Clinical academic research in the time of Corona: a simulation study in England and a call for action

Banerjee, A.; Katsoulis, M.; Lai, A. G.; Pasea, L.; Treibel, T. A.; Manisty, C.; Denaxas, S.; Quarta, G.; Hemingway, H.; Cavalcante, J.; Nousardeghi, M.; Moon, J. C.

Background: Coronavirus (COVID-19) poses health system challenges in every country. As with any public health emergency, a major component of the global response is timely, effective science. However, particular factors specific to COVID-19 must be overcome to ensure that research efforts are optimised. We aimed to model the impact of COVID-19 on the clinical academic response in the UK, and to provide recommendations for COVID-related research. Methods: We constructed a simple stochastic model to determine clinical academic capacity in the UK in four policy approaches to COVID-19 with differing population infection rates: Italy model (6%), mitigation (10%), relaxed mitigation (40%) and do-nothing (80%) scenarios. The ability to conduct research in the COVID-19 climate is affected by the following key factors: (i) infection growth rate and population infection rate (from UK COVID-19 statistics and WHO); (ii) strain on the healthcare system (from published model); and (iii) availability of clinical academic staff with appropriate skillsets affected by frontline clinical activity and sickness (from UK statistics). Findings: In Italy model, mitigation, relaxed mitigation and do-nothing scenarios, from 5 March 2020 the duration (days) and peak infection rates (%) are 95(2.4%), 115(2.5%), 240(5.3%) and 240(16.7%) respectively. Near complete attrition of academia (87% reduction, less than 400 clinical academics) occurs 35 days after pandemic start for 11, 34, 62, 76 days respectively, with no clinical academics at all for 37 days in the do-nothing scenario. Restoration of normal academic workforce (80% of normal capacity) takes 11,12, 30 and 26 weeks respectively. Interpretation: Pandemic COVID-19 crushes the science needed at system level. National policies mitigate, but the academic community needs to adapt. We highlight six key strategies: radical prioritisation (eg 3-4 research ideas per institution), deep resourcing, non-standard leadership (repurposing of key non-frontline teams), rationalisation (profoundly simple approaches), careful site selection (eg protected sites with large academic backup) and complete suspension of academic competition with collaborative approaches.