Social networks and disease transmission – A story of giraffes

World Giraffe Day celebrates the longest-necked animal on the longest day (or night, depending on your hemisphere!) of the year – 21st June.  Yet many aspects of giraffe ecology remain poorly studied.  Dr Kim VanderWaal, a researcher at the University of Minnesota, studies how animal social behaviour translates into contact networks and pathogen transmission patterns.  To mark World Giraffe Day, she tells us about her experiences working in giraffe ecology and provides a new perspective on this iconic animal.

Unlike so many other charismatic species roaming the plains of Africa, science seems to have neglected the giraffe (Giraffa camelopardalis) until only recently and giraffes are just now entering the conservation conversation (see figure below).  Indeed, there are still large holes in our understanding of the social nature of giraffe and it is becoming increasingly clear that giraffes do not randomly aggregate with others but rather have a more complex social structure based on kinship and social preferences.

The Neglected Giraffe: A graph of the top journals publishing giraffe research and a word cloud based on article titles (Credit: Kim VanderWaal).

However, those are not the reasons that brought me to studying giraffes beginning in 2010.  At the time, I was a young graduate student from UC Davis, with an interest in social networks and disease ecology.  Among the common struggles for any socio-ecological study of wildlife is how to identify individuals, and the fact that every giraffe is individually recognizable from unique spot patterns made them a perfect subject for my study of the importance of social relationships, contact, and transmission of pathogens. Once you get the trick of telling giraffe apart, it becomes second nature to identify each animal.  I drove well over 30,000 km in the bush of Ol Pejeta Conservancy, Kenya, conducting transects for giraffe.  All-in-all, I observed each of 200 animals in the population upwards of 30 times, recording their locations and which other giraffe they were with.

Spot the Difference: Each giraffe is individually recognizable from unique spot patterns (Photo: Kim VanderWaal)

From these detailed data, I was able to build social networks based on who was in contact with whom and spatial networks on which individuals shared home ranges. Ultimately, the goal of my work was to integrate network theory and microbial genetics to quantify pathogen transmission networks in these wild giraffes.  To measure transmission, I collected hundreds of fecal samples from giraffe and other species. I used the genetics of a diverse microbe, Escherichia coli, to infer where direct or indirect transmission had occurred and used these data to construct transmission networks. Results of this study (published in the Journal of Animal Ecology), showed that individuals who were social “hubs” (had a large number of connections to others in their social network) also were hubs in the transmission network, which means that they have great potential to be “superspreaders” of pathogens. In addition, individuals who served as social “bridges” between different cliques in the social network also tended to be bridges in the transmission network.

Individuals who were social ‘hubs’ were also hubs in the pathogen transmission network (Photo: Kim VanderWaal)

By using microbial genetic data to quantify individuals that were part of the same chain of transmission independently from behavioral data on who is in contact with whom, our team was able to directly investigate how the structure of contact networks influenced the structure of the transmission network. Such an approach permits one to go beyond simple detection and begin to address critical questions about the processes that underlie disease transmission at multiple scales, allowing for the potential for intervention at key steps.

For more information:

VanderWaal et al. (2014) Linking social and pathogen transmission networks using microbial genetics in giraffe (Giraffa camelopardalis). Journal of Animal Ecology, 83(2), 406-414.

 

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