Implementing a Weighted Spatial Smoothing Algorithm to Identify a Lung Cancer Belt in the United States
Lung cancer is the leading cause of cancer death in the United States, but a large fraction of cases is preventable. We use a spatial smoothing algorithm to identify a geographic pattern of high lung cancer mortality, primarily in the Southeast, which we call a lung cancer belt. Disease belts are an effective mode for conveying patterns of high incidence or mortality; formally defining this lung cancer belt may encourage increased public dialogue and more focused research. Public health officials could complement existing population lung cancer data with this information to help inform resource allocation decisions.
Blackley, David; Zheng, Shimin; and Ketchum, Winn. 2012. Implementing a Weighted Spatial Smoothing Algorithm to Identify a Lung Cancer Belt in the United States. Cancer Epidemiology. Vol.36(5). 436-438. https://doi.org/10.1016/j.canep.2012.05.015 ISSN: 1877-7821