ears. Getting it right is what’s important.<\/p>\n Fair warning:\u00a0 I would suggest you (a) sit down, and (b) get a cup of coffee (or something stronger) before you look at the model.\u00a0 And I wouldn’t recommend do so immediately after or while eating.<\/p>\n Assumptions used were the following.<\/p>\n For 9 October – the start date of the model’s generation 20 of the outbreak – this model predicted a reported number of cases of 7,724 and a reported number of deaths of 4,090.<\/p>\n Per the CDC website, on 8 October 2014, the reported number of cases was 8,011; the reported number of deaths was 3,857<\/a>.<\/p>\n On the “bright side” – if you can call it that – the model I developed doesn\u2019t predict 1.4 million cases until late Feb\/early Mar 2015. Without changes in the outbreak, CDC predicts that number of cases by late January<\/a>.<\/p>\n I guess I could say \u201cHappy Halloween\u201d at this point; the above is certainly scary enough. But I don\u2019t see much to be happy about above.<\/p>\n THIS is why we need to do everything possible to keep this sh!t out of the United States. Period.<\/strong><\/span><\/em><\/p>\n Are you listening, Mr. President?<\/p>\n","protected":false},"excerpt":{"rendered":"\n
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