Literature DB >> 27393878

The Arbo‑zoonet Information System.

Alessio Di Lorenzo1, Daria Di Sabatino, Valeria Blanda, Daniela Cioci, Annamaria Conte, Rossana Bruno, Francesca Sauro, Paolo Calistri, Lara Savini.   

Abstract

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. Since November 2011, when the Schmallenberg virus (SBV) has been discovered for the first time in Northern Europe, the Arbo‑zoonet Information System has been used in order to collect information on newly discovered disease and to manage the epidemic emergency. The system monitors the geographical distribution and epidemiological evolution of CCHF, RVF, and WND since 1946. More recently, it has also been deployed to monitor the SBV data. The Arbo‑zoonet Information System includes a web application for the management of the database in which data are stored and a WebGIS application to explore spatial disease distributions, facilitating the epidemiological analysis. The WebGIS application is an effective tool to show and share the information and to facilitate the exchange and dissemination of relevant data among project's participants.

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Year:  2016        PMID: 27393878     DOI: 10.12834/VetIt.522.2484.1

Source DB:  PubMed          Journal:  Vet Ital        ISSN: 0505-401X            Impact factor:   1.101


  2 in total

1.  Increased Susceptibility of Cattle to Intranasal RVFV Infection.

Authors:  Andrea L Kroeker; Valerie Smid; Carissa Embury-Hyatt; Brad Collignon; Mathieu Pinette; Shawn Babiuk; Bradley Pickering
Journal:  Front Vet Sci       Date:  2020-04-29

2.  A systematic review of spatial decision support systems in public health informatics supporting the identification of high risk areas for zoonotic disease outbreaks.

Authors:  Rachel Beard; Elizabeth Wentz; Matthew Scotch
Journal:  Int J Health Geogr       Date:  2018-10-30       Impact factor: 3.918

  2 in total

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