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We're meeting with others, as well as drawing inspiration from housing movements, networks and cooperatives in other countries.
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This paper presents a new method to assess herd disease risk in animal movement networks.
NodeXL software was used to describe pig movement networks at village level.
Next, we combined habitat-suitability maps with real movement data to develop graph models that represent movement networks as inter-connected patches of different quality.
Characterization of movement networks between pig farms and through other types of farm and household enterprises that are involved in pig value chains can provide useful information on the role that different participants in the networks play in pathogen transmission.
Network analyses revealed that movement networks demonstrate some well-studied properties regarding their structure and robustness (i.e. scale-free and small-world), providing insights on the contribution of patches of different quality to connectivity.
The close social relationships between actors in pig movement networks indicate the potential for possible interventions to develop shared norms and mutually accepted protocols amongst smallholder pig keepers to better manage the risk of ASF introduction and transmission.
These have taken two approaches to characterising the movement networks.
We also predicted greater activation in areas of the attention/eye movement networks that are specifically involved in the control of endogenously driven shits of attention.
In parallel with the disease-specific studies there have been a number of studies of the generic properties of livestock movement networks relating to the spread of infectious disease.
These included the lateral occipital cortex (LOC) [50], which has been implicated in both modal and amodal perceptual completion [41], and components of the eye movement networks that are associated with voluntary saccades and shifts of attention, i.e. the frontal and parietal eyefields (FEFs, PEFs) [51], [52].
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