Today, the Scientific Advisory Group for Emergencies (SAGE) released an update to a paper estimating the impacts of the coronavirus (COVID-19) on England’s mortality and morbidity. This was a collaboration between the Office for National Statistics (ONS), the Department of Health and Social Care (DHSC), the Government Actuary’s Department (GAD) and the Home Office, as was the case for the previous versions. It was discussed by SAGE on 19 November and 17 December 2020.
This paper presents updates to estimates in a report by the same four departments, discussed by SAGE on 23 July and released on 7 August. We released a statement to coincide with SAGE’s release of the previous version of this paper, outlining the significance and structure of this work.
The latest update continues to present the direct and indirect impacts of the coronavirus (COVID-19) on mortality and morbidity, for the same categories as previously shown. This paper updates estimated impacts for most categories using latest evidence, including an estimate of the possible health impacts “long COVID” could have on the population. The indirect impacts on the wider population have been updated to consider how the pandemic and ongoing levels of government intervention during 2020 will impact health and mortality; and the impact of changes to the economy is now presented using the Office for Budget Responsibility’s November 2020 Economic and fiscal outlook.
The paper presents new scenarios for both the central estimate of impacts, and the “counterfactual” situation in which there is little or no government intervention. Neither scenario is a forecast, so neither represents a prediction of the future trend, nor future government policy. The paper was not released after first presentation to SAGE in November to enable a new counterfactual scenario to be included, in order to provide context to the latest estimated impacts.
The analysis does not explicitly account for the new variant “VUI – 202012/01”, as it was written before evidence of this variant’s increased transmissibility was available; as such, health impacts could be greater than estimated in the paper. This analysis of the COVID-19 pandemic’s impact of excess deaths and morbidity is likely to be updated in the future, when new scenarios and/or evidence emerge.
The main points of the paper for SAGE are now summarised, and the whole paper and executive summary can be found in SAGE’s Meeting 73, 17 December meeting papers.
Main points from “Direct and indirect impacts of COVID-19 on excess deaths and morbidity: December 2020 update”
Under the specific scenarios considered, in most areas of harm our estimates have increased compared with our previous paper. This is largely because of updating the scenarios modelled, which are described in the executive summary and main paper, rather than because of updating the assumptions and methodologies for the categories of harm we have estimated.
Mortality impacts
- In total, we estimate there could be approximately 1.5 million lost quality-adjusted life years (QALYs) due to mortality across all categories and time periods in the main “Winter Scenario”.
- In the short-term across all categories of harm, we estimate 61,000 excess deaths may have occurred between March and September 2020, and 100,000 additional excess deaths may occur under the Winter Scenario between October 2020 and the end of February 2021.
- The greatest number of excess deaths in the short-term (until March 2021) is likely to be seen in direct COVID-19 deaths (Category A) – approximately 120,000 excess deaths.
- Additionally, approximately 40,000 excess deaths may occur in the longer-term (up to 50 years) as a result of economic impacts from the recession (Category D2).
Morbidity impacts
- In total, we estimate approximately 2.9 million lost QALYs because of morbidity across all categories of harm and time periods in the main Winter Scenario.
- The most significant morbidity impacts may occur not directly because of COVID-19 itself, but for the wider population living through a pandemic, as a result of restrictions introduced to control COVID-19, voluntary behaviour changes related to the presence of COVID-19, or the economic impacts of a recession (Category D).
- A new addition to our analysis is an estimated total 174,000 lost QALYs that could occur for people who contract COVID-19 and develop lasting health impacts (for example, fatigue), in order to provide an estimate for the impact of the condition or conditions termed as “long COVID” (Category A).
Counterfactual comparison (three-month period)
These estimates refer to a mitigated scenario where measures are put in place to control the transmission of the virus. We have also explored how these impacts would compare with one possible counterfactual where little or no government intervention is introduced, over a three-month period between the end of December 2020 and the end of March 2021. More information on this scenario is provided in both the executive summary and main paper.
Over a three-month period between the end of December 2020 and the end of March 2021
Category A: In terms of direct COVID-19 deaths, we estimate there could be an additional 97,000 excess deaths in a counterfactual compared with the Winter Scenario.
Category B: In our main scenario, some excess deaths may be expected but have not been quantified because of the unpredictable and uncertain nature of the dynamics as the NHS nears full capacity. In a counterfactual, modelling is less sensitive to this issue of nearing capacity, because in the counterfactual it is more clearly breached. It suggests there may be an additional 76,000 excess deaths because of a lack of NHS critical care capacity leading to worsened outcomes for COVID-19 patients.
Category C: Under a counterfactual there may be 12,000 additional excess deaths from changes to emergency care and 43,000 additional excess deaths from changes to adult social care. We are unable to quantify the impact on elective and primary and community care, but it seems likely there would be more significant health impacts under a counterfactual.
Category D: For health impacts affecting the wider population, it has not been possible to quantify the impact relative to a counterfactual where there is little or no government intervention. This is as a result of no established way in government of determining the degree of voluntary social distancing in the absence of government intervention and the impact of this on the economy. We expect the degree of voluntary social distancing to be related to the dynamic of the pandemic (when transmission is high, individuals are more likely to self-regulate their behaviour, relative to when transmission is lower). Therefore, our main estimates cannot be used to evaluate the impact of measures put in place to control the transmission of COVID-19. In Annex E, we present a discussion of how our estimates relate to a counterfactual with little or no government intervention over the three months between December and the end of February.