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. SIVENE was developed according to a multi-layer architecture with four integrated components: the database layer, which was implemented by an RDBMS Oracle 11 g; the ReST service layer, which was created using J2EE, Spring, and MyBatis technologies; the web application (business framework and user interface), which was developed in Angular4 framework using TypeScript language; and the web Geographic Information Systems (GIS), which was realized through the implementation of a geodatabase in Oracle RDBMS 11 g. This system allows us to build up and dynamically create a set of dedicated checklists to be used in the field when gathering the information needed for the management of non-epidemic emergencies; employ the application on mobile devices, such as tablets and smartphones; and use the web GIS to manage and visualize data of veterinary interest and territorial maps of risk and damage.

Veterinary Public Health Activities and Management of the Livestock Sector during Earthquakes and Snowstorms in the Abruzzo Region-Italy, January 2017.

In 2017 the Abruzzo region, located in central Italy, was struck by a sequence of four moderately powerful seismic events (5.0 magnitude on Richter scale), in addition to heavy snowfall that caused a state of emergency affecting the resident population and farm animals. A total of 282 stables were reported to have collapsed or been damaged and several animals (224 cows, 4025 ewes, 40,725 chickens, 22 horses and 3092 pigs) were killed. The Istituto Zooprofilattico of Abruzzo and Molise "G. Caporale" (IZSAM)-National Reference Center for Veterinary Urban Hygiene and Non-Epidemic Emergencies (IUVENE), played a crucial role in planning, coordinating and controlling veterinary activities during these catastrophic events. Operational and information tools were used to manage the needs of the communities involved, as well as to prioritize the veterinary interventions, record information, provide real-time data access, and produce reporting maps and Geographic Information System (GIS) layers. These events have highlighted how the integration of veterinary services into disaster management efforts can play an important role in protecting the health and welfare of animals, whilst also restoring economic activity and community life.

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. Risk assessment methods and other provisional modelling techniques may permit to estimate the probability of introduction and spread of infectious diseases in different geographical areas. Similarly, efficient information systems must be in place to assist the veterinary services in case of epidemic emergencies in order to support the prompt application of control measures for the containment of the infection and the reduction of the magnitude of negative consequences. This review describes two recent approaches to the estimation of the probability of introduction and spread of infectious diseases based on the use of risk maps/ spatial modelling and Social Network Analysis (SNA) techniques. The review also describes a web application developed in Italy to help official veterinary services to trace animals in case of outbreaks of infectious diseases.

Pet population management and public health: a web service based tool for the improvement of dog traceability.

The risks associated with zoonotic infections transmitted by companion animals are a serious public health concern: the control of zoonoses incidence in domestic dogs, both owned and stray, is hence important to protect human health. Integrated dog population management (DPM) programs, based on the availability of information systems providing reliable data on the structure and composition of the existing dog population in a given area, are fundamental for making realistic plans for any disease surveillance and action system. Traceability systems, based on the compulsory electronic identification of dogs and their registration in a computerised database, are one of the most effective ways to ensure the usefulness of DPM programs. Even if this approach provides many advantages, several areas of improvement have emerged in countries where it has been applied. In Italy, every region hosts its own dog register but these are not compatible with one another. This paper shows the advantages of a web-based-application to improve data management of dog regional registers. The approach used for building this system was inspired by farm animal traceability schemes and it relies on a network of services that allows multi-channel access by different devices and data exchange via the web with other existing applications, without changing the pre-existing platforms. Today the system manages a database for over 300,000 dogs registered in three different Italian regions. By integrating multiple Web Services, this approach could be the solution to gather data at national and international levels at reasonable cost and creating a traceability system on a large scale and across borders that can be used for disease surveillance and development of population management plans.

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. Epidemic simulations have been carried out on the network build out of movement data using a network-based meta-population model. The simulations show the influence of the network structure on the dynamics and size of a hypothetic epidemic and give useful indications on the effects of targeted removal of nodes based on the centrality of premises within the network of animal movements.

Animal welfare monitoring and livestock traceability during transport.

The authors present an experimental project that aims to establish an effective navigation system in accordance with European Council Regulation 1/2005 concerning animal welfare during transport. The prototype created during the project consists of both hardware and software components. An onboard unit is installed at truck level. It collects and transmits real-time information of the animal transport to a remote receiver database. A Web/geographic information system (GIS) application is used to analyse and monitor the information received. The architecture of the hardware and software of the project is presented, focusing on the features of the Web-GIS application.