Early Detection of Tuberculosis Outbreaks Among the San Francisco Homeless: Trade-offs Between Spatial Resolution and Temporal Scale

San Francisco has the highest rate of tuberculosis (TB) in the US. Exact locations of patients' primary residences at the time of diagnoses are routinely collected as part of the TB surveillance program. It has been shown for syndromic surveillance data that when exact geographic coordinates of individual patients are used, higher detection rates and accuracy are achieved compared to when data are aggregated into administrative regions such as zip codes and census tracts. Here, we examine the effect of varying the spatial resolution in the TB data on the San Francisco homeless population, on detection sensitivity, timeliness, and the amount of historical data needed to achieve better performance measures.