Abstract
Zoonotic diseases are an important cause of human morbidity and mortality; around 75% of recently emerging human infectious diseases are zoonoses. The movement of people, goods, and animals, globally, as facilitated by free trade and tourism may allow emerging diseases to spread quickly. Animal movement caused by natural migration, trading and marketing livestock represents an especially critical aspect in dis-semination of zoonotic diseases. In order to predict the spatial distribution for selected pathogen - Brucella spp., we developed models linking geo-referenced covariate information on geographical, ecological, social factors with geo-referenced samples of the selected pathogen. The proposed work will modernize national surveillance and identify areas at risk for Brucellosis in the South Caucasus. Quantitative disease ecology provides useful tools to analyze spatially referenced data on distributions of animal hosts and infectious agents, and their spatial concordance with environmental and social parameters. Animal movement caused by trading and marketing livestock represents an especially critical aspect in dissemination of zoonotic diseases. The Atlas will identify areas where brucellosis diseases might occur, but human cases have not been recognized, but where further surveillance should be targeted. Effective surveillance systems rely on localand national participants’ ability and willingness to accurately report disease outbreaks, and their capability to implement local and national responses. Early identification of zoonotic disease emergence is essential to rapidly contain outbreaks, yet many local and national authorities lack the human and technical capability, capacity, and supporting financial resources to do so. By developing the Atlas, we will acquire information on the specifics of where and how the pathogen emerged, in what populations, in the past and, by extension, identify other similar regions where their circulation has gone undetected.
