Coronavirus (COVID-19): modelling the epidemic (issue no. 74)

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 2020 and from mid‑January 2021 onwards. During mid-December 2020 to mid‑January 2021, the projections underestimated the number of infections, due to the unforeseen effects of the new variant.

Figure 19. Infections projections versus actuals, for historical projections published between one and two weeks before the actual data came in.
Figure 19. 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 20. Hospital bed projections versus actuals, for historical projections published between one and two weeks before the actual data came in.
Figure 20. 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 2021, after which they include people in ICU over the 28 day limit.

Figure 21. ICU bed projections versus actuals, for historical projections published between one and two weeks before the actual data came in.
Figure 21. 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 (31st October to 6th November 2021), data to 18th October.
Probability of exceeding (cases per 100K)
Local Authority (LA) 50 100 300 500
Aberdeen City 75-100% 75-100% 25-50% 5-15%
Aberdeenshire 75-100% 75-100% 25-50% 5-15%
Angus 75-100% 75-100% 25-50% 25-50%
Argyll and Bute 75-100% 50-75% 15-25% 5-15%
City of Edinburgh 75-100% 75-100% 25-50% 15-25%
Clackmannanshire 75-100% 75-100% 25-50% 25-50%
Dumfries & Galloway 75-100% 50-75% 15-25% 0-5%
Dundee City 75-100% 75-100% 25-50% 15-25%
East Ayrshire 75-100% 75-100% 25-50% 15-25%
East Dunbartonshire 75-100% 75-100% 50-75% 25-50%
East Lothian 75-100% 75-100% 25-50% 25-50%
East Renfrewshire 75-100% 75-100% 25-50% 15-25%
Falkirk 75-100% 75-100% 25-50% 15-25%
Fife 75-100% 75-100% 50-75% 25-50%
Glasgow City 75-100% 75-100% 25-50% 5-15%
Highland 50-75% 25-50% 25-50% 15-25%
Inverclyde 75-100% 50-75% 15-25% 0-5%
Midlothian 75-100% 50-75% 15-25% 5-15%
Moray 75-100% 50-75% 25-50% 15-25%
Na h-Eileanan Siar 15-25% 5-15% 0-5% 0-5%
North Ayrshire 75-100% 75-100% 25-50% 15-25%
North Lanarkshire 75-100% 75-100% 25-50% 15-25%
Orkney Islands 15-25% 0-5% 0-5% 0-5%
Perth and Kinross 75-100% 75-100% 25-50% 5-15%
Renfrewshire 75-100% 75-100% 50-75% 25-50%
Scottish Borders 75-100% 75-100% 25-50% 25-50%
Shetland Islands 5-15% 0-5% 0-5% 0-5%
South Ayrshire 75-100% 75-100% 25-50% 15-25%
South Lanarkshire 75-100% 75-100% 50-75% 25-50%
Stirling 75-100% 75-100% 50-75% 25-50%
West Dunbartonshire 75-100% 75-100% 25-50% 5-15%
West Lothian 75-100% 75-100% 50-75% 25-50%

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

Table 2 provides population weighted daily averages for normalised WW Covid-19 levels in the weeks beginning 6th and 13th October 2021, 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[15].

Table 2. Average daily cases per 100k as given by WW data [16].
Local authority (LA) w/b 6th October w/b 13th October Coverage
Aberdeen City 40 55 80%
Aberdeenshire 66 65 48%
Angus 77 84 43%
Argyll and Bute 0%
City of Edinburgh 35 38 96%
Clackmannanshire 35 91 92%
Dumfries & Galloway 63 56 32%
Dundee City 77 84 100%
East Ayrshire 46 56 72%
East Dunbartonshire 95 46 99%
East Lothian 33 34 65%
East Renfrewshire 36 75 89%
Falkirk 72 64 59%
Fife 62 56 79%
Glasgow City 72 58 98%
Highland 33 46 37%
Inverclyde 31 45 92%
Midlothian 47 40 88%
Moray 72 47 55%
Na h-Eileanan Siar 10 21%
North Ayrshire 41 27 84%
North Lanarkshire 62 73 81%
Orkney Islands 12 0%
Perth and Kinross 49 69 38%
Renfrewshire 45 77 57%
Scottish Borders 29 20 39%
Shetland Islands 1 0%
South Ayrshire 46 59 77%
South Lanarkshire 47 64 62%
Stirling 39 63%
West Dunbartonshire 95 46 48%
West Lothian 117 66 77%

Contact

Email: modellingcoronavirus@gov.scot

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