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Coronavirus (COVID-19): modelling the epidemic (Issue No.97)

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 projections have overestimated the actual figures since mid-December 2021, due to the lower severity of Omicron.

With the move to wastewater based estimates instead of actual case data, it is not comparable to present previous case based infection projections. We intend to include comparisons of wastewater derived data and projections in future issues.

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 19. 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 20. 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.

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 5th April and 12th April 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[12].

Table 2. Average Covid-19 wastewater levels (Mgc/p/d)[13].

Local authority (LA) w/e 5th April w/e 12th April Coverage
Aberdeen City 138 202 99%
Aberdeenshire 152 202 49%
Angus 240 207 68%
Argyll and Bute 197 262 23%
City of Edinburgh 196 287 98%
Clackmannanshire 242 208 92%
Dumfries & Galloway 198 125 30%
Dundee City 240 246 100%
East Ayrshire 232 248 72%
East Dunbartonshire 202 316 99%
East Lothian 162 260 65%
East Renfrewshire 214 290 95%
Falkirk 236 409 96%
Fife 180 166 84%
Glasgow City 261 298 75%
Highland 111 184 44%
Inverclyde 152 289 98%
Midlothian 196 308 88%
Moray 88 82 70%
Na h-Eileanan Siar 81 0%
North Ayrshire 181 165 92%
North Lanarkshire 225 218 94%
Orkney Islands 291 0%
Perth and Kinross 176 236 45%
Renfrewshire 170 178 97%
Scottish Borders 138 251 32%
Shetland Islands 2 0%
South Ayrshire 192 224 88%
South Lanarkshire 298 249 90%
Stirling 12 128 63%
West Dunbartonshire 127 202 98%
West Lothian 198 223 95%

Contact

Email: sgcentralanalysisdivision@gov.scot

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