Covid-19 and Flattening the Curve: A Feedback Control Perspective.

Many of the policies that were put into place during the Covid-19 pandemic had a common goal: to flatten the curve of the number of infected people so that its peak remains under a critical threshold. This letter considers the challenge of engineering a strategy that enforces such a goal using control theory. We introduce a simple formulation of the optimal flattening problem, and provide a closed form solution.

Models to capture the potential for disease transmission in domestic sheep flocks.

Successful control of livestock diseases requires an understanding of how they spread amongst animals and between premises. Mathematical models can offer important insight into the dynamics of disease, especially when built upon experimental and/or field data. Here the dynamics of a range of epidemiological models are explored in order to determine which models perform best in capturing real-world heterogeneities at sufficient resolution.

Tools to study trends in community structure: application to fish and livestock trading networks.

Partitioning of contact networks into communities allows groupings of epidemiologically related nodes to be derived, that could inform the design of disease surveillance and control strategies, e.g. contact tracing or design of 'firebreaks' for disease spread.