Resources

Videos, books and web pages linked by the instructor, by session

Everything here is linked from the Canvas posts or the session slides. Optional material is marked as such; none of it is required reading unless the course says otherwise. Links open in a new tab.

Session 1 · Introduction to spatial epidemiology

Resource What it is Where in the app
John Snow and the 1854 cholera outbreak Story map used for the in-class activity (Center for Spatial Data Science, University of Chicago) 1.5
Download GeoDa Free software for exploratory spatial data analysis. Install before 13 October 1.14
Geocomputation with R Free online book: spatial data in R 1.14
Spatial Data Science with R Free online tutorials 1.14
CSDS R spatial tutorials Workshops from the Center for Spatial Data Science 1.14

Session 2 · Disease mapping and spatial patterns

Resource What it is Where in the app
Axis Maps: Data classification Short guide to quantile, equal-interval and natural-breaks maps (source of slide figures) 2.1
GeoDa workbook: Distance-based spatial weights Connectivity histograms and graphs (source of slide figures) 2.10
GeoDa workbook: Local spatial autocorrelation LISA significance and cluster maps (source of slide figures) 2.13

Session 3 · Introduction to spatial regression

Optional viewing (Canvas post): Luc Anselin, Applied Spatial Regression Analysis, the whole YouTube playlist. “These lectures provide a step-by-step introduction to spatial regression. They also cover more advanced topics that we will not have time to discuss in STA530.”

# Lecture Relevance for STA530 Where in the app
1 Spatial Regression Specifications Core: lag and error models 3.4
2 Spatial Process Models Core: what process each model assumes 3.8
3 2SLS Beyond the course 3.12
4 Spatial Durbin Model Beyond the course 3.12
5 Spatial Spillovers Core: direct, indirect and total impacts 3.5
6 Specification Tests Core: residual Moran’s I, LM tests 3.10
7 Robust Tests Core: robust LM tests 3.10
8 Principles of Maximum Likelihood Estimation Beyond the course 3.12
9 ML Estimation of Spatial Lag Model Beyond the course 3.12
10 GMM Estimation Principle Beyond the course 3.12
11 IV Estimation of Spatial Lag Model Beyond the course 3.12
12 ML Estimation Spatial Error Model Beyond the course 3.12
13 GMM Estimation of Spatial Error Model Beyond the course 3.12

“Core” means the lecture covers something STA530 teaches; “beyond the course” lectures cover what the session explicitly leaves out (estimation, IV/GMM, the Durbin model).

Session 4 · Introduction to Bayesian disease mapping

Resource What it is Where in the app
Gómez-Rubio, Bayesian Inference with INLA Free online book: latent Gaussian models, spatial models and their implementation in R. Optional, not required reading; the computational details of INLA are not expected 4.21

Articles cited on the slides

Links go to the publisher via the DOI; some need university access (log in through the GU library). None of these is listed as required reading.

Reference Cited for Where in the app
Morrison et al. (2024). Defining spatial epidemiology: a systematic review and re-orientation. Epidemiology 35(4):542–555 Describe → analyze → intervene; 0 intervention studies; broader definition. The most-used source in Session 1 1.6, 1.7
Elliott & Wartenberg (2004). Spatial epidemiology: current approaches and future challenges. Environmental Health Perspectives 112(9):998–1006 Definition of spatial epidemiology 1.6
Lawson (2018). Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology. CRC Press (book) Definition of spatial epidemiology 1.6
Nattinger et al. (2001). JNCI 93(17):1344–1346 Distance to care and breast cancer. The slide says “mammography facilities”; the paper studies distance to a radiotherapy facility and the choice of surgery 1.8
Gordon-Larsen et al. (2006). Inequality in the built environment underlies key health disparities in physical activity and obesity. Pediatrics 117(2):417–424 Built environment and obesity 1.8
McEntee & Ogneva-Himmelberger (2008). Diesel particulate matter, lung cancer, and asthma incidences along major traffic corridors. Health & Place 14(4):817–828 Traffic corridors and health. The slide says “cardiovascular disease”; the paper studies lung cancer and asthma 1.8
WHO (2010). A Conceptual Framework for Action on the Social Determinants of Health Social determinants of health 1.8
Schwartz, Susser & Susser (1999). A future for epidemiology? Annual Review of Public Health 20:15–33 Eco-epidemiology 1.8
Buck Louis & Sundaram (2012). Exposome: time for transformative research. Statistics in Medicine 31(22):2569–2575 Multiple exposures over the life span 1.8
Dahlberg & Krug (2002). Violence: a global public health problem. In World Report on Violence and Health, WHO Social-ecological model (with Bronfenbrenner 1994, no online version) 1.9
Diderichsen, Evans & Whitehead (2001). The social basis of disparities in health. In Challenging Inequities in Health, Oxford University Press Life-course mechanisms behind social inequality in health 1.9
Robinson (1950). Ecological correlations and the behavior of individuals. American Sociological Review 15(3):351–357 The ecological fallacy 1.11
Anselin (1995). Local indicators of spatial association—LISA. Geographical Analysis 27(2):93–115 LISA and local Moran’s I 2.13

Not linked: Openshaw (1984), The Modifiable Areal Unit Problem (CATMOG 38, no DOI); Bronfenbrenner (1994), encyclopedia chapter; O’Sullivan & Unwin (2002), Geographic Information Analysis (book).

Original papers behind the Session 4 models (named on the slides, not cited; for the curious only):

Reference Model
Besag, York & Mollié (1991). Annals of the Institute of Statistical Mathematics 43:1–20 BYM (4.11)
Riebler et al. (2016). An intuitive Bayesian spatial model for disease mapping that accounts for scaling. Statistical Methods in Medical Research 25(4):1145–1165 BYM2 (4.12)
Simpson et al. (2017). Penalising model component complexity. Statistical Science 32(1):1–28 PC priors (4.14)
Rue, Martino & Chopin (2009). Journal of the Royal Statistical Society B 71(2):319–392 INLA (4.21)

Course books

From the literature list (not online):

  • Lawson, Banerjee, Haining & Ugarte (eds.) (2016). Handbook of Spatial Epidemiology. CRC Press. Main textbook.
  • Anselin (2024). An Introduction to Spatial Data Science with GeoDa, Volume 1: Exploring Spatial Data. Chapman & Hall/CRC. Chapters 1–7, 10, 13 and 16.