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Coronavirus (COVID-19): modelling the epidemic (issue no.92)

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.

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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 from mid-January 2021 until mid-December 2021, from which point the projections have underestimated the number of infections, due to the unforeseen effects of the Omicron variant. The same is true for the hospital beds projections, however the ICU beds 24 projections have overestimated the actual figures since mid-December 2021, due to the lower severity of Omicron.

Figure 31. Infections projections versus actuals, for historical projections published between one and two weeks before the actual data came in.
A combination line and scatter chart showing infections projections versus actuals, for historical projections published between one and two weeks before the actual data came in.

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 32. 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 chart showing hospital bed projections versus actuals, for historical projections published between one and two weeks before the actual data came in.

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 33. 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 chart showing ICU bed projections versus actuals, for historical projections published between one and two weeks before the actual data came in.

Which local authorities are likely to experience high levels of Covid-19 in two weeks' time

Table 1. Probability of local authority areas exceeding thresholds of cases per 100K (13th March to 19th March 2022). Data to 28th February.
Probability of exceeding (cases per 100K)
Local Authority (LA) 50 100 300 500 750 1000
Aberdeen City 75-100% 75-100% 50-75% 50-75% 25-50% 5-15%
Aberdeenshire 75-100% 75-100% 75-100% 50-75% 25-50% 25-50%
Angus 75-100% 75-100% 75-100% 50-75% 25-50% 15-25%
Argyll and Bute 75-100% 75-100% 75-100% 75-100% 50-75% 25-50%
City of Edinburgh 75-100% 75-100% 50-75% 25-50% 25-50% 5-15%
Clackmannanshire 75-100% 75-100% 50-75% 50-75% 25-50% 15-25%
Dumfries & Galloway 75-100% 75-100% 75-100% 50-75% 25-50% 25-50%
Dundee City 75-100% 75-100% 50-75% 25-50% 5-15% 0-5%
East Ayrshire 75-100% 75-100% 50-75% 25-50% 15-25% 5-15%
East Dunbartonshire 75-100% 75-100% 75-100% 75-100% 50-75% 50-75%
East Lothian 75-100% 75-100% 75-100% 50-75% 25-50% 25-50%
East Renfrewshire 75-100% 75-100% 75-100% 75-100% 75-100% 50-75%
Falkirk 75-100% 75-100% 50-75% 25-50% 5-15% 0-5%
Fife 75-100% 75-100% 50-75% 25-50% 15-25% 5-15%
Glasgow City 75-100% 75-100% 50-75% 25-50% 15-25% 5-15%
Highland 75-100% 75-100% 75-100% 75-100% 75-100% 50-75%
Inverclyde 75-100% 75-100% 75-100% 50-75% 25-50% 15-25%
Midlothian 75-100% 75-100% 50-75% 25-50% 5-15% 0-5%
Moray 75-100% 75-100% 75-100% 75-100% 50-75% 50-75%
Na h-Eileanan Siar 75-100% 75-100% 50-75% 25-50% 15-25% 5-15%
North Ayrshire 75-100% 75-100% 75-100% 75-100% 50-75% 25-50%
North Lanarkshire 75-100% 75-100% 75-100% 50-75% 25-50% 15-25%
Orkney Islands[13] - - - - - -
Perth and Kinross 75-100% 75-100% 75-100% 50-75% 25-50% 15-25%
Renfrewshire 75-100% 75-100% 75-100% 50-75% 25-50% 25-50%
Scottish Borders 75-100% 75-100% 50-75% 25-50% 15-25% 5-15%
Shetland Islands13 - - - - - -
South Ayrshire 75-100% 75-100% 75-100% 50-75% 25-50% 25-50%
South Lanarkshire 75-100% 75-100% 75-100% 75-100% 50-75% 25-50%
Stirling 75-100% 75-100% 50-75% 25-50% 5-15% 0-5%
West Dunbartonshire 75-100% 75-100% 75-100% 50-75% 25-50% 15-25%
West Lothian 75-100% 75-100% 50-75% 15-25% 5-15% 0-5%

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 ending 21st February and 28th February 2022, with no estimate for error. This is given in Million gene copies per person per day. Coverage is given as percentage of inhabitants in each local authority covered by a wastewater Covid‑19 sampling site delivering data during this period[14].

Table 2. Average Covid-19 wastewater levels (Mgc/p/d) [15].
Local authority (LA) w/e 21st February w/e 28th February Coverage
Aberdeen City 125 69 99%
Aberdeenshire 107 68 52%
Angus 133 77 56%
Argyll and Bute 57 88 23%
City of Edinburgh 92 51 98%
Clackmannanshire 159 89 23%
Dumfries & Galloway 61 68 36%
Dundee City 163 79 100%
East Ayrshire 38 86 72%
East Dunbartonshire 64 100 99%
East Lothian 92 51 65%
East Renfrewshire 39 43 95%
Falkirk 67 72 88%
Fife 68 65 84%
Glasgow City 53 97 98%
Highland 107 85 44%
Inverclyde 48 37 98%
Midlothian 93 52 88%
Moray 52 240 14%
Na h-Eileanan Siar 0%
North Ayrshire 34 54 93%
North Lanarkshire 67 88 92%
Orkney Islands 0%
Perth and Kinross 81 98 38%
Renfrewshire 43 76 97%
Scottish Borders 72 46 59%
Shetland Islands 63 51 29%
South Ayrshire 41 70 88%
South Lanarkshire 62 77 84%
Stirling 35 17 63%
West Dunbartonshire 77 115 98%
West Lothian 72 60 95%

Contact

Email: modellingcoronavirus@gov.scot

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