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Main: Spatial Epidemiology at Boston University School of Public Health

The Spatial Epidemiology Group at Boston University School of Public Health has several interests:

Disease Mapping and Clusters
Disease registry data are often mapped by town or county of diagnosis and contain limited data on possible confounders. These maps often possess poor spatial resolution, the potential for spatial confounding, and the inability to consider latency. Population-based case-control studies can, on the other hand, provide detailed information on residential history and covariates. We are developing and applying methods for mapping case-control and cohort data while adjusting for risk factors and latency. We map point patterns using generalized additive models (GAMs), a statistical framework which allows us to analyze binary outcome data, adjust for covariates, smooth on space (with optimal degree of smoothing), and perform hypothesis tests. For example, the map on the left above shows breast cancer risk at the time of diagnosis; the map on the right shows maps residential location twenty years prior to diagnosis. Our latest work has focused on time-space clustering.

Ecologic bias
Individual-level studies collect information on exposure, outcome and covariates for each individual; purely ecologic studies collect group-level (aggregate) information for these variables. Ecologic bias can occur when aggregate data are used to make inferences about individuals. We are interested in comparing the direction and magnitude of ecologic bias compared with biases occuring on the individual-level. Such information is useful in designing ecologic studies, doing sensitivity analyses of ecologic studies, and understanding what happens when a group-level variable is used in an otherwise individual-level study (e.g., as a proxy for exposure on the individual-level). For more information, look here.

Multi-level studies
Many diseases are associated with an individual's socioeconomic status (SES), also known as socioeconomic position (SEP). Community level SES is often associated with disease risk as well. However, despite our knowledge of these separate associations, most previous research has not examined individual and community SES simultaneously. As a result, it is unclear if the greater disease incidence in certain communities is related to the SES of the individuals who live there (composition) or because some aspect of living in a the community confers a greater risk of disease, regardless of their SES (context). A recent paper investigated this question for breast cancer on Cape Cod.

News & Awards (For details, look here)

Recent publications:

Recent conference presentations:

Upcoming conferences

Recent conferences

How do we make these maps?
We subscribe to the philosophy of the BU Superfund Research Program (BUSRP) to which we are also connected, i.e., making results and products freely available where possible through open-access publications and open source software available under general public license. We are currently creating maps using S-Plus (to calculate surfaces using GAMs) and ArcView (for mapping the surfaces). R may provide a useful alternative for gams. Our code is freely available, as is some synthetic data for trying it out: here. See also our BUSRP research translation core.

View a movie of breast cancer time-space analysis
The movie shows the risk of breast cancer diagnosis 1983-1993 based on residential history on upper Cape Cod discussed in our new publication, Vieira et al 2008. The movie is a Windows Media file (1 mb). Click to view

Spatial Epidemiology Group at Boston University School of Public Health

Where are we?

For more information:
email: Dr. Tom Webster, Dept. Environmental Health

return to Tom Webster

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Page last modified on August 23, 2010, at 09:59 PM