Identifying Pediatric Cancer Clusters in Florida Using Log-Linear Models and Generalized Lasso Penalties

Abstract

We discuss the identification of pediatric cancer clusters in Florida between 2000 and 2010 using a penalized generalized linear model. More specifically, we introduce a Poisson model for the observed number of cases on each of Florida’s ZIP Code Tabulation Areas (ZCTA) and regularize the associated disease rate estimates using a generalized Lasso penalty. Our analysis suggests the presence of a number of pediatric cancer clusters during the period over study, with the largest ones being located around the cities of Jacksonville, Miami, Cape Coral/Fort Meyers, and Palm Beach.

KEY WORDS::

• Bregman Algorithm
• Fused Lasso
• Disease clustering
• Generalized Lasso
• Log-linear models
• Pediatric cancer
• Poisson regression