If the UK’s planned distribution of a vaccine for covid-19 is to win widespread support it should be both clinically and cost effective. One dilemma is between prioritizing those at greatest risk of death or illness against those who are most likely to transmit the disease. Given the age profile of those affected by covid-19, this is between older people and the young. Another dilemma has to do with whether the focus should be on minimizing loss of life or life years.
The Joint Committee on Vaccination and Immunisation (JCVI) is the equivalent of NICE in this instance. It has outlined an interim ranking of priorities as a combination of clinical risk stratification and an age-based approach: 
- older adults’ resident in a care home and care home workers,
- all those 80 years of age and over and health and social care workers,
- all those 75 years of age and over, followed by each progressively younger age groups.
The JCVI’s policy clearly prioritises the oldest along with health and social care workers. The basis for this is not explained, but the policy is stated to be based on a review of UK epidemiological data on the impact of the covid-19 pandemic so far and modelling of impact, but not of cost effectiveness.
Studies on optimal vaccine distribution
A recent study which modelled the impact of different UK distribution strategies may provide the rationale for the JCVI’s policy.  It used an extended epidemiological Susceptible-Exposed-Infectious-Removed model to estimate optimal distribution by group, defined by age, co-morbidity, and if people worked in health or social care. Scenarios explored three types of vaccine: those reducing transmission, reducing symptoms, or reducing severe symptoms. The study compared priority order with equal access by group, defined mainly by age but also by comorbidity along with two groups made up of health and social care workers. Its aim was to minimize the health loss measured in both deaths and QALYs. It found age prioritization to be the optimal strategy unless vaccine efficacy was low. This result was robust across different scenarios. Health and social care workers were given the highest priority along with the eldest based on the model.
The study comes from a unit in Warwick University headed by Matt Keeling, a well established epidemiological modeller and member of JCVI. The work was funded by the National Institute for Health Research. The model was calibrated on UK data on demography and experience of covid infections.
A US study addressed the same issue taking a slightly different approach. This assessed optimal distribution by age only with a pro rata allocation.  It aimed to optimize deaths, symptomatic infections, ICU and non ICU hospitalisations. It used an optimization algorithm to consider the effectiveness of different levels of vaccine effectiveness and coverage.
It found that the optimal approach was prioritization by risk, that is by older age. This applied whether vaccine efficacy was low (<60%) or high (>60%) except in one instance. That exception was when both efficacy and coverage were high when the priority shifted in favour of prioritization of reducing transmission.
Both papers support prioritization as outlined by JCVI in large part. This is perhaps not too surprising given one of the authors of the UK study, Matt Keeling is also a member of JCVI. The paper above may well have influenced JCVI thinking. The JCVI guidance mentions modelling of this sort.
The main difference between the UK and US studies has to do with high coverage vaccines in which case the US paper favours prioritization of reduced transmission. This would favour healthcare workers which the US study assumed would be given priority.
The finding that prioritization by age is optimal by age is less surprising in relation to minimizing deaths than in relation to QALYs. This is because of the reduced life expectancy of older people. It means that the gradient of increased risk by age offsets the reduced life expectancy.
Although cost effectiveness is not considered in either, inclusion of costs seems unlikely to change the conclusions. A single price per dose and delivery seems likely. Other costs such as that of treatment and death seem unlikely to vary much. So cost effectiveness seems likely to be achieved as well.
Finally, these findings should be contrasted with what might otherwise happen. Without state control, vaccines might be distributed though the market with those willing to pay being first. While a fairer approach would involve equal distribution by age group, the proposed prioritization has the effect of minimizing both the deaths and morbidity due to covid-19.
James Raftery is a health economist with several decades’ experience of the NHS. He is professor of health technology assessment at Southampton University.
Competing interests: None declared.
2] Keeling et al ref Modelling optimal vaccination strategy for SARS-CoV-2 in the UK Sam Moore, Edward M Hill, Louise Dyson, Michael Tildesley, Matt J Keeling.https://www.medrxiv.org/content/10.1101/2020.09.22.20194183v2
3] PLoS Comput Biol. 2013 Mar; 9(3): e1002964. Published online 2013 Mar 21. doi: 10.1371/journal.pcbi.1002964 PMCID: PMC3605056 PMID: 23555207 Optimal Vaccine Allocation for the Early Mitigation of Pandemic Influenza