We used data from the MMWR. It contains weekly syphilis counts per state. We consider the time period from 1995 to 2009. We removed week 53 when present, due to inconsistencies in reporting. We considered 53 locations: the 50 states plus Puerto Rico, and the cities of New York City and Washington DC. To predict disease activity in each state, we constructed a series of linear lagged regression models that used several states as covariates. To benchmark our models, we constructed a basic ARIMA model with one autocorrelation term. All the models were constructed to forecast 4 weeks in advance. Prediction at week t was performed by fitting the models using all past data prior to week tÁ4. To identify bellwether states, we proceeded as follows. First, we repeatedly fitted 2-covariate models to forecast each state and obtained the top 5 most frequent bellwether states for each state. Then, we obtained the most frequent bellwether states from the above lists.