We developed a web-based site placement calculator to aid public health officials in designing their surveillance system. We then compare the two algorithmic site placement schemes against each other by simulating the spread of influenza across the state of Iowa. Our simulations are based on an Iowa Medicaid dataset comprised two million cases classified with 30 different ILI ICD-9 codes and their corresponding geocodes from 2000 to 2008. We use the Huff Model (3) to determine whether or not a case might have been detected by a particular network of sites. Using this scheme, we compare surveillance networks based on outbreak intensity (i.e., which networks detect the highest percentage of cases) and outbreak timing (i.e., which networks detect cases temporally in sync with the true start, peak and end of the disease season). To compare network outbreak timing, we generate the noise parameters of a state space time series model using the expectationmaximization (EM) algorithm implementation provided by Shumway and Stoffer (4). We then perform an analysis on which ICD-9 codes a network might consider.