A flexible load sharing system and implementation to anticipate and organise transfers based on ICU demand in the context of COVID-19 pandemic

Lacasa, L.; Challen, R.; Brooks-Pollock, E.; Danon, L.

As the number of cases of COVID-19 continues to grow exponentially, local health services are likely to be overwhelmed with patients requiring intensive care. We develop and implement an algorithm to provide optimal re-routing strategies to transfer patients requiring Intensive Care Units (ICU) between hospitals within NHS trusts, constrained by feasibility of transfer. We coarse-grain the NHS system at the level of NHS trusts and, subsequently cover the whole set of geopositioned trusts to extract a 4-regular geometric graph which indicates, for a given trust, its four nearest neighbors. Estimates of weekly ICU demand can be extrapolated from an age structured epidemiological model by considering contagion-to-ICU likelihood estimates, and through random search optimisation we identify the best load sharing strategy. The cost function to minimise is based on the total number of ICU units above capacity and we implement and test two optimisation strategies. Our framework is flexible allowing for additional criteria, different cost functions, and this methodology is general enough that it can easily be extended to optimise other resources beyond ICU units or ventilators. Assuming a uniform ICU demand across trusts, we show that using our method it is possible to enable access to ICU treatment to up to 1000 cases nationally in a single step of the algorithm, leading to potentially saving a large percentage of these lives that would otherwise not have access to ICU if no load sharing was implemented.