Preface

Hi, and welcome! I truly appreciate you taking the time to look over this work of mine. This digital book is designed to serve as a reference covering essential concepts that everyone working in epidemiology should know. We will explore some (minimal) theoretical epidemiology and examine various epidemiological concepts through real-world disease scenarios. After introducing how R works and how it can be applied across many areas of public health, we will discuss how to access and manage epidemiological data. Finally, we’ll bring everything together so that, regardless of your background, you’ll gain a solid foundational experience in epidemiology using R, enabling you to confidently dive deeper into this fascinating field.

Public health is a prime example of a multidisciplinary arena where diverse scientific fields converge. The One Health approach, in particular, not only connects different disciplines but also encourages multiple perspectives on the same issue. For example, a medical doctor may view a mosquito as a vector transmitting disease, while an ecologist might see it as an invasive species indicating changing habitat suitability, perhaps due to global warming. Although One Health experts recognize the importance of interdisciplinary collaboration and education, this integration often falls short when it comes to computers and data. This is precisely the gap this material aims to bridge.

While this reader covers fundamental topics in epidemiology and R, it will gradually expand to include more advanced and diverse content of interest to a wide audience. For readers already familiar with R and data analysis, I will occasionally provide suggestions for further reading, highlight useful R packages, and touch upon emerging fields where epidemiology intersects with disciplines like machine learning.

As this is a first draft intended as background material for a future course, I warmly welcome your feedback! Please feel free to share your thoughts by emailing me.