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Distribution of highly pathogenic avian influenza, January-June 2006 

Distribution of highly pathogenic avian influenza, January-June 2006 

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To respond to the lack of early warning in dealing with livestock diseases, the Food and Agriculture Organization (FAO) developed and launched the Emergency Prevention System for Transboundary Animal and Plant Pests and Diseases (EMPRES) programme in 1994. Emphasis was placed on the prevention of emergencies due to transboundary epidemic diseases o...

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... this GIS approach, HPAI disease observation data entered into EMPRES-i can be visualised as basic maps (Fig. 1) before being combined, for advanced disease analysis purposes, with additional geographical layers, such as land use, poultry density, remote- sensed imagery (Fig. 2) or other variables hypothesised as relevant to the epidemiology of the disease or ecology of the virus, host or environment (Fig. ...

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... Its aim was to deliver early warning messages to the international community at risk of transboundary animal diseases. The Emergency Prevention System (EMPRES) for Transboundary Animal and Plant Pests is another earlier example of a global effort by the FAO organization, with emphasis on the prevention of emergencies due to transboundary epidemic diseases and/or food security (11,12). The Predictive Livestock Early Warning System (PLEWS) is an example of a regional effort by researchers in Kenya for monitoring of forage condition and early warning system for the reduction of livestock loss and improvement of their resilience (13). ...
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... One good example of the use of GIS in the surveillance of animal diseases is, GIS applied to the international surveillance and control of transboundary animal diseases, a focus on highly pathogenic avian infl uenza. Occurrences and distribution of HPAI observed from 19 January to 19 July 2006 are represented by the use of maps Figure 5 [19][20][21][22][23][24][25][26][27][28]. ...
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... Also, prompt practice of quarantine 2013 protocol would reduce many transboundary diseases. Geographic information system (GIS) and remote sensing could be utilized as early warning systems and in the surveillance and control of infectious diseases (Martin et al., 2007);  Reducing man-made disasters that have adverse implications on climate. Global warming and climate change either due to natural or anthropogenic influences are likely to predispose the animal population to newer infections (FAO, 2008). ...
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... Although animal disease surveillance has traditionally been implemented at national and sub-national levels, the increasing number of transboundary animal disease epidemics has highlighted the need for establishing such systems at broader scales. As a result, data warehouses and disease reporting systems such as World Animal Health Information Database (WAHID) (Jebara et al., 2012) and EMPRES Global Animal Disease Information System (EMPRES-i) (FAO: EMPRES transboundary animal disease bulletin, 2011; Farnsworth et al., 2010; Martin et al., 2007) were launched to encourage and facilitate data collection and sharing at a global level (Table 2). However, in addition to their original role, such data warehouses also provide researchers with cost-effective access to regularly updated spatial disease data, potentially leading to increased knowledge gains, without the need for costly and time-consuming primary research. ...
... EMPRES-i); (http://empresi .fao.org/eipws3g/) (FAO: EMPRES transboundary animal disease bulletin, 2011; Farnsworth et al., 2010; Martin et al., 2007) ...
... reports from the OIE, World Health Organization, national authorities, FAO country or regional projects, field missions and field officers, non-governmental organizations , laboratories and reference centers) and informal sources (e.g. media reports and those disseminated by the Global Public Health Intelligence Network and ProMED) (Farnsworth et al., 2010; Martin et al., 2007), and all outbreaks appearing in the database are followed-up until either confirmed or denied (Farnsworth et al., 2010). WAHID, on the other hand, comprises official information submitted by OIE member countries regarding immediate and follow-up notifications of exceptional disease events, or semester and annual reports on OIE-listed diseases together with background information on animal health and control programs. ...
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During the last 30years it has become commonplace for epidemiological studies to collect locational attributes of disease data. Although this advancement was driven largely by the introduction of handheld global positioning systems (GPS), and more recently, smartphones and tablets with built-in GPS, the collection of georeferenced disease data has moved beyond the use of handheld GPS devices and there now exist numerous sources of crowdsourced georeferenced disease data such as that available from georeferencing of Google search queries or Twitter messages. In addition, cartography has moved beyond the realm of professionals to crowdsourced mapping projects that play a crucial role in disease control and surveillance of outbreaks such as the 2014 West Africa Ebola epidemic. This paper provides a comprehensive review of a range of innovative sources of spatial animal and human health data including data warehouses, mHealth, Google Earth, volunteered geographic information and mining of internet-based big data sources such as Google and Twitter. We discuss the advantages, limitations and applications of each, and highlight studies where they have been used effectively. Copyright © 2015 Elsevier Ltd. All rights reserved.