Disastro ambientale nel Mar Piccolo di Taranto durante la Prima Guerra Mondiale

Since 1883, the Mar Piccolo of Taranto (Ionian Sea, Mediterranean) has played a dual role as privileged area for shellfish farming and strategic military port. This historical research, based on the collection of direct, indirect and iconographic sources, provided socioeconomic information about Taranto from 1883 to 1926 and unprecedented data on the most probable catastrophic effects (the sinking of a dreadnought) on the marine environment during the First World War. The analysis of original documents showed that the strategies (scientific studies, application and propagation of best practices; economic evaluation of productions; communication with military and civil authorities and shellfish farmers) adopted by Attilio Cerruti (the Marine Biology Laboratory’s Inspector) ensured shellfish farming survival and its recovery in the post war period. Moreover, Cerruti’s holistic approach could be a useful example for the solution of current management and conservation problems related to goods and services of valuable ecosystems highly impacted by human activities (not limited to warfare), such as those affecting the Mar Piccolo of Taranto

Realistic assumptions about spatial locations and clustering of premises matter for models of foot-and-mouth disease spread in the United States

Spatially explicit livestock disease models require demographic data for individual farms or premises. In the U.S., demographic data are only available aggregated at county or coarser scales, so disease models must rely on assumptions about how individual premises are distributed within counties. Here, we addressed the importance of realistic assumptions for this purpose. We compared modeling of foot and mouth disease (FMD) outbreaks using simple randomization of locations to premises configurations predicted by the Farm Location and Agricultural Production Simulator (FLAPS), which infers location based on features such as topography, land-cover, climate, and roads. We focused on three premises-level Susceptible-Exposed-Infectious-Removed models available from the literature, all using the same kernel approach but with different parameterizations and functional forms. By computing the basic reproductive number of the infection (R0) for both FLAPS and randomized configurations, we investigated how spatial locations and clustering of premises affects outbreak predictions. Further, we performed stochastic simulations to evaluate if identified differences were consistent for later stages of an outbreak. Using Ripley's K to quantify clustering, we found that FLAPS configurations were substantially more clustered at the scales relevant for the implemented models, leading to a higher frequency of nearby premises compared to randomized configurations. As a result, R0 was typically higher in FLAPS configurations, and the simulation study corroborated the pattern for later stages of outbreaks. Further, both R0 and simulations exhibited substantial spatial heterogeneity in terms of differences between configurations. Thus, using realistic assumptions when de-aggregating locations based on available data can have a pronounced effect on epidemiological predictions, affecting if, where, and to what extent FMD may invade the population. We conclude that methods such as FLAPS should be preferred over randomization approaches

Spatio-temporal patterns and characteristics of swine shipments in the U.S. based on Interstate Certificates of Veterinary Inspection

Domestic swine production in the United States is a critical economic and food security industry, yet there is currently no large-scale quantitative assessment of swine shipments available to support risk assessments. In this study, we provide a national-level characterization of the swine industry by quantifying the demographic (i.e. age, sex) patterns, spatio-temporal patterns, and the production diversity within swine shipments. We characterize annual networks of swine shipments using a 30% stratified sample of Interstate Certificates of Veterinary Inspection (ICVI), which are required for the interstate movement of agricultural animals. We used ICVIs in 2010 and 2011 from eight states that represent 36% of swine operations and 63% of the U.S. swine industry. Our analyses reflect an integrated and spatially structured industry with high levels of spatial heterogeneity. Most shipments carried young swine for feeding or breeding purposes and carried a median of 330 head (range: 1–6,500). Geographically, most shipments went to and were shipped from Iowa, Minnesota, and Nebraska. This work, therefore, suggests that although the swine industry is variable in terms of its size and type of swine, counties in states historically known for breeding and feeding operations are consistently more central to the shipment network

Effects of regional differences and demography in modelling foot-and-mouth disease in cattle at the national scale

Foot-and-mouth disease (FMD) is a fast-spreading viral infection that can produce large and costly outbreaks in livestock populations. Transmission occurs at multiple spatial scales, as can the actions used to control outbreaks. The US cattle industry is spatially expansive, with heterogeneous distributions of animals and infrastructure. We have developed a model that incorporates the effects of scale for both disease transmission and control actions, applied here in simulating FMD outbreaks in US cattle. We simulated infection initiating in each of the 3049 counties in the contiguous US, 100 times per county. When initial infection was located in specific regions, large outbreaks were more likely to occur, driven by infrastructure and other demographic attributes such as premises clustering and number of cattle on premises. Sensitivity analyses suggest these attributes had more impact on outbreak metrics than the ranges of estimated disease parameter values. Additionally, although shipping accounted for a small percentage of overall transmission, areas receiving the most animal shipments tended to have other attributes that increase the probability of large outbreaks. The importance of including spatial and demographic heterogeneity in modelling outbreak trajectories and control actions is illustrated by specific regions consistently producing larger outbreaks than others

Estimating and exploring the proportions of inter- and intrastate cattle shipments in the United States

Mathematical models are key tools for the development of surveillance, preparedness and response plans for the potential events of emerging and introduced foreign animal diseases. Creating these types of plans requires data; when data are incomplete, mathematical models can help fill in missing information, provided they are informed by the data that are available. In the United States, the most complete national-scale data available on cattle shipments are based on Interstate Certificates of Veterinary Inspection, which track the shipment of cattle between states; data on intrastate cattle shipments are lacking. Here we develop four new datasets on intrastate cattle shipments in the U.S., including an expert elicitation survey covering 19 states and territories and three state-level brand inspection data sets. The expert elicitation survey provides estimates on the proportion of shipments that travel interstate over multiple regions of the U.S. These survey data also identify differences in shipment patterns between regions, cattle commodity types, and sectors of the cattle industry. These survey data cover more states than any other source of intrastate data; however, one limitation of these data is the small number of participating experts in many of the states, only seven of the 19 responding states and territories had a group size of three or larger. The brand data sets include origin and destination information for both intra- and interstate shipments. These data, therefore, also provide detailed information on the proportion of interstate shipments in three Western states, including the temporal and geographic variation in shipments. Because the survey and brand data overlap in the Western U.S., they can be compared. We find that in the Western U.S. the expert estimates of the overall proportion of cattle shipments matched the brand data well. However, the experts estimated that there would be larger differences in beef and dairy shipments than the brand data show. This suggests the cattle industries in the West may be sending similar proportions of commodity specific cattle shipments over state lines. We additionally used the expert survey data to explore how differences in the proportion of interstate shipments can change predictions about cattle shipment patterns using the example of model-guided suggestions for targeted surveillance in Texas. Together these four data sets are the most extensive and geographically comprehensive information to date on intrastate cattle shipments. Additionally, our analyses on predicted shipment patterns suggest that assumptions about intrastate shipments could have consequences for targeted surveillance

Equine Piroplasmosis Domestic Pathways Assessment (2011)

Abstract: Equine piroplasmosis (EP) is a tick borne disease of equids. It is considered a foreign animal disease in the United States. However, from January 2009 through November 2010, 542 confirmed positive cases have been identified in 16 different States. This domestic pathways assessment evaluates the risk of releasing an EP pathogen (Theileria equi or Babesia caballi) from a quarantined premises through movement of horses. In addition, this assessment evaluates the risk of disease transmission by ticks, vertical transmission, or iatrogenic transmission. When an acaricide is applied correctly, the risk of EP transmission by ticks to a horse is low. In addition, infected reservoir hosts, environmental factors, and competent vectors must be present for the disease transmission cycle to occur. Vertical transmission of T. equi is considered a moderate risk pathway and the risk of vertical transmission of B. caballi is negligible. Iatrogenic transmission via whole blood transfusion, blood doping, commercial serum/blood plasma, and contaminated equipment poses the highest risk of disease transmission. Blood is an efficient vehicle of transmission for EP pathogens and even a small volume of blood can be infectious. Exposure of an uninfected horse to any of these pathways is likely to result in EP transmission. Iatrogenic exposure may be difficult to regulate. Management practices such as testing blood donors would help mitigate this risk but these practices vary throughout the equine industry. The overall risk of EP spread by the movement of a horse from a quarantined premises is moderate

Spatio-temporal patterns and characteristics of swine shipments in the U.S. based on Interstate Certificates of Veterinary Inspection

Domestic swine production in the United States is a critical economic and food security industry, yet there is currently no large-scale quantitative assessment of swine shipments available to support risk assessments. In this study, we provide a national-level characterization of the swine industry by quantifying the demographic (i.e. age, sex) patterns, spatio-temporal patterns, and the production diversity within swine shipments. We characterize annual networks of swine shipments using a 30% stratified sample of Interstate Certificates of Veterinary Inspection (ICVI), which are required for the interstate movement of agricultural animals. We used ICVIs in 2010 and 2011 from eight states that represent 36% of swine operations and 63% of the U.S. swine industry. Our analyses reflect an integrated and spatially structured industry with high levels of spatial heterogeneity. Most shipments carried young swine for feeding or breeding purposes and carried a median of 330 head (range: 1–6,500). Geographically, most shipments went to and were shipped from Iowa, Minnesota, and Nebraska. This work, therefore, suggests that although the swine industry is variable in terms of its size and type of swine, counties in states historically known for breeding and feeding operations are consistently more central to the shipment network

Growth Performance of Mytilus galloprovincialis Lamarck, 1819 under an Innovative Integrated Multi-Trophic Aquaculture System (IMTA) in the Mar Grande of Taranto (Mediterranean Sea, Italy)

The cultivation of the Mediterranean mussel, Mytilus galloprovincialis Lamarck, 1819, has been tested in an innovative Integrated Multitrophic Aquaculture system (IMTA) in the Mar Grande of Taranto, as part of the EU-funded Remedialife project. This farming method could solve several problems including the low growth rate in mesotrophic environments while reducing the environmental impact of fish mariculture. Three productive cycles have been carried out. The first (2018–2019, traditional experiment) was conducted in three long lines around six cages of the fish farm in order to evaluate total mussel production under the innovative IMTA system and quality for human consumption by analyzing the concentration of culturable heterotrophic bacteria, total and fecal coliforms, Escherichia coli and Salmonella spp. in mussel tissues. In addition, 17 polycyclic aromatic hydrocarbons (PAHs), including 16 EPA priority compounds and seven polychlorinated biphenyls (PCBs), which are indicators of PCB contamination in the environment, were analyzed using gas chromatography in conjunction with a mass spectrometer. The second cycle (2020–2021, horizontal distance experiment) aimed to test the influence of fish cages on mussel growth by placing mussels near and far from the fish cages. The third cycle (2021–2022, vertical distance experiment) aimed to overcome the phenomenon of “heat waves” that can occur in the Mar Grande of Taranto during summer by testing the growth performance of mussels at two different depths (1 and 12 m). The following parameters were measured: Shell Length, L (mm); Shell Dry Weight, SDW (g); Flesh Dry Weight, FDW (g); Condition Index, IC = FDW/SDW. The results showed that the best growth performance was obtained near the fish cages and at a depth of 12 m. Moreover, the indicators of microbial contamination and concentrations of chemical compounds analyzed in mussel tissues cultured under the innovative IMTA system were in compliance with the reference values of European regulations

Clinical Remission Predictors in Non-Colonized Bronchiectasis and Severe Asthma with Type 2-Targeted Biologic Therapy: A Retrospective Real-Life Pilot Study

Background/Objective: Patients with severe asthma (SA) and non-cystic fibrosis bronchiectasis (BE) without microbiological colonization represent a unique and understudied population. Type 2-targeted biologic therapies have emerged as a promising treatment for these patients. However, predictive factors for achieving clinical remission remain unclear. This study aims to identify the predictive factors for achieving clinical remission in patients with severe asthma and non-colonized bronchiectasis undergoing type 2-targeted biologic therapies. Methods: A retrospective longitudinal analysis was conducted on 14 patients with severe asthma and non-cystic fibrosis bronchiectasis without microbiological colonization. Clinical remission was assessed at baseline (T0) and after 12 months (T1) of biologic therapy. Clinical remission was defined according to the Severe Asthma Network Italy (SANI) criteria, including the absence of oral corticosteroid use, no asthma-related symptoms, stable lung function, and no exacerbations. Logistic regression was performed to identify predictors of remission. ROC curves were constructed to evaluate the predictive accuracy of lung function parameters, specifically FEV1 and FVC. Results: After 12 months of biologic therapy, 28.6% of patients (n = 4) achieved clinical remission. The mean FEV1 percentage at baseline was significantly higher in the remission group (92.25 ± 15.64%) compared to the non-remission group (65.10 ± 23.36%, p = 0.034). Logistic regression analysis identified baseline FEV1 as a significant predictor of remission (OR = 1.008, p = 0.050). ROC curve analysis revealed that an FEV1 cutoff of 72.5% had a sensitivity of 100% and a specificity of 70% (AUC = 0.900, p = 0.024) for predicting clinical remission. Conclusions: FEV1 is a crucial predictor of clinical remission in patients with severe asthma and non-colonized bronchiectasis treated with type 2-targeted biologic therapies. An FEV1 threshold of 72.5% can guide clinicians in identifying patients most likely to achieve remission. These findings underline the importance of preserving lung function to optimize therapeutic outcomes in this complex population

Estimating and exploring the proportions of inter- and intrastate cattle shipments in the United States

Mathematical models are key tools for the development of surveillance, preparedness and response plans for the potential events of emerging and introduced foreign animal diseases. Creating these types of plans requires data; when data are incomplete, mathematical models can help fill in missing information, provided they are informed by the data that are available. In the United States, the most complete national-scale data available on cattle shipments are based on Interstate Certificates of Veterinary Inspection, which track the shipment of cattle between states; data on intrastate cattle shipments are lacking. Here we develop four new datasets on intrastate cattle shipments in the U.S., including an expert elicitation survey covering 19 states and territories and three state-level brand inspection data sets. The expert elicitation survey provides estimates on the proportion of shipments that travel interstate over multiple regions of the U.S. These survey data also identify differences in shipment patterns between regions, cattle commodity types, and sectors of the cattle industry. These survey data cover more states than any other source of intrastate data; however, one limitation of these data is the small number of participating experts in many of the states, only seven of the 19 responding states and territories had a group size of three or larger. The brand data sets include origin and destination information for both intra- and interstate shipments. These data, therefore, also provide detailed information on the proportion of interstate shipments in three Western states, including the temporal and geographic variation in shipments. Because the survey and brand data overlap in the Western U.S., they can be compared. We find that in the Western U.S. the expert estimates of the overall proportion of cattle shipments matched the brand data well. However, the experts estimated that there would be larger differences in beef and dairy shipments than the brand data show. This suggests the cattle industries in the West may be sending similar proportions of commodity specific cattle shipments over state lines. We additionally used the expert survey data to explore how differences in the proportion of interstate shipments can change predictions about cattle shipment patterns using the example of model-guided suggestions for targeted surveillance in Texas. Together these four data sets are the most extensive and geographically comprehensive information to date on intrastate cattle shipments. Additionally, our analyses on predicted shipment patterns suggest that assumptions about intrastate shipments could have consequences for targeted surveillance