Modeling a syphilis outbreak through space and time using the Bayesian maximum entropy approach.
PURPOSE: The aim of the study is to describe changes in the spatial distribution of syphilis before, during, and after an outbreak in Baltimore, MD, by using Bayesian maximum entropy (BME), a modern geostatistical technique for space-time analysis and mapping. METHODS: BME was used to conduct simple and composite space-time analyses of the density of syphilis infection based on primary, secondary and early latent syphilis cases reported to the Baltimore City Health Department between January 1, 1994, and December 31, 2002. RESULTS: Spatiotemporal covariance plots indicated that the distribution of the density of syphilis cases showed both spatial and temporal dependence. Temporally dependent disease maps suggested that syphilis increased within two geographic core areas of infection and spread outward. A new core area of infection was established to the northwest. As the outbreak waned, density diminished and receded in all core areas. Morbidity remained elevated in the two original central and new northwestern core areas after the outbreak. CONCLUSIONS: Density of syphilis infection was a simple informative measure easily compared across years. The BME approach was useful for quantitatively and qualitatively describing the spatial development and spread of syphilis. Our results are specific to Baltimore; however, the BME approach is generalizable to other settings and diseases.