During the ongoing pandemic, a lot of claims are being put forward on social media about the disease, how it spreads and what public health measures should be put in place. It can often be difficult for laypeople to navigate such claims if they do not have a robust background in epidemiology.
Simplified, epidemiology is the study of the distribution and causes of diseases as well as how to prevent them. There are many questions that are of interest in epidemiology: How can molecular epidemiology and public health genetics help us understand the spread of infectious diseases? How did researchers defeat smallpox? What steps did science show was effective to curbing diseases associated with a deficiency in iodine? How was it discovered that smoking causes cancer? The katter us a fascinating story of scientific discovery, mathematics and deceptive tobacco companies.
What is the difference between incidence and prevalence and how do you calculate them? What is a nested case-control study? What is a confounder and why is it important to adjust for them in epidemiological research? The latter is an issue that have plagued many scientific studies. Researchers might think they have found a robust association between some disease and some other trait, but future research might show that it was actually due to some other factor that correlated with both the disease and the trait.
What are the different kinds of screening types? Why is dose-response relationship effective? How do you set reasonable safety standards in the workplace? What is the health planning cycle and how does it work? What is the difference between risk difference, attributable fraction, relative risk and odds ratio? What is the ecological fallacy and how can it be avoided?
Basic Epidemiology is a textbook in epidemiology now in its second edition written by Bonita, Beaglehole and Kjellström that was published by the World Health Organization in 2006. The PDF of the textbook can be accessed directly by going here. It turns out that this textbook is also available in a multitude of other languages such as German, Swedish, Japanese, Persian, Italian, Polish and Portugese.
With over 200 pages and 11 chapters, it covers the historical context of epidemiology, major achievements of the field, how to measure how common diseases are, different study designs and their limitations, the basic tools of biostatistics, how to argue for causation in epidemiology, preventing chronic, non-infectious diseases, surveilling and responding to infectious diseases as well as epidemiology in the clinic, in the workplace, in the environment and political policy.
What makes this textbook stand apart from others? They have a detailed and readable section describing some of the achievements that epidemiology has reached, such as defeating smallpox, uncovering methyl mercury poisoning, rheumatic fever, iodine deficiency, smoking and lung cancer, HIV/AIDS and SARS.
One of the best features is the emphasis they put on the difference between correlation and causation. They pay great attention to the difference between correlation and causation, looking into the Bradford Hill criteria for making causation a more reasonable conclusion.
This is perhaps one of the most important things to keep in mind when evaluating claims about health and disease on the Internet. Is the proposed cause really a cause or just something that for some reason happen to correlate with the disease in question?
These criteria include if the cause exists before the effect, if the mechanism is plausible, if the causation model is supported by independent studies, how strong the association is, if a higher dose of the cause leads to a increased effect, evaluation of the study design and so on. These criteria should always be kept in mind when evaluation epidemiological studies and claims about epidemiology on social media.
It also focuses on the different kinds of errors, biases and confounding that can affect epidemiology studies. Another valuable aspect of the book is that it features a section on how to make your own research project, from writing the protocol to getting published.
A cache of the PDF version can be found here. This book will equip readers with a solid foundation in epidemiology and allow them to scale more difficult topics and books in the subject. Hopefully, it can also boost the ability of people to protect themselves against disinformation about epidemiology, diseases and the new coronavirus pandemic on the Internet.
For those interested in epidemiology in the context of vaccines, check out Epidemiology and Prevention of Vaccine-Preventable Diseases. The story of How Science Found the Cause of the 2010 Cholera Outbreak in Haiti is a great case study in the use of modern DNA sequencing techniques in the hunt for the source of a devastating outbreak that adds a great dose of practical information to the theoretical knowledge gained fro this book. A crucial concept needed to understand the natural history of outbreaks is herd immunity and provides a basic review of the concept. More details information is also available about specific diseases such as the Introduction to Dengue Fever Textbook, the review paper about HIV Denial in the Internet Era. To get a better understanding of anti-vaccine activism in the United States, checkout The Vaccine War documentary.