New analysis from the University of Bristol has evaluated options available to national governments to combat the COVID-19 pandemic using the J Value method, previously applied to mass evacuation scenarios. The method empirically assesses expenditure of a safety scheme against the value of life and potential gains in life expectancy.
The research paper, published in Nanotechnology Perceptions, finds that exceptionally high spending would be justified for three strategies that could reduce significantly the numbers of cases and deaths compared with an unmitigated epidemic.
Assessment of five options available to the UK Government
An epidemic model has been developed to explore the range of possible actions open to the UK and other nations to combat the virus. This model is in fact a simplification of a model devised for the dynamics of a nuclear reactor core.
The five options evaluated were:
- Option 0: "Business as usual", where hospitals are overwhelmed
- Option 1: 4 month lockdown with the start time chosen to minimise deaths and give the UK herd immunity from further Covid-19 epidemics
- Option 2: early 12 month lockdown followed by a lifting of restrictions
- Option 3: early 12 month lockdown followed by a second, optimally timed 4 month lockdown later; greatly enhanced hospital capacity made available by the end of 12 months;
- Option 4: early 12 month lockdown with widespread vaccination at the end of the lockdown period using a newly developed vaccine
A "business as usual" approach would lead to the epidemic being over by September 2020, but it would lead to a loss of life comparable to that suffered by the UK in the Second World War.
Option 2 of a 12-month lockdown would merely delay the onset of the epidemic by a year and the number of deaths would be little altered from Option 0, and is therefore strongly discouraged as an option.
However, Option 3 of a 12 month lockdown followed by an optimally timed 4 month shutdown could cut casualties by two thirds. Similarly, Option 4 where a newly developed vaccine could be deployed would cut the damage done by the coronavirus to less than the average toll on people caused by influenza each year.
Without using J-Value constraints, the exceptionally high spending required for Options 1, 3 and 4 are justified. However when constraints are brought in to ensure GDP per head does not decrease so much that the UK population as a whole loses more life than it gains from the countermeasure, the balance of health and economic outcomes becomes harder.
Philip Thomas, Professor of Risk Management and the author of the paper, commented: “The challenge for the UK Government, and other governments around the world, is to manage its interventions so that the recession that is now inevitable is not significantly worse than that following the 2007 – 2009 financial crash."
Professor Thomas appeared on BBC Radio 4 on Sunday 3rd May on the programme 'A cure at what cost?' at 6 minutes into the programme.[button link="https://www.bbc.co.uk/programmes/m000htrs" bg_color="#806ab7" border="#806ab7" window="yes"]Listen[/button]
The J-value provides an objective tool that assesses the cost-effectiveness of safety schemes for a wide range of industries. It is a new approach, based on established economic theory, that balances safety expenditure against the extension of life-expectancy brought about by the safety scheme.
A major application was in the NREFS Project: Coping with a big nuclear accident that was released in a special issue of Process Safety and Environmental Protection in 2017.
Thomas, P. and May, J. (eds.), 2017, "Coping with a big nuclear accident; Closing papers from the NREFS project", Special Issue of Process Safety and Environmental Protection, Volume 112, Part A, Pages 1–198, November. Get all these open access papers from ScienceDirect
Further information can be found at jvalue.co.uk
Epidemic model source
As mentioned above, the epidemic model used in this paper is a simplification of a model devised for the dynamics of a nuclear reactor core.
This can be found in the book Simulation of Industrial Processes for Control Engineers (Thomas, 1999).