Coronavirus (COVID-19): modelling the epidemic (issue no.79)

Coronavirus (COVID-19): modelling the epidemic in Scotland (Issue No. 79)

Background

This is a report on the Scottish Government modelling of the spread and level of Covid-19. This updates the previous publication on modelling of Covid-19 in Scotland published on 18th November 2021. The estimates in this document help the Scottish Government, the health service and the wider public sector plan and put into place what is needed to keep us safe and treat people who have the virus.

This edition of the research findings focuses on the epidemic as a whole, looking at estimates of R, growth rate and incidence as well as local measures of change in the epidemic.

In Scotland, the modelled estimate for R is between 0.9 and 1.1, with the growth rate between -1% and 1%.

Key Points

• The reproduction rate R in Scotland is currently estimated as being between 0.9 and 1.1, as of 9th November. This has not changed since last week.
• The number of new daily infections for Scotland is estimated as being between 90 and 125, per 100,000 people.
• The growth rate for Scotland is currently estimated as between -1% and 1%. The lower limit has increased and the upper limit has decreased since last week.
• Average contacts from the most recent Panel A cohort of the Scottish Contact Survey (week ending 17th November) indicate an average of 4.8 contacts.
• Mean contacts within the other setting (contacts outside home, school and work) have decreased by 7% in the last two weeks. Contacts within the home and work setting remained at a similar level over the same period.
• The largest increase was reported by the 60-69 age group, increasing overall contacts by 14%. This was largely due to a rise in contacts within the other setting. The biggest decrease was reported in the 18‑29 age group.
• Those aged between 40-49 have reported the biggest decrease in interactions with those aged under 18 in the last two weeks.
• A contact can also be recorded as both indoor and outdoor. The proportion of contacts reported to have been indoors only has remained at similar level to two weeks prior, currently at 72%.
• The number of people wearing a face covering where they have at least one contact outside of the home has increased in the last two weeks from 80% to 83%.
• Hospital occupancy has fallen recently, and ICU occupancy has plateaued. There continues to be uncertainty over hospital occupancy and intensive care in the next four weeks.
• Modelled rates of positive tests per 100K using data to 22nd November indicate that, for the week commencing 5th December 2021, 29 of the 32 local authorities are expected to exceed 50 cases per 100K with at least 75% probability. These 29 local authorities are also expected to exceed 100 cases per 100K with this probability.
• Two local authorities are expected to exceed 300 cases per 100K with at least 75% probability. These are Dumfries & Galloway and Falkirk.
• There are no local authorities which are expected to exceed 500 cases per 100K with at least 75% probability.
• Nationwide, wastewater Covid-19 levels have risen, with the week ending on 23rd November seeing levels of around 77 million gene copies per person per day (Mgc/p/d), up from around 62 Mgc/p/d in the previous week.
• Modelling of long Covid estimates that on 12^th December 2021 between 1.4% and 3.0% of the population are projected to self-classify with long Covid for 12 weeks or more after their first suspected Covid infection in Scotland. The upper limit of the estimate is unchanged from last week.

Recent cases

Figure 1 shows the number of Covid-19 cases reported in Scotland between October and November 2021. The vertical dashed lines indicate the cut off points for each of the modelling inputs; after these dates, the number of cases is not incorporated into the outputs.

R, growth rate and incidence are as of 9th November (dashed line 1). The Scottish Contact Survey uses data to 17th November (dashed line 2). The Scottish Government modelling of infections, hospitalisations and ICU beds, the long Covid analysis, the medium term projections and the modelled rates of positive tests per 100K use data to 22nd November (dashed line 3). Wastewater analysis used data to 23rd November (dashed line 4).

Overview of Scottish Government Modelling

Modelling outputs are provided here on the current epidemic in Scotland as a whole, based on a range of methods. Because it takes a little over three weeks on average for a person who catches Covid-19 to show symptoms, become sick, and either die or recover, there is a time lag in what our model can tell us about any re-emergence of the epidemic and where in Scotland this might occur.

However modelling of Covid-19 deaths is an important measure of where Scotland lies in its epidemic as a whole. In addition, the modelling groups that feed into the UK Health Security Agency (UKHSA) consensus use a range of other data along with deaths in their estimates of R and the growth rate. These outputs are provided in this research findings. The type of data used in each model to estimate R is highlighted in Figure 2.

We use the Scottish Contact Survey (SCS) to inform a modelling technique based on the number of contacts between people. Over time, a greater proportion of the population will be vaccinated. This is likely to impact contact patterns and will become a greater part of the analysis going forwards.

The logistical model utilises results from the epidemiological modelling, principally the number of new infections. The results are split down by age group, and the model is used to give a projection of the number of people that will go to hospital, and potentially to ICU. This will continue to be based on both what we know about how different age groups are affected by the disease and the vaccination rate for those groups to estimate the proportion of cases that will require hospital, and the length of time people that people will stay there.

What the modelling tells us about the epidemic as a whole

The R value and growth rates are estimated by several independent modelling groups based in universities and the UKHSA. Estimates are considered, discussed and combined at the Epidemiology Modelling Review Group (EMRG), which sits within the UKHSA.

UKHSA's consensus view across these methods, was that the value of R as at 9th November^[1] in Scotland was between 0.9 and 1.1 (see Figure 2)^[2].

R is an indicator that lags by two to three weeks and therefore should not be expected to reflect recent fluctuations.

This week the Scottish Government presented two outputs to EMRG. The first uses confirmed cases, as published by Public Health Scotland (PHS), and deaths from National Records Scotland (NRS). The second uses instead wastewater data to estimate the number of cases, and deaths from NRS. Both outputs are shown in Figures 2 and 3.

Source: EMRG

The various groups which report to the EMRG use different sources of data in their models to produce estimates of incidence (Figure 3). UKHSA's consensus view across these methods, as at 9th November, was that the incidence of new daily infections in Scotland was between 90 and 125 new infections per 100,000. This equates to between 4,900 and 6,800 people becoming infected each day in Scotland.

Source: EMRG

The consensus from UKHSA for this week is that the growth rate in Scotland is between -1% and 1% per day as at 9th November. The lower limit has increased and the upper limit has decreased since last week.

What we know about how people's contact patterns have changed

Average contacts from the most recent Panel A cohort of the Scottish Contact Survey (week ending 17th November) indicate an average of 4.8 contacts. This has remained at similar levels compared to the previous Panel A of the survey (week ending 3rd November), as seen in Figure 4.

Mean contacts within the other setting (contacts outside home, school and work) have decreased by 7% in the last two weeks. Contacts within the home and work setting remained at a similar level over the same period.

Figure 5 shows how contacts change across age group and setting. The largest increase was reported by the 60-69 age group, increasing overall contacts by 14%. This was largely due to a rise in contacts within the other setting. The biggest decrease was reported in the 18-29 age group, reducing by 27%.

The heatmaps in Figure 6 show the mean overall contacts between age groups for the weeks relating to 28th October - 3rd November and 11th November - 17th November and the difference between these periods. Those aged between 40-49 have reported the biggest decrease in interactions with those aged under 18 in the last two weeks.

As shown in Figure 7, The biggest changes in the proportion of participants visiting different locations, though slight, is seen in those attending healthcare facility and those visiting an non-essential shop. Visits to a healthcare facility increased from approximately 24% to 26% while the proportion of individuals visiting an non-essential shop decreased from approximately 45% to 42% in the last two weeks.

Figure 8 shows the proportion of participants that reported contacts had indoors and outdoors for contacts individually reported for panel A. A contact can also be recorded as both indoor and outdoor. The proportion of contacts reported to have been indoors only has remained at similar level to two weeks prior, currently at 72%.

Figure 9 shows the number of people wearing a face covering where they have at least one contact outside of the home. This has increased in the last two weeks from 80% to 83%.

What the modelling tells us about estimated infections as well as Hospital and ICU bed demand

The Scottish Government assesses the impact of Covid-19 on the NHS in the next few weeks in terms of estimated number of infections. Figure 10 shows three projections over the four weeks to 20th December.

'Central' assumes that infections will plateau at the current level or fall slightly. 'Worse' assumes a rise in transmission from the current level. 'Better' assumes a drop in transmission^[4].

Figure 11 shows the impact of the projections on the number of people in hospital. The modelling includes all hospital stays, whereas the actuals only include stays up to 28 days duration that are linked to Covid-19.

There continues to be uncertainty over hospital occupancy and intensive care in the next four weeks.

Figure 12 shows the impact of the projection on ICU bed demand.

The methodology for estimating projections is included in the Technical Annex. Also included is a comparison of the actual data against historical projections.

What the modelling tells us about projections of hospitalisations and deaths in the medium term

SPI-M produces projections of the epidemic^[8] (Figures 13 and 14), combining estimates from several independent models (including the Scottish Government's logistics modelling, as shown in Figures 10 to 12). These projections are not forecasts or predictions. They represent a scenario in which the trajectory of the epidemic continues to follow the trends that were seen in the data up to 22nd November and do not include the effects of any future policy or behavioural changes.

The delay between infection, developing symptoms, the need for hospital care, and death means they cannot fully reflect the impact of behaviour changes in the two to three weeks prior to 22nd November. Projecting forwards is difficult when the numbers of admissions and deaths fall to very low levels, which can result in wider credible intervals reflecting greater uncertainty. The interquartile range should be used, with judgement, as the projection from which estimates may be derived until 21st December.

These projections include the potential impact of vaccinations over the next few weeks. Modelling groups have used their expert judgement and evidence from UKHSA, Scottish Universities & Public Health Scotland, and other published efficacy studies when making assumptions about vaccine effectiveness.

What we know about which local authorities are likely to experience high levels of Covid-19 in two weeks' time

We continue to use modelling based on Covid-19 cases and deaths using data to 22nd November from several academic groups to give us an indication of whether a local authority is likely to experience high levels of Covid-19 in the future. This has been compiled via UKHSA into a consensus. In this an area is defined as a hotspot if the two week prediction of cases (positive tests) per 100K population is predicted to exceed a threshold, e.g. 500 cases.

There is uncertainty in regions with smaller populations, and hence lower test counts, in particular in regions such as Na h-Eileanan Siar, Orkney Islands and Shetland Islands.

Modelled rates of positive tests per 100K using data to 22nd November (Figure 15) indicate that, for the week commencing 5th December 2021, 29 of the 32 local authorities are expected to exceed 50 cases per 100K with at least 75% probability. These 29 local authorities are also expected to exceed 100 cases per 100K with this probability^[9].

Two local authorities are expected to exceed 300 cases per 100K with at least 75% probability. These are Dumfries & Galloway and Falkirk.

There are no local authorities which are expected to exceed 500 cases per 100K with at least 75% probability^[10].

What can analysis of wastewater samples tell us about local outbreaks of Covid-19 infection?

Levels of Covid-19 RNA in wastewater (WW) collected at a number of sites around Scotland are adjusted for population and local changes in intake flow rate (or ammonia levels where flow is not available) and compared to 7-day average daily new case rates derived from Local Authority and Neighbourhood (Intermediate Zone) level aggregate data. See Technical Annex in Issue 34 of these Research Findings for the methodology.

Nationwide, wastewater Covid-19 levels have risen, with the week ending on 23rd November seeing levels of around 77 million gene copies per person per day (Mgc/p/d), up from around 62 Mgc/p/d in the previous week (week ending 16th November). These changes in WW Covid-19 levels appear broadly across Scotland, but are not reflected as of yet in case data, and thus it is unclear if they are indicative of a major change in the WW trend.

Figure 16 shows the national running average trend (over a 7-day period) for the full set of sampled sites, with a small number of unrealistically large outliers excluded. In this figure, we see the rise in WW Covid-19 levels, attaining values slightly less than the peak we saw at the start of November. Meanwhile, case numbers have been rising only slowly since October, with a slight and likely insignificant dip at the end of the period. In Figure 16 we also consider data from the Office of National Statistics' Coronavirus Infection Survey (CIS), with positivity estimates up to 13th November – however, the observed rise in viral levels would be after this date. The rise is not limited to sites around Glasgow, and does come with the caveat of substantial recent variability in WW Covid-19 data. Thus it is unclear at present if this is likely to persist or represents a temporary effect as was seen at the start of November.

What estimates do we have of the number of people experiencing long Covid symptoms?

The Scottish Government is modelling the number of people likely to experience long Covid symptoms. This gives a projection of estimated self-reported long Covid rates in the future, based on Scottish Government medium term projection modelling, as set out in Figure 17.

This modelling estimates that at 12th December 2021 between 79,000 (1.4% of the population) and 166,000 (3.0%) people are projected to self-classify with long Covid for 12 weeks or more after their first suspected Covid infection in Scotland. The upper limit of the estimate is unchanged from last week.

These are preliminary results, further data on rates of long Covid and associated syndromes as research emerges are required.

See the Technical Annex in issue 73 for information about the methodology.

What next?

The modelled estimates of the numbers of new cases and infectious people will continue to be provided as measures of the epidemic as a whole, along with measures of the current point in the epidemic such as R_t and the growth rate.

We may report on exceedance in future weeks when the background levels of Covid-19 reduces so that it can be useful in identifying outbreaks.