Insights for brucellosis eradication in Italy through a model-based spread evaluation in grazing livestock - Sicily case study.

Brucellosis is one of the world's major zoonotic pathogens and is responsible for enormous economic losses as well as considerable human morbidity in endemic areas. Definitive control of human brucellosis requires control of brucellosis in livestock through practical solutions that can be easily applied to the field. In Italy, brucellosis remains endemic in several southern provinces, particularly in Sicily Region. The purpose of this paper is to describe the developed brucellosis model and its applications, trying to reproduce as faithfully as possible the complex transmission process of brucellosis accounting for the mixing of grazing animals. The model focuses on the contaminated environment rather than on the infected animal, uses real data from the main grazing areas of the Sicily Region, and aims to identify the best control options for minimizing the spread (and the prevalence) and to reach the eradication within the concerned areas. Simulation results confirmed the efficacy of an earlier application of the controls, showed the control should take place 30 days after going to pasture, and the culling time being negligible. Moreover, results highlighted the importance of the timing of both births and grazing pastures (and their interaction) more than other factors. As these factors are region­specific, the study encourages the adoption of different and new eradication tools, tuned on the grazing and commercial behavior of each region. This study will be further extended to improve the model's adaptability to the real world, with the purpose of making the model an operational tool able to help decision makers in accelerating brucellosis eradication in Italy.

Culex pipiens distribution in Tunisia: Identification of suitable areas through Random Forest and MaxEnt approaches.

BACKGROUND: Tunisia has experienced several West Nile virus (WNV) outbreaks since 1997. Yet, there is limited information on the spatial distribution of the main WNV mosquito vector Culex pipiens suitability at the national level. OBJECTIVES: In the present study, our aim was to predict and evaluate the potential and current distribution of Cx. pipiens in Tunisia. METHODS: To this end, two species distribution models were used, i.e. MaxEnt and Random Forest. Occurrence records for Cx. pipiens were obtained from adult and larvae sampled in Tunisia from 2014 to 2017. Climatic and human factors were used as predictors to model the Cx. pipiens geographical distribution. Mean decrease accuracy and mean decrease Gini indices were calculated to evaluate the importance of the impact of different environmental and human variables on the probability distribution of Cx. pipiens. RESULTS: Suitable habitats were mainly distributed next to oases, in the north and eastern part of the country. The most important predictor was the population density in both models. The study found out that the governorates of Monastir, Nabeul, Manouba, Ariana, Bizerte, Gabes, Medenine and Kairouan are at highest epidemic risk. CONCLUSIONS: The potential distribution of Cx. pipiens coincides geographically with the observed distribution of the disease in humans in Tunisia. Our study has the potential for driving control effort in the fight against West Nile vector in Tunisia.

Epidemiological and genomic findings of the first documented Italian outbreak of SARS-CoV-2 Alpha variant of concern.

From 24 December 2020 to 8 February 2021, 163 cases of SARS-CoV-2 Alpha variant of concern (VOC) were identified in Chieti province, Abruzzo region. Epidemiological data allowed the identification of 14 epi-clusters. With one exception, all the epi-clusters were linked to the town of Guardiagrele: 149 contacts formed the network, two-thirds of which were referred to the family/friends context. Real data were then used to estimate transmission parameters. According to our method, the calculated Re(t) was higher than 2 before the 12 December 2020. Similar values were obtained from other studies considering Alpha VOC. Italian sequence data were combined with a random subset of sequences obtained from the GISAID database. Genomic analysis showed close identity between the sequences from Guardiagrele, forming one distinct clade. This would suggest one or limited unspecified viral introductions from outside to Abruzzo region in early December 2020, which led to the diffusion of Alpha VOC in Guardiagrele and in neighbouring municipalities, with very limited inter-regional mixing.

Epidemiological and Evolutionary Analysis of West Nile Virus Lineage 2 in Italy.

West Nile virus (WNV) is a mosquito-borne virus potentially causing serious illness in humans and other animals. Since 2004, several studies have highlighted the progressive spread of WNV Lineage 2 (L2) in Europe, with Italy being one of the countries with the highest number of cases of West Nile disease reported. In this paper, we give an overview of the epidemiological and genetic features characterising the spread and evolution of WNV L2 in Italy, leveraging data obtained from national surveillance activities between 2011 and 2021, including 46 newly assembled genomes that were analysed under both phylogeographic and phylodynamic frameworks. In addition, to better understand the seasonal patterns of the virus, we used a machine learning model predicting areas at high-risk of WNV spread. Our results show a progressive increase in WNV L2 in Italy, clarifying the dynamics of interregional circulation, with no significant introductions from other countries in recent years. Moreover, the predicting model identified the presence of suitable conditions for the 2022 earlier and wider spread of WNV in Italy, underlining the importance of using quantitative models for early warning detection of WNV outbreaks. Taken together, these findings can be used as a reference to develop new strategies to mitigate the impact of the pathogen on human and other animal health in endemic areas and new regions.

Environmental temperature and relative humidity differently affect the sperm characteristics in Brown Swiss and Belgian Blue bulls.

In a temperature-increasing scenario, due to global warming, the individual thermic resilience of the male assumes a crucial role in the reproductive efficiency of a male since the thermic stress, such as the inability of the male to reduce body or regional temperature on a physiological level, impairs testicular function. In this study, the effect of the environmental conditions on the fresh semen quality, in terms of volume, concentration, total sperm in the ejaculate, total motility, normal morphology, membrane integrity, and discarding rate, were compared longitudinally in Belgian Blue (BB) and Brown Swiss (BS) bulls. The environmental conditions, summarized in the mean temperature-humidity index (THI), were calculated on the day of collection, as well as 7 days (epididymal maturation), 35 days (late spermatogenesis), and 70 days (early spermatogenesis) before the collection, to reflect spermatogenesis time. Our findings showed that limited seasonal effects were present in the semen quality of BS bulls. On the other hand, in BB bulls lower semen quality was found between July and November, with a different timing depending on the seminal parameter. This effect of the season on BB semen parameters appears to be related to the THI. The data presented in this study shows that the temperature and humidity, summarized in THI, could affect the semen quality of the bull on breed basis, given that volume, concentration, total sperm in the ejaculate, total motility, membrane integrity, and sperm normal morphology were significantly reduced by an increasing THI in the Belgian Blue bulls, but not in Brown Swiss bulls.

A Municipality-Based Approach Using Commuting Census Data to Characterize the Vulnerability to Influenza-Like Epidemic: The COVID-19 Application in Italy.

In February 2020, Italy became the epicenter for COVID-19 in Europe, and at the beginning of March, the Italian Government put in place emergency measures to restrict population movement. Aim of our analysis is to provide a better understanding of the epidemiological context of COVID-19 in Italy, using commuting data at a high spatial resolution, characterizing the territory in terms of vulnerability. We used a Susceptible-Infectious stochastic model and we estimated a municipality-specific infection contact rate () to capture the susceptibility to the disease. We identified in Lombardy, Veneto and Emilia Romagna regions (52% of all Italian cases) significant clusters of high , due to the simultaneous presence of connections between municipalities and high population density. Local simulated spreading in regions, with different levels of infection observed, showed different disease geographical patterns due to different values and commuting systems. In addition, we produced a vulnerability map (in the Abruzzi region as an example) by simulating the epidemic considering each municipality as a seed. The result shows the highest vulnerability values in areas with commercial hubs, close to the highest populated cities and the most industrial area. Our results highlight how human mobility can affect the epidemic, identifying particular situations in which the health authorities can promptly intervene to control the disease spread.

Validation via challenge test of a dynamic growth-death model for the prediction of Listeria monocytogenes kinetics in Pecorino di Farindola cheese.

Pecorino di Farindola is a typical cheese produced in the area surrounding the village of Farindola, located in the Abruzzo Region (central Italy), unique among Italian cheese because only raw ewe milk and pig rennet are used for its production. In the literature it is well documented that raw milk is able to support the growth of pathogenic microorganisms such as Listeria monocytogenes. Predictive microbiology can be useful in order to predict growth-death kinetics of pathogenic bacteria, on the basis of known environmental conditions. Aim of this study was to compare predictions obtained from a model, originally designed to predict the kinetics of L. monocytogenes in the dynamic growth-death environment of drying fresh sausage, with the results of challenge tests performed during the ripening of Pecorino di Farindola produced from artificially contaminated raw ewe milk. A challenge test was carried out using ewe raw milk inoculated with L. monocytogenes, in order to produce Pecorino di Farindola cheese stored at 18 °C for 149 days of ripening. During the ripening period, pH and aw values decreased in all samples analysed; lactic acid bacteria become the prevailing microbial population, while for L. monocytogenes a period of stability (neither growth nor death) followed the initial situation. The growth inhibition and the following inactivation may mostly be due to competition with the autochthonous microbiota and to the reduction of water activity. Mathematical modelling was used in order to predict microbial kinetics in the dynamic ripening environment, joining growth and death patterns in a continuous way, and including the highly uncertain growth/no growth range separating the two regions. The effect of lactic acid bacteria on the growth of pathogens was also included. Predicted microbial kinetics were satisfactory, as confirmed by the absence of statistically significant difference between observed and predicted values (p > 0.05). The present study proved, via challenge tests, that a dynamic growth/death model, previously used for a meat product, can be fruitfully used in cheese characterized by active competitive microbiota and progressive drying during ripening.

EpiExploreR: A Shiny Web Application for the Analysis of Animal Disease Data.

Emerging and re-emerging infectious diseases are a significant public and animal health threat. In some zoonosis, the early detection of virus spread in animals is a crucial early warning for humans. The analyses of animal surveillance data are therefore of paramount importance for public health authorities to identify the appropriate control measure and intervention strategies in case of epidemics. The interaction among host, vectors, pathogen and environment require the analysis of more complex and diverse data coming from different sources. There is a wide range of spatiotemporal methods that can be applied as a surveillance tool for cluster detection, identification of risk areas and risk factors and disease transmission pattern evaluation. However, despite the growing effort, most of the recent integrated applications still lack of managing simultaneously different datasets and at the same time making available an analytical tool for a complete epidemiological assessment. In this paper, we present EpiExploreR, a user-friendly, flexible, R-Shiny web application. EpiExploreR provides tools integrating common approaches to analyze spatiotemporal data on animal diseases in Italy, including notified outbreaks, surveillance of vectors, animal movements data and remotely sensed data. Data exploration and analysis results are displayed through an interactive map, tables and graphs. EpiExploreR is addressed to scientists and researchers, including public and animal health professionals wishing to test hypotheses and explore data on surveillance activities.

Defining ecological regions in Italy based on a multivariate clustering approach: A first step towards a targeted vector borne disease surveillance.

Ecoregionalization is the process by which a territory is classified in similar areas according to specific environmental and climatic factors. The climate and the environment strongly influence the presence and distribution of vectors responsible for significant human and animal diseases worldwide. In this paper, we developed a map of the eco-climatic regions of Italy adopting a data-driven spatial clustering approach using recent and detailed spatial data on climatic and environmental factors. We selected seven variables, relevant for a broad set of human and animal vector-borne diseases (VBDs): standard deviation of altitude, mean daytime land surface temperature, mean amplitude and peak timing of the annual cycle of land surface temperature, mean and amplitude of the annual cycle of greenness value, and daily mean amount of rainfall. Principal Component Analysis followed by multivariate geographic clustering using the k-medoids technique were used to group the pixels with similar characteristics into different ecoregions, and at different spatial resolutions (250 m, 1 km and 2 km). We showed that the spatial structure of ecoregions is generally maintained at different spatial resolutions and we compared the resulting ecoregion maps with two datasets related to Bluetongue vectors and West Nile Disease (WND) outbreaks in Italy. The known characteristics of Culicoides imicola habitat were well captured by 2/22 specific ecoregions (at 250 m resolution). Culicoides obsoletus/scoticus occupy all sampled ecoregions, according to its known widespread distribution across the peninsula. WND outbreak locations strongly cluster in 4/22 ecoregions, dominated by human influenced landscape, with intense cultivations and complex irrigation network. This approach could be a supportive tool in case of VBDs, defining pixel-based areas that are conducive environment for VBD spread, indicating where surveillance and prevention measures could be prioritized in Italy. Also, ecoregions suitable to specific VBDs vectors could inform entomological surveillance strategies.

Farm productive contexts and the dynamics of bovine viral diarrhea (BVD) transmission.

Bovine viral diarrhea (BVD) is a viral disease that affects cattle and that is endemic to many European countries. It has a markedly negative impact on the economy, through reduced milk production, abortions, and a shorter lifespan of the infected animals. Cows becoming infected during gestation may give birth to Persistently Infected (PI) calves, which remain highly infective throughout their life, due to the lack of immune response to the virus. As a result, they are the key driver of the persistence of the disease both at herd scale, and at the national level. In the latter case, the trade-driven movements of PIs, or gestating cows carrying PIs, are responsible for the spatial dispersion of BVD. Past modeling approaches to BVD transmission have either focused on within-herd or between-herd transmission. A comprehensive portrayal, however, targeting both the generation of PIs within a herd, and their displacement throughout the country due to trade transactions, is still missing. We overcome this by designing a multiscale metapopulation model of the spatial transmission of BVD, accounting for both within-herd infection dynamics, and its spatial dispersion. We focus on Italy, a country where BVD is endemic and seroprevalence is very high. By integrating simple within-herd dynamics of PI generation, and the highly-resolved cattle movement dataset available, our model requires minimal arbitrary assumptions on its parameterization. We use our model to study the role of the different productive contexts of the Italian market, and test possible intervention strategies aimed at prevalence reduction. We find that dairy farms are the main drivers of BVD persistence in Italy, and any control strategy targeting these farms would lead to significantly higher prevalence reduction, with respect to targeting other production compartments. Our multiscale metapopulation model is a simple yet effective tool for studying BVD dispersion and persistence at country level, and is a good instrument for testing targeted strategies aimed at the containment or elimination of this disease. Furthermore, it can readily be applied to any national market for which cattle movement data is available.

Network-based assessment of the vulnerability of Italian regions to bovine brucellosis.

The endemic circulation of bovine brucellosis in cattle herds has a markedly negative impact on economy, due to decreased fertility, increased abortion rates, reduced milk and meat production. It also poses a direct threat to human health. In Italy, despite the long lasting efforts and the considerable economic investment, complete eradication of this disease still eludes the southern regions, as opposed to the northern regions that are disease-free. Here we introduced a novel quantitative network-based approach able to fully exploit the highly resolved databases of cattle trade movements and outbreak reports to yield estimates of the vulnerability of a cattle market to brucellosis. Tested on the affected regions, the introduced vulnerability indicator was shown to be accurate in predicting the number of bovine brucellosis outbreaks (Spearman r= 0.82, p= 0.04), thus confirming the suitability of our tool for epidemic risk assessment. We evaluated the dependence of regional vulnerability to brucellosis on a set of factors including premises spatial distribution, trading patterns, farming practices, herd market value, compliance to outbreak regulations, and exploring different epidemiological conditions. Animal trade movements were identified as a major route for brucellosis spread between farms (r=0.85,p<10-5 between vulnerability and number of inbound movements), with an additional potential risk attributed to the use of shared pastures (r=0.4,p=0.04). By comparing the vulnerability of disease-free regions in the north to affected regions in the south, we found that more intense trade and higher market value of the cattle sector in the north (r=0.56,p=0.01) likely inducing more efficient biosafety measures, together with poor compliance to trade restrictions following outbreaks in the south were key factors explaining the diverse success in eradicating brucellosis. Our modeling scheme is both synthetic and effective in gauging regional vulnerability to brucellosis persistence. Its general formulation makes it adaptable to other diseases and host species, providing a useful tool for veterinary epidemiology and policy assessment.

Intake estimates of dioxins and dioxin-like polychlorobiphenyls in the Italian general population from the 2013-2016 results of official monitoring plans in food.

The implementation of the European Union strategy for polychlorodibenzo-dioxins and -furans (PCDD/Fs), and dioxin-like polychlorobiphenyls (DL-PCBs) is determining a general reduction of their presence in the environment and in the food chain. The most important route for human exposure to these substances is food consumption and, as a consequence, a progressive decrease of their dietary intake has been observed in the last decades. In this context, it seemed worth updating the PCDD/F and DL-PCB intake estimation for the Italian population. A total of 2659 samples of food of animal and vegetable origin analyzed for PCDD/Fs and DL-PCBs in the period 2013-2016 by accredited official laboratories and the national food consumption database were considered for the dietary intake assessment in different age groups of the Italian general population The median cumulative intake estimates expressed as pg WHO-TEQ/kg body weight per day and computed with a deterministic and a probabilistic approach were 1.40-1.52 for children, 0.82-0.85 for adolescents, and 0.64-0.61 for adults, respectively. Such results confirm the decreasing trend of PCDD/F and DL-PCB dietary intake even though the Tolerable Daily Intake (TDI) value of 2 WHO-TEQ/kg body weight per day is exceeded at the 95th percentile for all age groups, with children as sensitive group. Most contributing food categories to the intake resulted fish, food of vegetable origin, and cheese. A sensitivity analysis was also performed to calculate the target contamination levels able to keep the dietary exposure below the TDI. Computed target levels fall between P50 and P97 of the occurrence distribution of the main food groups, meaning that most of the Italian food production can be considered safe.

A New Weighted Degree Centrality Measure: The Application in an Animal Disease Epidemic.

In recent years researchers have investigated a growing number of weighted heterogeneous networks, where connections are not merely binary entities, but are proportional to the intensity or capacity of the connections among the various elements. Different degree centrality measures have been proposed for this kind of networks. In this work we propose weighted degree and strength centrality measures (WDC and WSC). Using a reducing factor we correct classical centrality measures (CD) to account for tie weights distribution. The bigger the departure from equal weights distribution, the greater the reduction. These measures are applied to a real network of Italian livestock movements as an example. A simulation model has been developed to predict disease spread into Italian regions according to animal movements and animal population density. Model's results, expressed as infected regions and number of times a region gets infected, were related to weighted and classical degree centrality measures. WDC and WSC were shown to be more efficient in predicting node's risk and vulnerability. The proposed measures and their application in an animal network could be used to support surveillance and infection control strategy plans.

Analysis of climatic factors involved in the BTV-1 incursion in Central Italy in 2014.

In 2012, six years after the previous epidemic, Bluetongue virus serotype 1 (BTV-1) re-emerged in Sardinia causing a limited number of outbreaks. Due to impossibility of implementing a vaccination campaign, the BTV-1 then spread all over the island in 2013 with about 7,000 outbreaks and, in September 2013, the virus reached Central Italy, with a limited number of outbreaks located along the Tyrrhenian coast. The surveillance system in place in Italy detected viral circulation during the following winter, when a few seroconversions were notified. Starting from mid July 2014, a huge number of outbreaks were reported and the disease spread toward inland territories, affecting Umbria, Abruzzo and Marche. In 2014, BTV-1 affected areas where Culicoides species belonging to the Obsoletus and Pulicaris complexes were identified as main vectors. The analysis of temperature and rainfall in Central Italy revealed a significant warmer winter (2013-2014) and a cooler and rainy summer season (2014). These climatic aspects might have certainly favored the overwintering of the virus in local vector or host populations in the Tyrrhenian coast, and, then, the spread of the virus to the rest of Central Italy. However, the heavy circulation of BTV-1 and the severity of clinical outbreaks recorded leave a number of 'open questions' that are currently under investigations.

Tracing Back Clinical Campylobacter jejuni in the Northwest of Italy and Assessing Their Potential Source.

Food-borne campylobacteriosis is caused mainly by the handling or consumption of undercooked chicken meat or by the ingestion of contaminated raw milk. Knowledge about the contributions of different food sources to gastrointestinal disease is fundamental to prioritize food safety interventions and to establish proper control strategies. Assessing the genetic diversity among Campylobacter species is essential to our understanding of their epidemiology and population structure. We molecularly characterized 56 Campylobacter jejuni isolates (31 from patients hospitalized with gastroenteritis, 17 from raw milk samples, and 8 from chicken samples) using multilocus sequence typing (MLST) and pulsed-field gel electrophoresis (PFGE) in order to trace the source of the disease. We also used a population genetic approach to investigate the source of the human cases from six different reservoirs of infection. MLST identified 25 different sequence types and 11 clonal complexes (CCs) (21, 658, 206, 353, 443, 48, 61, 257, 1332, 354, 574) and these included several alleles not cited previously in the PubMLST international database. The most prevalent CCs were 21, 206, and 354. PFGE showed 34 pulsotypes divided between 28 different clusters. At the fine scale, by means of PFGE and MLST, only two human cases were linked to raw milk, while one case was linked to chicken meat. The investigation revealed the presence of several genotypes among the human isolates, which probably suggests multiple foci for the infections. Finally, the source attribution model we used revealed that most cases were attributed to chicken (69.75%) as the main reservoir in Italy, followed to a lesser extent by the following sources: cattle (8.25%); environment (6.28%); wild bird (7.37%); small ruminant (5.35%), and pork (2.98%). This study confirms the importance of correlating epidemiological investigations with molecular epidemiological data to better understand the dynamics of infection.

Outbreak of unusual Salmonella enterica serovar Typhimurium monophasic variant 1,4 [5],12:i:-, Italy, June 2013 to September 2014.

Monophasic variant of Salmonella enterica subspecies enterica serovar Typhimurium (monophasic S. Typhimurium), with antigenic structure 1,4,[5],12:i:-, appears to be of increasing importance in Europe. In Italy, monophasic S. Typhimurium represented the third most frequent Salmonella serovar isolated from human cases between 2004 and 2008. From June 2013 to October 2014, a total of 206 human cases of salmonellosis were identified in Abruzzo region (Central Italy). Obtained clinical isolates characterised showed S. Typhimurium 1,4,[5],12:i:- with sole resistance to nalidixic acid, which had never been observed in Italy in monophasic S. Typhimurium, neither in humans nor in animals or foods. Epidemiological, microbiological and environmental investigations were conducted to try to identify the outbreak source. Cases were interviewed using a standardised questionnaire and microbiological tests were performed on human as well as environmental samples, including samples from fruit and vegetables, pigs, and surface water. Investigation results did not identify the final vehicle of human infection, although a link between the human cases and the contamination of irrigation water channels was suggested.

Spatio-Temporal Identification of Areas Suitable for West Nile Disease in the Mediterranean Basin and Central Europe.

West Nile virus (WNV) is a mosquito-transmitted Flavivirus belonging to the Japanese encephalitis antigenic complex of the Flaviviridae family. Its spread in the Mediterranean basin and the Balkans poses a significant risk to human health and forces public health officials to constantly monitor the virus transmission to ensure prompt application of preventive measures. In this context, predictive tools indicating the areas and periods at major risk of WNV transmission are of paramount importance. Spatial analysis approaches, which use environmental and climatic variables to find suitable habitats for WNV spread, can enhance predictive techniques. Using the Mahalanobis Distance statistic, areas ecologically most suitable for sustaining WNV transmission were identified in the Mediterranean basin and Central Europe. About 270 human and equine clinical cases notified in Italy, Greece, Portugal, Morocco, and Tunisia, between 2008 and 2012, have been considered. The environmental variables included in the model were altitude, slope, night time Land Surface Temperature, Normalized Difference Vegetation Index, Enhanced Vegetation Index, and daily temperature range. Seasonality of mosquito population has been modelled and included in the analyses to produce monthly maps of suitable areas for West Nile Disease. Between May and July, the most suitable areas are located in Tunisia, Libya, Egypt, and North Cyprus. Summer/Autumn months, particularly between August and October, characterize the suitability in Italy, France, Spain, the Balkan countries, Morocco, North Tunisia, the Mediterranean coast of Africa, and the Middle East. The persistence of suitable conditions in December is confined to the coastal areas of Morocco, Tunisia, Libya, Egypt, and Israel.

Genetic characterization of Brucella melitensis and Brucella abortus geographical clusters in Italy.

The genetic diversity of Brucella melitensis and Brucella abortus strains isolated in 199 cattle and sheep from 156 brucellosis outbreaks which occurred in 8 regions of Southern Italy in 2011, was determined using a Multiple-Locus Variable Number of Tandem Repeats Analysis approach. The existence of possible genetic clusters was verified through a hierarchical cluster analysis based on 'single link', which is closely related to the minimum spanning tree. The Hamming weighted distance matrix was adopted in the analysis. All calculations were performed using R and the additional libraries phangorn and Cluster. For a number of clusters, ranging from 2 to 15, the average silhouette width was calculated. The number of clusters adopted was identified according to the maximum average silhouette width. For B. abortus and B. melitensis, 6 and 11 genetic clusters were identified, respectively. Three out of 6 B. abortus clusters included the 96.7% of all B. abortus isolates. Clusters were clearly geographically separated, and this highlighted the known epidemiological links among them. Brucella melitensis genotypes resulted more heterogeneous; the 3 more representative genetic clusters included 79.7% of all B. melitensis isolates. A clear geographical clusterization of genotypes is recognizable only for 1 cluster, whereas the others are more widespread across Southern Italy. The genetic characterization of Brucella strains isolated from animals may be a useful tool to better understand the epidemiology and dissemination patterns of this pathogen through host populations.

Evaluation of different enzyme-linked immunosorbent assays for the diagnosis of brucellosis due to Brucella melitensis in sheep.

Six serological assays for the diagnosis of ovine brucellosis, due to Brucella melitensis were evaluated. Reference serum samples from sheep of known B. melitensis infection status (n=118) were assessed using the Rose Bengal test (RBT), complement fixation test (CFT) and four commercial enzyme-linked immunosorbent assays (ELISAs), including two indirect ELISAs (iELISAs), one competitive ELISA (cELISA) and one blocking ELISA (bELISA). The highest differential positive rates (DPR) were obtained with the cELISA and bELISA, while the lowest DPR was estimated using iELISAs. A latent class analysis was performed to estimate the accuracy of the CFT, RBT and bELISA using 1827 sera from sheep undergoing testing as part of a surveillance and control programme. Lower sensitivity and specificity were obtained for the three serological tests when the field samples were used. A higher DPR was achieved by the CFT, compared to bELISA and RBT. The results suggest that ELISAs, and particularly the bELISA, might be suitable for inclusion in the European Union legislation on intra-community trade for diagnosing B. melitensis infection in sheep, as it has a similar test performance compared to the RBT.