Updates
Model and report changes
- We have reverted to using the regional definitions used by the NHS, dividing the country up into seven regions, rather than the nine ONS regions we have used in our most recent publications.
- A further modification to the model has been required due to the scaling back of the testing programme both in the community and in hospitals. Initially, from March 2020 we were calibrating the model against reported deaths within sixty days of a positive test. More recently we replaced these with data on new diagnoses in hospitals (where testing was still routine). Since 1st September 2022, routine testing of asymptomatic patients has been discontinued, so now we only work with data on new SARS-CoV-2 infections detected in patients within 2 days of their admission. The structure of the model remains similar but we make new assumptions about the proportion of infections that are detected by hospital-based testing, and the time taken post-infection for this detection to occur.
- Over January 2022 our model was redesigned to incorporate the booster vaccination campaign and to be able to capture, in an unbiased way, the ecological effects of the emergence and subsequent dominance of the omicron variant. In particular, we have stratified the entire model by vaccination status so that we can more accurately capture the impacts of waning immunity. The duration of immunity following infection is assumed to have a mean of around 18 months, but this falls rapidly around the time of the emergence of Omicron to account for the immune escape of this variant. The waning of vaccine-derived immunity is captured through an assumed drop in vaccine efficacy at this time.
- We have extended the use of serological data to use samples taken beyond the first wave of the pandemic. The samples are those collected by NHS Blood and Transplant using the Roche-N assay, which measures the prevalence of infection-acquired antibodies in the population.
- The model also accounts for a different susceptibility to infection in each adult age group (no prior information is used); and for the under-15s, (using prior information from Viner et al, 2020, which estimates children to be less likely to acquire infection when in contact with an infectious individual).
- The model has the ability to incorporate estimates of community prevalence, by region and age group, from the Office of National Statistics Coronavirus (COVID-19) Infection Survey (ONS CIS; see Data Sources for details). These are included weekly since the outset of the Survey in May 2020 for the age groups >4 years to provide a more timely source of information on recent trends in incidence.
- The underlying probability of an unvaccinated individual testing positive in hospital following infection with SARS-CoV2 (the apparent infection-hospitalisation rate, IHR) is allowed to change gradually over the course of 30 days every (approximately) 100 days. This is designed to reflect fluctuations due to seasonal effects, demand on healthcare services or the emergence of new virus variants of differing severity.
- The ‘Epidemic summary’ only reports the current value for the IHR by age. To visualise how this has changed over time in our model, see the IHR tab in the ‘Infections and Deaths’ section of the report. The quantity that is now plotted under this tab is the probability of being diagnosed in hospital if infected, taking into account the impact of the immunisation programme - it is an average of a lower rate of hospitalisation among vaccinated individuals and a higher rate among the unvaccinated.
- The attack rate table shows the proportion of individuals to have ever been infected over the course of the pandemic. Under any `Infections’ tab, what is presented is the totality of all infections, including reinfections, and will therefore show values higher than the attack rate might suggest.
Updated findings
- The estimated number of new daily infections on 2nd December across England has increased substantially since our last publication to 183,000 (134,000--245,000, 95% credible interval) infections per day, corresponding to a national daily infection rate of 327 per 100k population. The highest rates are in London (GL) and the Midlands (Mids) (458 and 457 infections per 100k population respectively). All other regions are estimated to have rates below the national average, with the highest rates in the Northern regions (NW and NE, 293 and 279 new infections per 100K population, respectively) with the South East (SE) not far behind. The two regions with the lowest levels of infection still have rates that are higher than any region in our last publication. All estimates are, however, highly uncertain.
- We estimate the daily number of new diagnoses in hospitals to have hit a low on the 19th November. Since this time there has been an increase in the number of new diagnoses among patients admitted to hospital, with the estimate for December 2nd being in the range of 129–203, much higher than the 49–144 in our previous publication. The trend is set to continue such that by the 23rd December there are 198–425 new diagnoses among admissions to hospitals each day. At the current rate, admissions double in number every three weeks.
- The rate of growth of infections in England is 0.04 (0.02-- 0.06) per day. This means that, nationally, the number of infections is increasing, corresponding to an Rt of around 1.30.
- In all regions the central estimate for Rt is greater than 1. The corresponding increase in infections appears fastest in GL and slowest in the East of England (EE). Though infections are increasing nationally, the regional picture is less certain and we present probabilities of 34% and 35% that the epidemic is actually declining in the South West (SW) and EE, respectively.
- Our estimates for the attack rate, the proportion of a population who have ever been infected, is up to 94.7% nationwide, and is now almost certainly over 90% in all regions. The estimated total number of infections to date (89.0m) far exceeds the size of the population of England, due to the presence of reinfections. On average people have experienced over 1.6 infections, though this will differ significantly by age.
- Note that the hospitalised diagnosis data used are only partially informative on Rt over the last two weeks. Therefore, the estimate for current incidence, Rt and the forecast of daily numbers of deaths are likely to be subject to significant revision.
Interpretation
Across England, we estimate that since around the 19th of November the daily number of diagnoses in hospitals has been increasing. PCR-positive infection prevalence is estimated to be most likely increasing in all NHS regions and in all age groups.
Currently Rt is above 1. Based on the periodicity of the Omicron waves and the degree of waning of immunity required to generate these waves, hospital admissions attributable to SARS-CoV-2 infection are anticipated to continue to rise for at least three further weeks beyond the end of the analysis presented here. The estimated levels of incidence represent a large increase from our previous published estimates, which was of 51k--99k infections per day on the 11th November. This estimate is now updated to 79k–88k, but the country has seen substantial growth since.
The Omicron variants have led to more than a tripling in the total number of infections. However, this has not translated into a proportionate increase in new diagnoses in hospitals, which have increased from 190k to 308k. Accordingly, since mid-September, we estimate a steep decline in the infection-hospitalisation ratio in younger age groups (and a less steep decline in older ages groups). This decline also coincides with a change to testing policy for new admissions. Therefore it is difficult to quantify the severity of the virus exactly as both reduced severity and reduced ascertainment will contribute to recent trends in IHR. Currently 0.14% of infections are detected in new admissions to hospital, with this figure rising to 1.1% in the over-75s.
Summary
Real-time tracking of an epidemic, as data accumulate over time, is an essential component of a public health response to a new outbreak. A team of statistical modellers at the MRC Biostatistics Unit (BSU), University of Cambridge, are working to provide regular now-casts and forecasts of COVID-19 infections and deaths. This information feeds directly to the SAGE sub-group, Scientific Pandemic Influenza sub-group on Modelling (SPI-M), and to regional Department of Health and Social Care (DHSC) teams.
Methods
We fit a transmission model (Birrell et al. 2020) to a number of data sources (see 'Data Sources'), to reconstruct the number of new COVID-19 infections over time in different age groups and ONS regions, estimate a measure of ongoing transmission and predict the number of new hospital admissions associated with COVID-19.
Data sources
We use:
- Data on COVID-19 confirmed deaths from the Public Health England (PHE) line-listing This consists of a combination of deaths notified to:
- the Demographics Batch Service (DBS), a mechanism that allows PHE to submit a file of patient information to the National Health Service spine for tracing against the personal demographics service (PDS). PHE submit a line list of patients diagnosed with COVID-19 to DBS daily. The file is returned with a death flag and date of death updated (started 20th March, 2020).
- NHS England, who report data from NHS trusts relating to patients who have died after admission to hospital or within emergency department settings.
- Health Protection Teams (HPTs), resulting from a select survey created by PHE to capture deaths occurring outside of hospital settings, e.g. care homes (started 23rd March, 2020)
- Data on antibody prevalence in blood samples from a PHE survey of NHS Blood Transfusion (NHSBT) donors.
Data are stratified into eight age groups: <1, 1-4, 5-14, 15-24, 25-44, 45-64, 65-74, 75+, and the ONS regions, similar to government office regions (North East, Yorkshire and Humberside, North West, East Midlands, West Midlands, East of England, London, South East, South West).
- Published information on the the natural history of COVID-19 (Verity et al., 2020; Li et al, 2020)
- Information on contacts between different age groups from:
- A Survey that describes relative rates of contacts between different age groups (Mossong et al. 2008).
- Google Community Mobility reports, informing the changes in people’s mobility over the course of the pandemic, particularly after the March 23rd lockdown measures.
- The ONS’ time use survey, which in conjunction with the google mobility study, allows estimation of the changing exposure to infection risk over time.
- Data from the Department for Education describing the proportion of children currently attending school.
- Daily data on the numbers of people getting immunised by age-group and region. These data are derived from the National Immunisation Management Service (NIMS). These data includes all COVID-19 immunisations administered at hospital hubs, local immunisation service sites such as GP practices, and dedicated immunisation centres.
- Data on new diagnoses in hospital testing. This is a composite dataset derived from two sources:
- February-October 2020: The NHS England Secondary Uses Service (SUS) dataset, a collection of complete, accurate information on all hospitalisations with and due to COVID-19 infection. This is a comprehensive dataset but lacks the timeliness required for real-time surveillance, as individual records are completed for an individual and recorded on the system only upon death or hospital discharge.
- October 2020 onwards: NHS England and NHS Improvement COVID-19 Hospital Daily Situation Reports. Prior to this date, the NHS Situation Reports did not have the age-group granularity required by the model.
Epidemic summary
Current \(R_t\)
Value of \(R_t\), the average number of secondary infections due to a typical infection today.
Attack rate
The percentage of a given group that has been infected.
Change in infections incidence
Growth rates
NB: negative growth rates are rates of decline. Values are daily changes.
| England |
0.04 |
0.02 |
0.06 |
| East of England |
0.01 |
-0.05 |
0.07 |
| London |
0.06 |
0.00 |
0.10 |
| Midlands |
0.03 |
-0.01 |
0.07 |
| North East and Yorkshire |
0.03 |
-0.02 |
0.07 |
| North West |
0.04 |
-0.03 |
0.08 |
| South East |
0.03 |
-0.03 |
0.07 |
| South West |
0.01 |
-0.06 |
0.08 |
Halving times
Halving times in days, if a region shows growth than value will be NA.
| England |
NA |
NA |
NA |
| East of England |
NA |
13.38 |
NA |
| London |
NA |
NA |
NA |
| Midlands |
NA |
103.54 |
NA |
| North East and Yorkshire |
NA |
37.72 |
NA |
| North West |
NA |
20.76 |
NA |
| South East |
NA |
25.84 |
NA |
| South West |
NA |
10.34 |
NA |
Doubling times
Doubling times in days, if a region shows decline then the value will be NA.
| England |
16.26 |
10.76 |
32.01 |
| East of England |
54.99 |
10.45 |
NA |
| London |
12.59 |
7.21 |
147.12 |
| Midlands |
19.95 |
10.27 |
NA |
| North East and Yorkshire |
24.71 |
10.13 |
NA |
| North West |
19.35 |
8.39 |
NA |
| South East |
25.76 |
9.90 |
NA |
| South West |
50.58 |
9.10 |
NA |
Change in admissions incidence
Growth rates
NB: negative growth rates are rates of decline. Values are daily changes.
| England |
0.03 |
0.02 |
0.05 |
| East of England |
0.00 |
-0.04 |
0.05 |
| London |
0.05 |
0.01 |
0.10 |
| Midlands |
0.04 |
0.00 |
0.08 |
| North East and Yorkshire |
0.02 |
-0.01 |
0.07 |
| North West |
0.03 |
-0.02 |
0.09 |
| South East |
0.02 |
-0.02 |
0.07 |
| South West |
0.00 |
-0.04 |
0.06 |
Halving times
Halving times in days, if a region shows growth than value will be NA.
| England |
NA |
NA |
NA |
| East of England |
NA |
17.77 |
NA |
| London |
NA |
NA |
NA |
| Midlands |
NA |
NA |
NA |
| North East and Yorkshire |
NA |
59.84 |
NA |
| North West |
NA |
37.90 |
NA |
| South East |
NA |
41.97 |
NA |
| South West |
NA |
16.54 |
NA |
Doubling times
Doubling times in days, if a region shows decline then the value will be NA.
| England |
20.41 |
13.23 |
43.44 |
| East of England |
412.45 |
13.39 |
NA |
| London |
12.78 |
6.96 |
55.83 |
| Midlands |
17.04 |
8.58 |
480.65 |
| North East and Yorkshire |
29.02 |
10.62 |
NA |
| North West |
23.35 |
8.06 |
NA |
| South East |
29.52 |
10.14 |
NA |
| South West |
515.27 |
12.27 |
NA |
## The execution of the prevalence code block will proceed if
## prev.dat exists and this is TRUE
## it is not an external report and this is FALSE
Infections and hospitalisations
The shaded areas show periods of national lockdown, the green lines the dates (once confirmed) of the steps in the roadmap in the UK Governement's COVID-19 Response -- Spring 2021, and the red line shows the date these results were produced (02 Dec).