<p/><br></br><p><b> Book Synopsis </b></p></br></br><p>Science is based on models that we construct to help us to better understand the world. This is especially true for epidemic diseases, </p><p>where we want to know the effects of different sorts of transmission, different control strategies, and so forth.</p><p><br></p><p>But what <em>is</em> a model of disease? How are they built, and what questions can we ask of them? This book tries to explain network-based epidemic</p><p>modelling through a unique combination of accessible text, introductory mathematics, and all the Python code needed to perform computational experiments that explore different disease models and countermeasures.</p><p><br></p><p>Written at the height of the 2020 covid-19 pandemic, the book aims to demystify the science that underlies many of the policy responses we</p><p>can make to disease outbreaks, and make the necessary experimental and analytical tools more accessible to anyone with an interest in science.</p><p><br>
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