Multiple sclerosis spatial cluster in Tuscany.

Tuscany (Central Italy) is a high-risk area for multiple sclerosis (MS) with a prevalence of 188 cases per 100,000 at 2011, and it is characterized by a heterogeneous geographic distribution of this disease. Our objective was to update prevalence at 2013 and to evaluate the presence of spatial clusters in Tuscany. The MS prevalence was evaluated on 31 December 2013 using a validated case-finding algorithm, based on administrative data. To identify spatial clusters, we calculated standardized morbidity ratios (SMRs) for each Tuscan administrative municipality. In addition to the classical approach, we applied the hierarchical Bayesian model to overcome random variability due to the presence of small number of cases per municipality. We identified 7330 MS patients (2251 males and 5079 females) with an overall prevalence of 195.4/100,000. The SMR for each Tuscan municipality ranged from 0 to 271.4, but this approach produced an extremely non-homogeneous map. On the contrary, the Bayesian map was much smoother than the classical one. The posterior probability (PP) map showed prevalence clusters in some areas in the province of Massa-Carrara, Pistoia, and Arezzo, and in the municipalities of Siena, Florence, and Barberino Val d'Elsa. Our prevalence data confirmed that Tuscany is a high-risk area, and we observed an increasing trend during the time. Using the Bayesian method, we estimated area-specific prevalence in each municipality reducing the random variation and the effect of extreme prevalence values in small areas that affected the classical approach.