Daiana Bezzini

Estimated prevalence of multiple sclerosis in Italy in 2015

Italy is a high risk area for multiple sclerosis (MS) as confirmed by the numerous prevalence and incidence studies conducted in several regions/districts of the country. Nevertheless, there are no recent published epidemiological data, nor studies about the total prevalence of MS in Italy. Our aim was to update as of 2015 the prevalence rates of MS in different geographical areas using already published epidemiological studies, and to estimate the overall prevalence of the disease in Italy. We made a search in MEDLINE database of all published studies on epidemiology of MS in Italy. Then, we applied, to the already published prevalence data, the last published incidence and mortality rates to recalculate, as of 2015, the prevalence of MS. So, we calculated the mean prevalence rate from our extrapolations, and we applied it to the population in 2015 to estimate the number of MS patients in Italy. Our prevalence extrapolations ranged from 122 to 232 cases/100,000 in the mainland and Sicily, with an average of 176/100,000, and from 280 to 317 cases/100,000 in Sardinia with an average of 299/100,000. Applying these media to the Italian population in 2015, we obtained an estimate of more than 109,000 MS patients in Italy. Our estimates were higher than the latest published rates but consistent with the annual increase of prevalence due to incidence that exceeds mortality, with the increase of survival and, maybe, with the probable increase of incidence.

Prevalence of Multiple Sclerosis in Tuscany (Central Italy): A Study Based on Validated Administrative Data.

Background: Multiple Sclerosis (MS) epidemiology in Italy is mainly based on population-based prevalence studies. Administrative data are an additional source of information, when available, in prevalence studies of chronic diseases such as MS. The aim of our study is to update the prevalence rate of MS in Tuscany (central Italy) as at 2011 using a validated case-finding algorithm based on administrative data. Methods: The prevalence was calculated using an algorithm based on the following administrative data: hospital discharge records, drug-dispensing records, disease-specific exemptions from copayment to health care, home and residential long-term care and inhabitant registry. To test algorithm sensitivity, we used a true-positive reference cohort of MS patients from the Tuscan MS register. To test algorithm specificity, we used another cohort of individuals who were presumably not affected by MS. Results: As at December 31, 2011, we identified 6,890 cases (4,738 females and 2,152 males) with a prevalence of 187.9 per 100,000. The sensitivity of algorithm was 98% and the specificity was 99.99%. Conclusions: We found a prevalence higher than the rates present in literature. Our algorithm, based on administrative data, can accurately identify MS patients; moreover, the resulting cohort is suitable to monitor disease care pathways.

Multiple Sclerosis Epidemiology in Europe

Multiple sclerosis is characterized by a non-homogeneous distribution around the world. Some authors in past described a latitude gradient, with increasing risk from the equator to North and South Poles, but this theory is still controversial. Regarding Europe, there are many articles in the literature concerning the epidemiology of this disease but, unfortunately, they are not always comparable due to different methodologies, they do not cover all countries in the continent, and most of them reported data of small areas and rarely at a national level. In 2012 there were 20 national registries that could help to describe the epidemiology of the disease and, in addition, there is an European Register for Multiple Sclerosis that collect data from already existing national or regional MS registries and databases. Another valid alternative to obtain epidemiological data, also at national level, in a routinely and cost-saving way is through administrative data that are of increasing interest in the last years.

Multiple sclerosis incidence in Tuscany from administrative data

BackgroundItaly is a high-risk area for multiple sclerosis with 110,000 prevalent cases estimated at January 2016 and 3400 annual incident cases. To study multiple sclerosis epidemiology, it is preferable to use population-based studies, e.g., with a registry. A valid alternative to obtain data on entire population is from administrative sources.ObjectiveTo estimate the incidence of multiple sclerosis in Tuscany using a case-finding algorithm based on administrative data.MethodsIn a previous study, we calculated the prevalence in Tuscany using a validated case-finding algorithm based on administrative data. Incident cases were identified as a subset of prevalent cases among those patients not traced in the years before the analysis period, and the date of the first multiple sclerosis-related claim was considered the incidence date of multiple sclerosis diagnosis. We examined the period 2011–2015.ResultsWe identified 1147 incident cases with annual rates ranged from 5.60 per 100,000 in 2011 to 6.58 in 2015.ConclusionsWe found a high incidence rate, similarly to other Italian areas, especially in women, that may explain the increasing prevalence in Tuscany. To confirm this data and to calculate the possible bias caused by our inclusion method, we will validate our algorithm for incident cases.

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.

Automatic Vending-Machines Contamination: A Pilot Study

Hot-drinks vending machines are disseminated worldwide and millions of drinks are served every day. Because of a small number of studies on hot-drinks related illnesses, the aim of this pilot study was to identify the presence and load of bacterial species, potentially harmful for consumers, within hot-drinks vending machines external critical surfaces. This preliminary cross sectional study was carried out in April 2015 at the University of Siena, Italy. Samples were taken from the critical surfaces of 4 hot-drinks vending machines (VM); the analyzed VMs critical surfaces were: Dispense Areas, Nozzles and Glass-Holders. The samples were sown on selective culture media: Plate Count Agar (PCA) at 22°C and 36°C, Slanetz and Bartely Agar (SBA) and Mannitol Salt Agar (MSA). Total Viable Count (TVC) at 36°C and 22°C was assessed for mesophilic and psychrophilic contamination. Results were expressed in terms of average CFU/cm2. Descriptive and statistical analyses were performed in order to assess which surface was the most contaminated. The nozzles resulted to be the most contaminated critical surface, showing average values over the limits in all the culture media (PCA 36°C, PCA 22°C, MSA and SBA). The statistical analysis showed that the nozzles were significantly more contaminated (p <0.05) than Dispense Areas and Glass-holders both in PCA 36°C and in PCA 22°C. Given the high number of CFU/cm2, VM may constitute a potential threat for consumers health, reason for which further studies are recommendable.