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We analyse JUNE: a detailed model of Covid-19 transmission with high spatial and demographic resolution, developed as part of the RAMP initiative. JUNE requires substantial computational resources to evaluate, making model calibration and general uncertainty analysis extremely challenging. We describe and employ the Uncertainty Quantification approaches of Bayes linear emulation and history matching, to mimic the JUNE model and to perform a global parameter search, hence identifying regions of parameter space that produce acceptable matches to observed data.

We analyze JUNE : a detailed model of COVID-19 transmission with high spatial and demographic resolution, developed as part of the RAMP initiative. JUNE  requires substantial computational resources to evaluate, making model calibration and general uncertainty analysis extremely challenging. We describe and employ the uncertainty quantification approaches of Bayes linear emulation and history matching to mimic JUNE  and to perform a global parameter search, hence identifying regions of parameter space that produce acceptable matches to observed data, and demonstrating the capability of such methods. This article is part of the theme issue ‘Technical challenges of modelling real-life epidemics and examples of overcoming these’.

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Background We undertook a prospective qualitative survey to ascertain the perceptions and experience of National Health Service patients in the United Kingdom who underwent planned or elective procedures and surgery at alternate ‘clean’ hospital sites during the coronavirus disease 2019 (COVID-19) pandemic. These alternate ‘clean’ hospital sites were independent hospitals running active staff and patient testing programmes for COVID-19 and which did not admit or treat patients suffering with COVID-19. Methods A prospective survey was undertaken to include patients at least 30 days after a planned surgery or procedure conducted at a ‘clean’ alternate hospital site during the COVID-19 pandemic. The study was conducted using structured interviews undertaken by trained assessors. A 20% sample group of patients were randomly selected to participate in this study. Qualitative data related to confidence, safety and perceptions of safety were collected. Results Ninety-five patients (60%) reported that they had prior worries or concerns about undergoing an elective procedure during the COVID-19 pandemic. A total of 47 patients (30%) had delayed their surgery at least once because of these concerns. A total of 150 patients (95%) felt that the precautions in place to protect their safety in the setting of an alternate ‘clean’ hospital site were well thought out and proportionate. Patients reported high levels of confidence in the measures undertaken. Separation of patient pathways using the independent sector and patient testing were identified by patients as having the greatest impact on their perception of safety. Conclusions Patient confidence will be key to ensuring uptake of planned and elective procedures and surgery during the COVID-19 pandemic. Perceptions of safety will be key to this confidence and efforts to demonstrably enhance safety are well received by patients. In particular, patients felt that a dedicated programme of patient testing and separation of patient pathways provided the greatest levels of confidence in the safety of their treatment.