Modelling resource-driven movements of livestock herds to predict the impact of climate change on network dynamics

Abstract

In East Africa, climate change is likely to profoundly impact livestock management and the potential spread of infectious diseases. Here, we developed a network model to describe livestock movements to grazing and watering sites, fitted it to data from the Serengeti district of Tanzania, and used it to explore how projected changes in resource availability due to climate change could impact future network structures and therefore infectious disease risks, using 2050 and 2080 as exemplar scenarios. Our modelled networks show increased connections between villages in grazing and watering networks, with connectivity increasing further in the future in correspondence with changes in vegetation and water availability. Our analyses show that targeted interventions to efficiently control regional disease spread may become more difficult, as village connectivity increases and disease vulnerability becomes more evenly distributed. This analysis also provides proof of principle for a novel approach applicable to agropastoral settings across many developing countries, where livestock trade plays a crucial role in maintaining local livelihoods but also in spreading disease.