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Potential disease-transmission sources in animals ID'd by calculating risk using social network mathematics

Date:
June 11, 2013
Source:
University of Granada
Summary:
Scientists have successfully identified animal species that can transmit more diseases to humans by using mathematical tools similar to those applied to the study of social networks like Facebook or Twitter. Their research describes how parasite-primate interactions transmit diseases like malaria, yellow fever or AIDS to humans. Their findings could make an important contribution to predicting the animal species most likely to cause future pandemics.

Chlorocebus aethiops, a primate species highly likely to transmit emerging diseases.
Credit: Image courtesy of University of Granada

Spanish and US scientists have successfully identified animal species that can transmit more diseases to humans by using mathematical tools similar to those applied to the study of social networks like Facebook or Twitter. Their research -- recently published in the journal PNAS -- describes how parasite-primate interactions transmit diseases like malaria, yellow fever or AIDS to humans. Their findings could make an important contribution to predicting the animal species most likely to cause future pandemics.

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Professor José María Gómez of the University of Granada Department of Ecology is the principal author of this research, in collaboration with Charles L. Nunn (University of Cambridge, Massachusetts, US) and Miguel Verdú (Spanish National Research Council Desertification Research Center, Valencia, Spain). They propose a criterion to identify disease-transmission agents based on complex network metrics similar to those used to study social networks.

As Prof Gómez explains, "most emerging diseases in humans are zoonotic, that is, they are transmitted to humans by animals. To identify animal species that are potential high-risk sources of emerging diseases it's essential we set up mechanisms that control and observe these diseases."

Study of 150 primate species

To conduct their study, the researchers constructed a network in which each node represented one of the approximately 150 non-human primate species about which we have enough data on their parasite fauna. "Each primate species is connected to the other primates as a function of the number of parasites they share. Once the network was constructed, we studied each primate species' position -- whether central or peripheral. A primate's centrality is measured by its connection intensity with many other primates that are, in turn, closely connected," says the University of Granada researcher.

The article published in PNAS reports the researchers' discovery that the most central primates could be more capable of transmitting parasites to other species and, therefore, to humans, than the rest. "This is comparable to the idea that, in social networks, web pages that are central and have links to many other pages, spread their contents all through the Web," José María Gómez affirms.

The researchers have confirmed their hypothesis by relating the centrality value of each primate with the number of emerging pathogens shared with humans. And, in effect, they have found that the most central primates were those that share more emerging pathogens with humans.

In conclusion, the study proposes a simple criterion to detect potential zoonotic agents of emerging disease transmission to humans: the centrality of these agents in their network interaction with their parasites. "The only information needed to construct these networks is the diversity and type of parasite infecting each host -- and we already know about many zoonotic organisms. This is why we think that our approach will be useful in developing early warning plans for emerging disease in humans," Prof Gómez concludes.


Story Source:

The above story is based on materials provided by University of Granada. Note: Materials may be edited for content and length.


Cite This Page:

University of Granada. "Potential disease-transmission sources in animals ID'd by calculating risk using social network mathematics." ScienceDaily. ScienceDaily, 11 June 2013. <www.sciencedaily.com/releases/2013/06/130611102027.htm>.
University of Granada. (2013, June 11). Potential disease-transmission sources in animals ID'd by calculating risk using social network mathematics. ScienceDaily. Retrieved November 28, 2014 from www.sciencedaily.com/releases/2013/06/130611102027.htm
University of Granada. "Potential disease-transmission sources in animals ID'd by calculating risk using social network mathematics." ScienceDaily. www.sciencedaily.com/releases/2013/06/130611102027.htm (accessed November 28, 2014).

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