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Coronavirus (COVID-19): modelling the epidemic (issue no.94)

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.

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 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 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 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 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 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 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 (20th March to 26th March 2022). Data to 7th March.

Probability of exceeding (cases per 100K)

Local Authority

50

100

100

500

1000

2500

3000

Aberdeen City

75-100%

75-100%

75-100%

75-100%

75-100%

75-100%

50-75%

Aberdeenshire

75-100%

75-100%

75-100%

75-100%

75-100%

50-75%

50-75%

Angus

75-100%

75-100%

75-100%

75-100%

75-100%

50-75%

50-75%

Argyll and Bute

75-100%

75-100%

75-100%

75-100%

75-100%

50-75%

25-50%

City of Edinburgh

75-100%

75-100%

75-100%

75-100%

75-100%

75-100%

50-75%

Clackmannanshire

75-100%

75-100%

75-100%

75-100%

75-100%

75-100%

50-75%

Dumfries & Galloway

75-100%

75-100%

75-100%

75-100%

75-100%

75-100%

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%

75-100%

75-100%

75-100%

50-75%

East Dunbartonshire

75-100%

75-100%

75-100%

75-100%

75-100%

50-75%

25-50%

East Lothian

75-100%

75-100%

75-100%

75-100%

75-100%

75-100%

50-75%

East Renfrewshire

75-100%

75-100%

75-100%

75-100%

75-100%

50-75%

25-50%

Falkirk

75-100%

75-100%

75-100%

75-100%

75-100%

75-100%

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%

75-100%

25-50%

Highland

75-100%

75-100%

75-100%

75-100%

75-100%

75-100%

50-75%

Inverclyde

75-100%

75-100%

75-100%

75-100%

75-100%

50-75%

25-50%

Midlothian

75-100%

75-100%

75-100%

75-100%

75-100%

75-100%

50-75%

Moray

75-100%

75-100%

75-100%

75-100%

75-100%

50-75%

50-75%

Na h-Eileanan Siar[6]

-

-

-

-

-

-

-

North Ayrshire

75-100%

75-100%

75-100%

75-100%

75-100%

75-100%

75-100%

North Lanarkshire

75-100%

75-100%

75-100%

75-100%

75-100%

75-100%

50-75%

Orkney Islands6

-

-

-

-

-

-

-

Perth and Kinross

75-100%

75-100%

75-100%

75-100%

75-100%

75-100%

50-75%

Renfrewshire

75-100%

75-100%

75-100%

75-100%

75-100%

75-100%

50-75%

Scottish Borders

75-100%

75-100%

75-100%

75-100%

75-100%

75-100%

50-75%

Shetland Islands6

-

-

-

-

-

-

-

South Ayrshire

75-100%

75-100%

75-100%

75-100%

75-100%

75-100%

50-75%

South Lanarkshire

75-100%

75-100%

75-100%

75-100%

75-100%

75-100%

50-75%

Stirling

75-100%

75-100%

75-100%

75-100%

75-100%

75-100%

50-75%

West Dunbartonshire

75-100%

75-100%

75-100%

75-100%

75-100%

75-100%

50-75%

West Lothian

75-100%

75-100%

75-100%

75-100%

75-100%

75-100%

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 ending 8th March and 15th 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[7].

Table 2. Average Covid-19 wastewater levels (Mgc/p/d) [8].

Local authority (LA)

w/e 8th March

w/e 15th March

Coverage

Aberdeen City

144

196

99%

Aberdeenshire

151

186

44%

Angus

134

190

68%

Argyll and Bute

73

96

23%

City of Edinburgh

140

220

98%

Clackmannanshire

122

182

92%

Dumfries & Galloway

149

180

33%

Dundee City

164

206

100%

East Ayrshire

130

145

72%

East Dunbartonshire

190

296

99%

East Lothian

133

238

74%

East Renfrewshire

96

147

89%

Falkirk

125

244

96%

Fife

95

198

84%

Glasgow City

117

225

75%

Highland

199

268

48%

Inverclyde

188

179

98%

Midlothian

149

220

88%

Moray

165

186

55%

Na h-Eileanan Siar

118

0%

North Ayrshire

115

177

92%

North Lanarkshire

116

267

91%

Orkney Islands

208

0%

Perth and Kinross

107

124

45%

Renfrewshire

120

156

97%

Scottish Borders

122

194

59%

Shetland Islands

6

0%

South Ayrshire

130

171

88%

South Lanarkshire

96

205

90%

Stirling

53

66

63%

West Dunbartonshire

139

171

98%

West Lothian

132

181

95%

Contact

Email: sgcentralanalysisdivision@gov.scot

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