Some light summer reading in spatial epidemiology

01 May 2018

I just finished teaching my first course at Michigan, which was called Theory and Applications of Spatial Epidemiology. At the end of the term, one of the students asked for suggestions for further reading.

Like so many topics in public health and the social sciences, ‘spatial epidemiology’ turned out to be an idea that only got blurrier and blurrier the more time I spent trying to explain what it was specifically: it involves space, place, inequality, environmental and climatic variation, and on and on and on. This made picking readings for the term - and beyond - more of a challenge than I had anticipated, although mostly in a good way.

In any event, the resulting list is eclectic and I thought potentially worth sharing here. Many of these books do not brand themselves as being either spatial or necessarily even epidemiological in nature. But what they share is a contribution to a way of thinking about how healthy or unhealthy places emerge and are sustained, whether that relates to specific diseases (e.g. TB) or to clusters of risks that may connect multiple (infectious and non-communicable) diseases.

In many ways, I have found these more useful than specific analyses for shaping the kinds of questions I think are useful and answerable:

A long view:

• Angus Deaton. (2015). The Great Escape: Health, Wealth, and the Origins of Inequality.

Very interesting takes on TB and its relationship to urban inequality:

• Samuel Kelton Roberts. (2009). Infectious Fear: Politics, Disease, and the Health Effects of Segregation.

• Deborah Wallace & Rodrick Wallace. (2001). A Plague on Your Houses: How New York Was Burned Down and National Public health Crumbled.

Something of a challenge to ‘vertical’ ideas in development and public health:

• The Idealist: Jeffrey Sachs and the Quest to End Poverty.

The only way I can describe this one is as a ‘Tao of Pooh’ for ecologists and epidemiologists. Not sure if its authors would agree with that characterization, but to me this book was foundational for thinking about ecological modeling as a kind of adventure and mindset, and it has kept me going at moments of frustration:

• Ray Hilborn & Marc Mangel. (2001). The Ecological Detective: Confronting Models with Data.

Finally for hands-on learning of spatial (and other) analysis in R:

• Chris Brundson & Lex Comber. (2016). An Introduction to R for Spatial Analysis.

• Hadley Wickham. (2016). R for Data Science.

Feel free to make other suggestions below if you see anything else that should be on the list!