Rapid review of COVID-19 UK policy focused decision models
Project theme: Applied economic evaluation and policy analysis
Government policy on COVID-19 has been informed by epidemiological modelling examining the impacts of alternative non pharmaceutical interventions (NPIs) on the levels of COVID-19-related hospitalisation and mortality from the disease. Many of the NPIs considered could result in potentially large impacts on costs and outcomes in other parts of the economy. It is unclear the extent to which epidemiological type models of COVID-19 or other pandemics have attempted to capture these wider costs and benefits. There is also uncertainty in whether these models have sought to capture effects on non-COVID-19 health and associated NHS costs. This project aims to review available UK reports detailing models that have sought to reflect impacts on non-COVID-19 health and associated NHS costs wider costs and outcomes. Further, the project will highlight how modelling could be improved to reflect non-COVID-19 health and the benefits and costs beyond health and the health care sector, suggest suitable data to inform these and highlight alternative approaches to trading off the benefits and costs.
Conduct a rapid review of published and preprint papers, as well as grey literature, of models that seek to inform decisions about approaches to managing COVID 19. Models capturing impacts of NPIs beyond COVID-19-related health and beyond health and the health care sector.
Specific questions to address:
What non-COVID-19 health effects and outcomes and costs beyond health and the health care sector have been considered in candidate models of COVID 19?
What interventions and policies have been considered in these methods?
What subpopulations have the model considered? (e.g. age, region, profession)
What evidence sources have they used?
How have any non-financial constraints (e.g. hospital capacity) been reflected in the models?
How, if at all, have different outcomes and costs been aggregated?
Ana Duarte, Simon Walker, Andrew Metry, Ruth Wong, Jasmina Panovska‐Griffiths, Mark Sculpher