Coronavirus (COVID-19): modelling the epidemic (Issue No.96)
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.
Which local authorities are likely to experience high levels of Covid-19 in two weeks' time
Table 2. Probability of local authority areas exceeding thresholds of cases per 100K (10th to 16th April 2022), data to 28th March. The local modelling consensus will be paused in future weeks but will be ready to re-instate if required in the future.
| Local Authority | Probability of exceeding (cases per 100K) | ||||||
|---|---|---|---|---|---|---|---|
| 50 | 100 | 300 | 500 | 600 | 750 | 1000 | |
| Aberdeen City | 75-100% | 75-100% | 75-100% | 75-100% | 75-100% | 50-75% | 50-75% |
| Aberdeenshire | 75-100% | 75-100% | 75-100% | 75-100% | 75-100% | 50-75% | 50-75% |
| Angus | 75-100% | 75-100% | 75-100% | 50-75% | 50-75% | 50-75% | 25-50% |
| Argyll and Bute | 75-100% | 75-100% | 75-100% | 75-100% | 50-75% | 50-75% | 50-75% |
| City of Edinburgh | 75-100% | 75-100% | 75-100% | 75-100% | 75-100% | 75-100% | 50-75% |
| Clackmannanshire | 75-100% | 75-100% | 75-100% | 50-75% | 50-75% | 50-75% | 25-50% |
| Dumfries & Galloway | 75-100% | 75-100% | 75-100% | 75-100% | 75-100% | 50-75% | 50-75% |
| Dundee City | 75-100% | 75-100% | 75-100% | 75-100% | 75-100% | 50-75% | 25-50% |
| East Ayrshire | 75-100% | 75-100% | 75-100% | 50-75% | 50-75% | 50-75% | 50-75% |
| East Dunbartonshire | 75-100% | 75-100% | 75-100% | 50-75% | 50-75% | 50-75% | 50-75% |
| East Lothian | 75-100% | 75-100% | 75-100% | 50-75% | 50-75% | 50-75% | 50-75% |
| East Renfrewshire | 75-100% | 75-100% | 75-100% | 75-100% | 50-75% | 50-75% | 25-50% |
| Falkirk | 75-100% | 75-100% | 75-100% | 75-100% | 75-100% | 50-75% | 50-75% |
| Fife | 75-100% | 75-100% | 75-100% | 75-100% | 75-100% | 75-100% | 50-75% |
| Glasgow City | 75-100% | 75-100% | 75-100% | 75-100% | 75-100% | 50-75% | 25-50% |
| Highland | 75-100% | 75-100% | 75-100% | 75-100% | 50-75% | 50-75% | 50-75% |
| Inverclyde | 75-100% | 75-100% | 75-100% | 50-75% | 50-75% | 50-75% | 25-50% |
| Midlothian | 75-100% | 75-100% | 75-100% | 75-100% | 75-100% | 50-75% | 50-75% |
| Moray | 75-100% | 75-100% | 75-100% | 75-100% | 50-75% | 50-75% | 25-50% |
| Na h-Eileanan Siar[15] | - | - | - | - | - | - | - |
| North Ayrshire | 75-100% | 75-100% | 75-100% | 75-100% | 50-75% | 50-75% | 50-75% |
| North Lanarkshire | 75-100% | 75-100% | 75-100% | 75-100% | 75-100% | 50-75% | 25-50% |
| Orkney Islands[15] | - | - | - | - | - | - | - |
| Perth and Kinross | 75-100% | 75-100% | 75-100% | 75-100% | 75-100% | 50-75% | 50-75% |
| Renfrewshire | 75-100% | 75-100% | 75-100% | 75-100% | 50-75% | 50-75% | 50-75% |
| Scottish Borders | 75-100% | 75-100% | 75-100% | 75-100% | 75-100% | 75-100% | 50-75% |
| Shetland Islands[15] | - | - | - | - | - | - | - |
| South Ayrshire | 75-100% | 75-100% | 75-100% | 75-100% | 75-100% | 50-75% | 50-75% |
| South Lanarkshire | 75-100% | 75-100% | 75-100% | 50-75% | 50-75% | 50-75% | 25-50% |
| Stirling | 75-100% | 75-100% | 75-100% | 75-100% | 50-75% | 50-75% | 50-75% |
| West Dunbartonshire | 75-100% | 75-100% | 75-100% | 50-75% | 50-75% | 50-75% | 25-50% |
| West Lothian | 75-100% | 75-100% | 75-100% | 75-100% | 75-100% | 50-75% | 50-75% |
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 22nd March and 29th March 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.[16]
| Local authority (LA) | w/e 22nd March | w/e 29th March | Coverage |
|---|---|---|---|
| Aberdeen City | 125 | 210 | 80% |
| Aberdeenshire | 180 | 232 | 28% |
| Angus | 256 | 258 | 68% |
| Argyll and Bute | 102 | 311 | 29% |
| City of Edinburgh | 205 | 265 | 98% |
| Clackmannanshire | 270 | 752 | 11% |
| Dumfries & Galloway | 197 | 156 | 35% |
| Dundee City | 256 | 279 | 100% |
| East Ayrshire | 112 | 411 | 72% |
| East Dunbartonshire | 275 | 297 | 99% |
| East Lothian | 228 | 249 | 65% |
| East Renfrewshire | 196 | 360 | 95% |
| Falkirk | 273 | 333 | 88% |
| Fife | 184 | 370 | 73% |
| Glasgow City | 235 | 320 | 75% |
| Highland | 289 | 421 | 34% |
| Inverclyde | 248 | 236 | 98% |
| Midlothian | 210 | 242 | 88% |
| Moray | 313 | – | 0% |
| Na h-Eileanan Siar | – | – | 0% |
| North Ayrshire | 166 | 242 | 84% |
| North Lanarkshire | 196 | 298 | 91% |
| Orkney Islands | 168 | 284 | 34% |
| Perth and Kinross | 234 | 136 | 38% |
| Renfrewshire | 205 | 272 | 97% |
| Scottish Borders | 102 | 175 | 46% |
| Shetland Islands | 47 | – | 0% |
| South Ayrshire | 138 | 338 | 77% |
| South Lanarkshire | 141 | 385 | 74% |
| Stirling | 45 | 166 | 63% |
| West Dunbartonshire | 190 | 229 | 98% |
| West Lothian | 227 | 396 | 79% |
How will Scottish Government models be used in the future?
The following table provides information of the Covid-19 models used in Scottish Government, their outputs, the section they refer to in the Modelling the Epidemic report and changes to the frequency of results.
Over the coming weeks, archiving of models will be undertaken via the publicly available Data Science Scotland GitHub organisation.[18]
| Model |
Outputs |
Section in Modelling the Epidemic Report |
Change |
|---|---|---|---|
| Scottish Contact Survey |
Average number and nature of contacts for adults in Scotland per day |
What we know about how people's contact patterns have changed |
Weekly panels will be merged together and results will published fortnightly |
| Wastewater |
National and local Covid-19 estimates Sequencing outputs |
What can analysis of wastewater samples tell us about local outbreaks of Covid-19 infection? |
Weekly updates will still be available. Results will be published fortnightly. |
| Covasim |
Estimates R using contact patterns |
Not currently published |
This is still in development. Estimates will be published fortnightly as part of the EMRG consensus |
| Epidemia |
Estimates of R incidence and growth rate |
Overview of Scottish Government Modelling |
Estimates will be published fortnightly as part of the EMRG consensus |
| Long Covid |
A projection of estimated self-reported long Covid-19 rates in the future |
Long Covid Estimates |
Work will be undertaken to assess if this project can continue. |
| Medium Term Projections Modelling |
Projections for incidence, hospital beds, ICU demand and deaths. |
What the modelling tells us about estimated infections and hospitalisations |
Estimate will be published fortnightly as part of the EMRG consensus |
| Local authority cases projections |
Gives projected number of cases in each local authority in two weeks' time. |
What we know about which local authorities are likely to experience high levels of Covid-19 in two weeks' time |
This will be archived. |
| Enduring Transmission (not published) |
Informs estimates of Health Board demand for Hospital and ICU beds Identifies areas (intermediate zones) of early increasing prevalence and/or slower decline in prevalence |
Not currently published |
This will be archived. |
| CANNA Model (not published) |
Estimates impact of Test and Protect policy |
Not currently published |
This will be archived |
| Kalman Filter (not published used as an internal check) |
R estimate as a comparison to other methods |
Not currently published |
This will be archived |
| Doubling time |
Estimates the time required for the relative abundance of the Omicron variant to double in the Scottish population |
What we know about the Omicron variant |
This will be archived |
| Exceedance |
Calculates whether the number of confirmed infections (based on testing) in each area exceeds the number that was expected when cases are below 50 per 100,000 |
What the modelling tells us about whether Covid-19 infections exceeded what would be expected at this stage in the epidemic |
This will be archived |
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