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Coronavirus (COVID-19): modelling the epidemic (issue no. 61)

Latest findings in modelling the COVID-19 epidemic in Scotland, both in terms of the spread of the disease through the population (epidemiological modelling) and of the demands it will place on the system, for example in terms of health care requirement.

This document is part of a collection


Technical Annex

Epidemiology is the study of how diseases spread within populations. One way we do this is using our best understanding of the way the infection is passed on and how it affects people who catch it to create mathematical simulations. Because people who catch Covid-19 have a relatively long period in which they can pass it on to others before they begin to have symptoms, and the majority of people infected with the virus will experience mild symptoms, this "epidemiological modelling" provides insights into the epidemic that cannot easily be measured through testing e.g. of those with symptoms, as it estimates the total number of new daily infections and infectious people, including those who are asymptomatic or have mild symptoms.

Modelling also allows us to make short-term forecasts of what may happen with a degree of uncertainty. These can be used in health care and other planning. The modelling in this research findings is undertaken using different types of data which going forward aims to both model the progress of the epidemic in Scotland and provide early indications of where any changes are taking place.

The delivery of the vaccination programme will offer protection against severe disease and death. The modelling includes assumptions about compliance with restrictions and vaccine take-up. Work is still ongoing to understand how many vaccinated people might still spread the virus if infected. As Covid-19 is a new disease there remain uncertainties associated with vaccine effectiveness. Furthermore, there is a risk that new variants emerge for which immunisation is less effective.

How the modelling compares to the real data as it emerges

The following charts show the history of our modelling projections in comparison to estimates of the actual data. The infections projections were largely accurate during October to mid-December and from mid‑January onward. During mid-December to mid-January, the projections underestimated the number of infections, due to the unforeseen effects of the new variant.

Figure 17. Infections projections versus actuals, for historical projections published between one and two weeks before the actual data came in.
A combination line and scatter graph comparing infections projections against actuals.

Hospital bed projections have generally been more precise than infections estimates due to being partially based on already known information about numbers of current infections, and number of people already in hospital. The projections are for number of people in hospital due to Covid-19, which is slightly different to the actuals, which are number of people in hospital within 28 days of a positive Covid-19 test.

Figure 18. Hospital bed projections versus actuals, for historical projections published between one and two weeks before the actual data came in.
A combination line and scatter graph comparing hospital bed occupancy projections against actuals.

As with hospital beds, ICU bed projections have generally been more precise than infections. The projections are for number of people in ICU due to Covid-19. The actuals are number of people in ICU within 28 days of a positive Covid-19 test up to 20 January, after which they include people in ICU over the 28 day limit.

Figure 19. ICU bed projections versus actuals, for historical projections published between one and two weeks before the actual data came in.
A combination line and scatter graph comparing ICU occupancy projections against actuals.

Long COVID

Long Covid is a complex condition, with an emerging, but limited, evidence base. It is characterised by the existence of symptoms for several weeks or months after acute Covid-19. As the available evidence accrues techniques need to be developed to assess the prevalence of long Covid at national and sub-national level in Scotland to inform health board planning.

Emerging evidence shows that a significant proportion of people who have contracted Covid-19 go on to have long term rehabilitation support needs. This is not limited just to intensive care survivors and those who received acute hospital care, for whom needs can be complex and varied.

The condition usually presents with clusters of symptoms, often overlapping, which may change over time and can affect many systems within the body. Common symptoms can include, but are not limited to: fatigue, persisting high temperature, breathlessness, cognitive impairment, generalised pain, and mental health problems.

The term long Covid is commonly used to describe signs and symptoms that continue or develop after acute Covid-19 and are not explained by an alternative diagnosis. It includes both ongoing symptomatic Covid-19 (from 4 to 12 weeks) and post-Covid-19 syndrome (12 weeks or more). The ONS has provided estimates publically of the number of people in the community population in Scotland with self-reported long Covid[13].

A significant proportion of people that experienced milder symptoms during their initial illness struggle with a range of longer lasting symptoms.

Table 1. Probability of local authority areas exceeding thresholds of cases per 100K (1 st to 8 th August 2021), data to 19th July.

Probability of exceeding (cases per 100k)
Local Authority (LA) 20 50 100 150 300 500 750 1000 2000
Aberdeen City 75-100% 75-100% 75-100% 50-75% 50-75% 50-75% 15-25% 15-25% 5-15%
Aberdeenshire 75-100% 75-100% 75-100% 50-75% 50-75% 25-50% 15-25% 5-15% 0-5%
Angus 75-100% 75-100% 75-100% 75-100% 50-75% 50-75% 25-50% 15-25% 0-5%
Argyll and Bute 75-100% 75-100% 50-75% 50-75% 25-50% 5-15% 5-15% 0-5% 0-5%
City of Edinburgh 75-100% 75-100% 75-100% 75-100% 50-75% 50-75% 25-50% 25-50% 25-50%
Clackmannanshire 75-100% 75-100% 75-100% 75-100% 50-75% 25-50% 0-5% 0-5% 0-5%
Dumfries & Galloway 75-100% 75-100% 75-100% 75-100% 50-75% 25-50% 15-25% 5-15% 0-5%
Dundee City 75-100% 75-100% 75-100% 75-100% 50-75% 50-75% 25-50% 25-50% 15-25%
East Ayrshire 75-100% 75-100% 75-100% 50-75% 50-75% 25-50% 25-50% 15-25% 5-15%
East Dunbartonshire 75-100% 75-100% 75-100% 75-100% 50-75% 25-50% 15-25% 15-25% 5-15%
East Lothian 75-100% 75-100% 75-100% 75-100% 50-75% 50-75% 25-50% 15-25% 0-5%
East Renfrewshire 75-100% 75-100% 75-100% 75-100% 50-75% 50-75% 25-50% 15-25% 0-5%
Falkirk 75-100% 75-100% 75-100% 75-100% 50-75% 25-50% 15-25% 5-15% 0-5%
Fife 75-100% 75-100% 75-100% 75-100% 50-75% 50-75% 25-50% 25-50% 15-25%
Glasgow City 75-100% 75-100% 75-100% 75-100% 50-75% 50-75% 25-50% 25-50% 25-50%
Highland 75-100% 75-100% 75-100% 75-100% 50-75% 25-50% 5-15% 0-5% 0-5%
Inverclyde 75-100% 75-100% 50-75% 50-75% 50-75% 25-50% 15-25% 0-5% 0-5%
Midlothian 75-100% 75-100% 75-100% 75-100% 50-75% 50-75% 25-50% 15-25% 0-5%
Moray 75-100% 75-100% 75-100% 50-75% 50-75% 25-50% 15-25% 5-15% 0-5%
Na h-Eileanan Siar 25-50% 25-50% 25-50% 25-50% 5-15% 0-5% 0-5% 0-5% 0-5%
North Ayrshire 75-100% 75-100% 50-75% 50-75% 50-75% 25-50% 25-50% 15-25% 5-15%
North Lanarkshire 75-100% 75-100% 75-100% 75-100% 50-75% 50-75% 25-50% 25-50% 15-25%
Orkney Islands 25-50% 25-50% 5-15% 5-15% 0-5% 0-5% 0-5% 0-5% 0-5%
Perth and Kinross 75-100% 75-100% 75-100% 75-100% 50-75% 50-75% 25-50% 15-25% 0-5%
Renfrewshire 75-100% 75-100% 75-100% 75-100% 75-100% 50-75% 25-50% 25-50% 15-25%
Scottish Borders 75-100% 75-100% 75-100% 50-75% 50-75% 25-50% 5-15% 0-5% 0-5%
Shetland Islands 25-50% 25-50% 25-50% 25-50% 25-50% 25-50% 15-25% 5-15% 0-5%
South Ayrshire 75-100% 75-100% 75-100% 75-100% 50-75% 25-50% 15-25% 5-15% 0-5%
South Lanarkshire 75-100% 75-100% 75-100% 75-100% 50-75% 25-50% 25-50% 25-50% 25-50%
Stirling 75-100% 75-100% 75-100% 75-100% 50-75% 25-50% 5-15% 0-5% 0-5%
West Dunbartonshire 75-100% 75-100% 75-100% 50-75% 50-75% 25-50% 15-25% 5-15% 0-5%
West Lothian 75-100% 75-100% 75-100% 75-100% 50-75% 50-75% 25-50% 25-50% 15-25%

What levels of Covid-19 are indicated by wastewater (WW) data?

Table 2 provides population weighted daily averages for normalised WW Covid-19 levels in the weeks beginning the 7th and 14th July, with no estimate for error. This is given in Million gene copies per person, which approximately corresponds to new cases per 100,000 per day. Coverage is given as percentage of LA inhabitants covered by a wastewater Covid‑19 sampling site delivering data during this period[14].

Table 2. Average daily cases per 100k as given by WW data

Local authority (LA) Average daily WW case estimate,
with outliers included
Average daily WW case estimate,
with outliers removed
Coverage[15]
w/b 7th July w/b 14th July w/b 7th July w/b 14th July
Aberdeen City 52.0 46.0 52.0 46.0 80%
Aberdeenshire 49.0 28.0 35.0 28.0 53%
Angus 156.0 81.0 156.0 81.0 56%
Argyll and Bute 5.0 - 5.0 - 0%
City of Edinburgh 68.0 63.0 68.0 63.0 97%
Clackmannanshire 68.0 204.0 68.0 123.0 11%
Dumfries & Galloway 22.0 21.0 20.0 20.0 35%
Dundee City 179.0 90.0 179.0 90.0 100%
East Ayrshire 28.0 32.0 28.0 32.0 72%
East Dunbartonshire 138.0 85.0 138.0 85.0 0%
East Lothian 90.0 59.0 90.0 59.0 65%
East Renfrewshire 80.0 52.0 80.0 52.0 95%
Falkirk 64.0 48.0 64.0 48.0 69%
Fife 86.0 48.0 86.0 48.0 83%
Glasgow City 112.0 67.0 112.0 67.0 59%
Highland 53.0 30.0 43.0 30.0 36%
Inverclyde 31.0 25.0 31.0 25.0 93%
Midlothian 97.0 63.0 97.0 63.0 73%
Moray 30.0 33.0 25.0 33.0 56%
Na h-Eileanan Siar 0.0 12.0 0.0 12.0 21%
North Ayrshire 30.0 22.0 30.0 22.0 92%
North Lanarkshire 116.0 76.0 116.0 76.0 24%
Orkney Islands 18.0 6.0 18.0 6.0 34%
Perth and Kinross 51.0 37.0 51.0 37.0 45%
Renfrewshire 81.0 86.0 81.0 86.0 57%
Scottish Borders 20.0 75.0 20.0 26.0 5%
Shetland Islands 3.0 11.0 3.0 11.0 29%
South Ayrshire 25.0 33.0 25.0 33.0 88%
South Lanarkshire 73.0 59.0 65.0 59.0 67%
Stirling 45.0 22.0 45.0 22.0 10%
West Dunbartonshire 77.0 - 77.0 - 0%
West Lothian 79.0 44.0 79.0 44.0 85%

Contact

Email: modellingcoronavirus@gov.scot

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