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I am in the beginning stages of a capstone project for my master's in Data Science. For various reasons, I have landed on the subject of Clostridium difficile infection. My background is in Computer Science, Mathematics, and Statistics, but biology is way outside of my wheelhouse. While most of my project will focus on the statistical modelling aspect, I would like to be able to speak intelligently on the subject itself and be able to read through journal articles without getting tripped up on some of the terminology.

I'm not trying to cut corners, but I'm on a tight timeline (about 4 months). What resources - books, references, online courses - would you recommend to bootstrap me into the field of infectious diseases?

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  • $\begingroup$ Welcome to Biology.SE! Is it an intro book to epidemiology that you're looking for? $\endgroup$
    – Remi.b
    Commented Dec 27, 2017 at 16:54
  • $\begingroup$ I think that could be helpful. Something to get me started with basic concepts or to use as a reference maybe. $\endgroup$
    – bdetweiler
    Commented Dec 27, 2017 at 19:57

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Since I didn't get an answer, I'll mention what I did.

My goal was to understand a particular disease well enough to talk intelligently about it while focusing mostly on the statistics. So learning Epidemiology from the ground up wouldn't have been practical in the 4-5 months I had.

I started with a high level patient-oriented book, C. diff in 30 Minutes. That gave me a general understanding of the disease. Then I began reading academic articles. Not only were these useful for citations in my paper, but it also helped expand my understanding. I would notice common terms that kept popping up. Gram-positive, rod shaped, anaerobic, endospore-forming is intimidating at first, but each of these modifiers can be googled individually to build an understanding.

Finally, it was necessary to know how much I needed to know. I began reading about the hypervirulent strain, ribotype 027 with its binary toxin yadda yadda. None of that was actually important for my paper because that level of detail wasn't in the data.

So while knowing the general landscape was important, knowing each and every detail, for my purposes, wasn't.

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