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Biology subjects

Eubank, S.

Publications and source records attributed to Eubank, S..

2 recordsLinked to original sources

Comparing Livestock Mobility-Informed Strategies for Peste des Petits Ruminants Control in Nigeria: The Central Role of the Network Backbone

Animal mobility is central to pastoral livelihoods and regional trade in West Africa, but it also facilitates the spread of transboundary animal diseases such as Peste des petits ruminants (PPR). In Nigeria, PPR outbreaks recur regularly, yet surveillance and control remain limited in the absence of routine animal-movement tracking. Here, we assess and compare movement-informed control options for PPR using a reconstructed livestock mobility network from a one-time market survey conducted in three northern Nigerian states. We simulate transmission on this network and evaluate three intervention strategies: (i) targeting vulnerable villages, (ii) targeting the links that connect movement communities, and (iii) targeting villages belonging to the network backbone. Across scenarios, backbone-based targeting consistently produced the largest reductions in network connectivity and epidemic outcomes, outperforming strategies focused on vulnerable nodes or inter-community links. These results suggest that backbone-informed control could provide a practical, resource-efficient pathway to strengthen PPR control in settings where routine movement data are scarce.

animal behavior and cognition↗

Determining whether a class of random graphs is consistent with an observed contact network

We demonstrate a general method to analyze the sensitivity of attack rate in a network model of infectious disease epidemiology to the structure of the network. We use Moore and Shannons \"network reliability\" statistic to measure the epidemic potential of a network. A number of networks are generated using exponential random graph models based on the properties of the contact network structure of one of the Add Health surveys. The expected number of infections on the original Add Health network is significantly different from that on any of the models derived from it. Because individual-level transmissibility and network structure are not separately identifiable parameters given population-level attack rate data it is possible to re-calibrate the transmissibility to fix this difference. However, the temporal behavior of the outbreak remains significantly different. Hence any estimates of the effectiveness of time dependent interventions on one network are unlikely to generalize to the other. Moreover, we show that in one case even a small perturbation to the network spoils the re-calibration. Unfortunately, the set of sufficient statistics for specifying a contact network model is not yet known. Until it is, estimates of the outcome of a dynamical process on a particular network obtained from simulations on a different network are not reliable.

epidemiology↗