The hidden role of buffalo trade network in bovine epidemic spreading.

Animal movements are a key factor in the spread of pathogens. Consequently, network analysis of animal movements is a well-developed and well-studied field. The relationships between animals facilitate the diffusion of infectious agents and, in particular, shared environments and close interactions can facilitate cross-species transmission.

The "Working Group Land of Fires" Platform for emergency management, data sharing and dissemination.

Over the last decades, the Campania Region in Italy has faced an environmental crisis due to the widespread illegal dumping and burning of waste. This has led to the area being notoriously known as the Land of Fires (Terra dei Fuochi - TdF), sparking serious concerns about public health and threatening the region's agricultural sector, one of its economic mainstays. In such a context, a timely, accurate, and reliable flow of information, aimed both at the population and at stakeholders, is crucial for establishing a proper dialogue between institutions and people, driving the empowerment of citizens.

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.

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.

A New Information System for the Management of Non-Epidemic Veterinary Emergencies.

The Italian National Veterinary Services, public health professionals, and policy makers are asked to participate at different levels in the decision-making process for the management of non-epidemic emergencies. A decision support system offering the different administrative and operational emergency management levels with a spatial and decisional tool to be used in the case of natural disasters is still missing at the national level. Within this context, the Italian General Directorate for Animal Health of the Ministry of Health funded a research project for the implementation of a new Veterinary Information System for Non-Epidemic Emergencies (SIVENE), an innovative real-time decision support tool for emergency response in a disaster management scenario.

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.

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.

Disease persistence on temporal contact networks accounting for heterogeneous infectious periods.

The infectious period of a transmissible disease is a key factor for disease spread and persistence. Epidemic models on networks typically assume an identical average infectious period for all individuals, thus allowing an analytical treatment. This simplifying assumption is, however, often unrealistic, as hosts may have different infectious periods, due, for instance, to individual host-pathogen interactions or inhomogeneous access to treatment.

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.

A Web Geographic Information System to share data and explorative analysis tools: The application to West Nile disease in the Mediterranean basin.

Background: In the last decades an increasing number of West Nile Disease cases was observed in equines and humans in the Mediterranean basin and surveillance systems are set up in numerous countries to manage and control the disease. The collection, storage and distribution of information on the spread of the disease becomes important for a shared intervention and control strategy. To this end, a Web Geographic Information System has been developed and disease data, climatic and environmental remote sensed data, full genome sequences of selected isolated strains are made available.

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).

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.

OIEBTLABNET: the web-based network of the OIE Bluetongue Reference Laboratories.

Bluetongue (BT) is a mild to severe disease of domestic and wild ruminants caused by the Bluetongue virus (BTV) and generally transmitted by Culicoides biting midges. Its occurrence also determines a livestock trade ban in affected countries with severe economic consequences on national and international trade. For this reason, in May 2011, the OIE encouraged the OIE Reference Laboratories to establish and maintain a BT network to provide expertise and training to the OIE and OIE Member Countries for BT diagnosis, surveillance and control.

Rift Valley fever trasmission dynamics described by compartmental models.

Rift Valley fever (RVF) is one of the most important zoonotic Transboundary Animal Diseases able to cross international borders and cause devastating effect on animal health and food security. Climate changes and the presence of competent vectors in the most of the current RVF-free temperate countries strongly support the inclusion of RVF virus (RVFV) among the most significant emerging viral threats for public and animal health. The transmission of RVFV is driven by complex eco-climatic factors making the epidemiology of RVF infection difficult to study and to understand.

The Arbo‑zoonet Information System.

The Arbo‑zoonet Information System has been developed as part of the 'International Network for Capacity Building for the Control of Emerging Viral Vector Borne Zoonotic Diseases (Arbo‑zoonet)' project. The project aims to create common knowledge, sharing data, expertise, experiences, and scientific information on West Nile Disease (WND), Crimean‑Congo haemorrhagic fever (CCHF), and Rift Valley fever (RVF). These arthropod‑borne diseases of domestic and wild animals can affect humans, posing great threat to public health.

Predicting epidemic risk from past temporal contact data.

Understanding how epidemics spread in a system is a crucial step to prevent and control outbreaks, with broad implications on the system's functioning, health, and associated costs. This can be achieved by identifying the elements at higher risk of infection and implementing targeted surveillance and control measures. One important ingredient to consider is the pattern of disease-transmission contacts among the elements, however lack of data or delays in providing updated records may hinder its use, especially for time-varying patterns.

Systems for prevention and control of epidemic emergencies.

The development of early warning systems is fundamental for preventing the spread of infectious diseases. Data collection, however, is a costly activity and it is not possible to implement early warning systems everywhere and for all possible events. Hence, tools helping to improve the focus of surveillance efforts are of paramount importance.

Optimizing surveillance for livestock disease spreading through animal movements.

The spatial propagation of many livestock infectious diseases critically depends on the animal movements among premises; so the knowledge of movement data may help us to detect, manage and control an outbreak. The identification of robust spreading features of the system is however hampered by the temporal dimension characterizing population interactions through movements. Traditional centrality measures do not provide relevant information as results strongly fluctuate in time and outbreak properties heavily depend on geotemporal initial conditions.

Dynamical patterns of cattle trade movements.

Despite their importance for the spread of zoonotic diseases, our understanding of the dynamical aspects characterizing the movements of farmed animal populations remains limited as these systems are traditionally studied as static objects and through simplified approximations. By leveraging on the network science approach, here we are able for the first time to fully analyze the longitudinal dataset of Italian cattle movements that reports the mobility of individual animals among farms on a daily basis. The complexity and inter-relations between topology, function and dynamical nature of the system are characterized at different spatial and time resolutions, in order to uncover patterns and vulnerabilities fundamental for the definition of targeted prevention and control measures for zoonotic diseases.

Evaluation of risk and vulnerability using a Disease Flow Centrality measure in dynamic cattle trade networks.

A new method for the calculation of a centrality measure (Disease Flow Centrality, DFC), which takes into account temporal dynamics of livestock movement networks, is proposed. The method is based on a network traversal algorithm which represents an epidemic process more realistically compared with traditional graph traversal algorithms used in the calculation of centrality measures on static networks. The new approach was tested on networks generated from all the registered movements of cattle in Italy in the years 2007, 2008 and 2009 and the results were compared to those obtained by classical centrality measures.

Network analysis of Italian cattle trade patterns and evaluation of risks for potential disease spread.

Livestock movement data represent a valuable source of information to understand the pattern of contacts between premises which may determine the spread of diseases. Social network analysis techniques have been used to analyse the movement patterns of cattle in Italy in 2007. A description of the structure of the Italian cattle industry is presented and the main trade flows and the relations between premises in relation to the potential spread of cattle diseases are investigated.

A Web-based geographic information system for the management of animal disease epidemics.

Outbreaks of highly contagious animal diseases severely affect the global economy, seriously disrupting domestic economies and the international trade of livestock and animal commodities. Italy has a series of contingency plans for the management of outbreaks of all major animal diseases. Disease control measures are mainly based on a traditional approach and eradication policies range from culling and stamping-out to movement restrictions of animals and commodities.

A Web-based geographic information system for monitoring animal welfare during long journeys.

Animal welfare protection during long journeys is mandatory according to European Union regulations designed to ensure that animals are transported in accordance with animal welfare requirements and to provide control bodies with a regulatory tool to react promptly in cases of non-compliance and to ensure a safe network between products, animals and farms. Regulation 1/2005/EC foresees recourse to a system of traceability within European Union member states. The Joint Research Centre of the European Commission (JRC) has developed a prototype system fulfilling the requirements of the Regulation which is able to monitor compliance with animal welfare requirements during transportation, register electronic identification of transported animals and store data in a central database shared with the other member states through a Web-based application.

Web-based geographic information system tools and international surveillance network for bluetongue in the Balkans and south-east Europe (East-BTNet).

Bluetongue (BT) is an infectious, non-contagious vector-borne disease. Since 1998, the disease has spread across the Mediterranean Basin and into the Balkans. During a Workshop devoted to the electronic identification of animals and bluetongue, held in Civitella del Tronto, Teramo, in December 2002, the representatives of Balkan and Eastern Mediterranean countries stated the need for implementing a regional surveillance network capable of collecting and disseminating relevant epidemiological data on BT.