Coronavirus (COVID-19): modelling the epidemic (issue no. 62)

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.


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 20. 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 21. 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 22. 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.
Table 1. Probability of local authority areas exceeding thresholds of cases per 100K (8th to 14th August 2021), data to 26th July.
Probability of exceeding (cases per 100k)
Local Authority (LA) 50 100 300 500
Aberdeen City 25-50% 15-25% 0-5% 0-5%
Aberdeenshire 25-50% 5-15% 0-5% 0-5%
Angus 25-50% 5-15% 0-5% 0-5%
Argyll and Bute 50-75% 25-50% 5-15% 0-5%
City of Edinburgh 25-50% 15-25% 0-5% 0-5%
Clackmannanshire 75-100% 50-75% 25-50% 15-25%
Dumfries & Galloway 75-100% 50-75% 15-25% 5-15%
Dundee City 25-50% 5-15% 0-5% 0-5%
East Ayrshire 75-100% 50-75% 15-25% 5-15%
East Dunbartonshire 50-75% 25-50% 5-15% 0-5%
East Lothian 50-75% 25-50% 5-15% 0-5%
East Renfrewshire 50-75% 25-50% 5-15% 0-5%
Falkirk 50-75% 25-50% 5-15% 0-5%
Fife 50-75% 15-25% 0-5% 0-5%
Glasgow City 75-100% 50-75% 5-15% 0-5%
Highland 50-75% 25-50% 5-15% 0-5%
Inverclyde 25-50% 5-15% 0-5% 0-5%
Midlothian 50-75% 25-50% 0-5% 0-5%
Moray 75-100% 50-75% 15-25% 5-15%
Na h-Eileanan Siar 5-15% 0-5% 0-5% 0-5%
North Ayrshire 50-75% 25-50% 5-15% 0-5%
North Lanarkshire 75-100% 50-75% 5-15% 0-5%
Orkney Islands 0-5% 0-5% 0-5% 0-5%
Perth and Kinross 25-50% 15-25% 0-5% 0-5%
Renfrewshire 25-50% 15-25% 0-5% 0-5%
Scottish Borders 25-50% 15-25% 0-5% 0-5%
Shetland Islands 5-15% 0-5% 0-5% 0-5%
South Ayrshire 50-75% 25-50% 15-25% 5-15%
South Lanarkshire 75-100% 25-50% 5-15% 0-5%
Stirling 75-100% 25-50% 5-15% 5-15%
West Dunbartonshire 75-100% 50-75% 15-25% 5-15%
West Lothian 75-100% 25-50% 5-15% 0-5%

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 10th and 17th 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[18].

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[19]
w/b 10th July w/b 17th July w/b 10th July w/b 17th July
Aberdeen City 27.0 51.0 27.0 51.0 80%
Aberdeenshire 27.0 33.0 27.0 30.0 52%
Angus 93.0 46.0 93.0 46.0 56%
Argyll and Bute 2.0 27.0 2.0 27.0 18%
City of Edinburgh 56.0 45.0 56.0 45.0 96%
Clackmannanshire 96.0 55.0 96.0 39.0 92%
Dumfries & Galloway 10.0 25.0 10.0 24.0 36%
Dundee City 92.0 45.0 92.0 45.0 100%
East Ayrshire 32.0 43.0 32.0 43.0 72%
East Dunbartonshire 140.0 60.0 140.0 60.0 99%
East Lothian 79.0 45.0 79.0 45.0 65%
East Renfrewshire 82.0 53.0 82.0 53.0 95%
Falkirk 61.0 33.0 61.0 33.0 69%
Fife 70.0 64.0 70.0 64.0 81%
Glasgow City 129.0 66.0 129.0 66.0 98%
Highland 47.0 32.0 37.0 32.0 37%
Inverclyde 29.0 22.0 29.0 22.0 92%
Midlothian 87.0 45.0 87.0 45.0 73%
Moray 33.0 23.0 32.0 23.0 56%
Na h-Eileanan Siar 13.0 13.0 21%
North Ayrshire 28.0 22.0 28.0 22.0 93%
North Lanarkshire 138.0 98.0 138.0 98.0 95%
Orkney Islands 29.0 6.0 29.0 6.0 34%
Perth and Kinross 72.0 27.0 72.0 27.0 45%
Renfrewshire 88.0 86.0 88.0 86.0 57%
Scottish Borders 16.0 19.0 16.0 17.0 51%
Shetland Islands 3.0 8.0 3.0 8.0 29%
South Ayrshire 27.0 45.0 27.0 45.0 88%
South Lanarkshire 88.0 60.0 71.0 56.0 84%
Stirling 33.0 15.0 33.0 15.0 63%
West Dunbartonshire 77.0 37.0 77.0 37.0 98%
West Lothian 69.0 57.0 69.0 48.0 85%

Contact

Email: modellingcoronavirus@gov.scot

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