COVID-19 in Iceland

A prediction model for the number of individuals diagnosed with COVID-19 and the corresponding burden on the health care system.

2020-05-04

Summary

This will be the last prediction for the current wave of the COVID-19 epidemic in Iceland. The research team will continue to monitor and evaluate whether it’s timely to resume predictions later on. It’s possible to monitor the development of new infections in Iceland, in addition to everywhere else, at the University of Iceland’s Health Sciences’ dashboard, available here.

To use the dashboard, you must first turn it on by pressing the “Birta (publish)” button. You can then add countries for comparison. For example:

You can view the total number of infections on two different scales; clean numbers (or what’s called a linear scale) or the logit of the numbers. The logit is useful for comparison of the growth rate. Fixed relative growth then follows a straight line.

The trend can be checked by date or number of days based on a given condition (such as the number of diagnosed infections exceeding one hundred).

Today, there are 66 active infections. On March 9, the number of active infections was similar (68). One week later, the number had tripled and it took six weeks of strict social distancing to curb the epidemic. So it’s vital to maintain the progress we’ve made, install the tracking app on phones and encourage others to do the same. Do not hesitate to get tested by your health care provider if the slightest suspicion of infection arises.

The main results of the prediction model, with data through 3rd of May, are as follows:

It is expected that throughout the epidemic, about 1800 individuals in Iceland will have been diagnosed with COVID-19, but the number could reach as high as 2100 individuals, according to the pessimistic forecast.

It is expected that the number of diagnosed individuals with an active disease peaks in the first week of April and will at that time probably be about 1300, but could be as many as 1600 individuals in the week after, according to the pessimistic forecast.

It is expected that while the epidemic is ongoing, about 120 individuals will need hospitalization but this number might reach 150 according to the pessimistic forecast.

The greatest burden on health care services due to hospital admissions will be around mid-April. At that time it is expected that around 60 individuals will be hospitalized but the pessimistic forecast predicts 90 individuals.

It is expected that during the epidemic, approximately 25 individuals will become seriously ill (i.e. hospitalized in intensive care units), but this number might turn out to be as high as 35, according to the pessimistic forecast.

The heaviest burden on intensive care units is likely to be in the second week of April, when 10 COVID-19 patients are anticipated to need intensive care at the same time, or even 18 according to the pessimistic forecast.

Age distribution changing towards more diagnosed infections among individuals over the age of sixty would significantly increase the burden on health care.



It is necessary to keep in mind that as Iceland‘s population is small (about 360.000) the number of confirmed cases can vary greatly from day to day, which will affect the results of the prediction model. The model will, though, become more stable as time passes.

Methods and premises of the prediction model

We used a logistic growth model with negative binomial distribution for the number of COVID-19 infections diagnosed daily in Iceland to predict the median (likeliest prediction) and 97.5% upper limit (pessimistic prediction) of the cumulative number of confirmed COVID-19 cases in Iceland and active diagnosed cases (assuming 21 days of illness) in the upcoming weeks.

The epidemic prediction model assumes exponential growth of diagnosed infections to slow down at a certain point, as the epidemic reaches its peak and the number of new infections starts to decline and the number of active infections subsequently starts to decline.

The calculation method used to assess the shape of the growth curve in Iceland takes into account information on COVID-19 epidemic processes in other countries (see annex) to estimate the possible shape of the process in Iceland. Countries that have progressed further in the epidemic, e.g. South Korea, weigh more than the ones not as far into it.

Since all infected individuals in Iceland are clients of the Icelandic health care system, the forecast is based on the total number of infected individuals in Iceland, regardless of the source of infection, whether individuals are diagnosed in quarantine or not, whether they are diagnosed through the screening through the healthcare services or deCODE genetics. It should be kept in mind that infected individuals in quarantine may possibly add less to the exponential growth than other individuals.

We used the age distribution of already confirmed COVID-19 cases in Iceland to estimate the distribution of future cases into age groups. We then used data from Ferguson and colleagues at Imperial College (Table 1) (https://www.imperial.ac.uk/media/imperial-college/medicine/sph/ide/gida-fellowships/Imperial-College-COVID19-NPI-modelling-16-03-2020.pdf?fbclid=IwAR17JB7RqzU491sxa8eV1gqHFv-GTl2vh06sOUGaqaQ9RJ5vjWO_jNZbWjo) on age-related proportions of hospital admissions in our prediction of the number of patients in Iceland who might be admitted to hospital and/or intensive care.

There are various reasons why such age-related risks should be different in Iceland than in Hubei. For example, this implicit assumption is that the distribution of risk factors for the serious consequences of the disease is similar. In addition, it is assumed that decisions about when it is time to admit people into hospital or intensive care will be the same. Discrepancies between predictions and the number of intensive care units could indicate that the epidemic response is different here than in Hubei. However, this assumption is necessary at the beginning of the epidemic while there is insufficient data on hospital and intensive care in this country.



It should be kept in mind that the age distribution of infected individuals in Iceland is favorable so far. If the number of infections among the elderly increases, it will significantly impact the prediction model towards an increased burden on the health care system.

All code can be found here: website In addition, techincal report on methods behind the development of the prediction model can be found here. Finally, a dashboard measuring the development of COVID-19 in Iceland and elsewhere can be found here.

Results

Diagnosed COVID-19 cases

Cumulative confirmed infections in total

Active diagnosed infections each day

New diagnosed infections each day

Hospitalization

Cumulative hospitalizations

Cumulative total of hospitalizations

Active hospitalizations each day

Intensive care

Cumulative intensive care admissions

Cumulative total of individuals in intensive care

Number of individuals in intensive care each day

Distribution by age

Diagnosed infections

Cumulative

Cumulative diagnosed infections by age

Active

Active infections by age

Hospitalizations

Cumulative

Cumulative total of hospital admissions by age

Active

Active hospital admissions by age



Intensive care

Cumulative

Cumulative total of individuals in intensive care units by age

Active

Total of individuals with active infections by age

Results with a different age distribution

Different age distribution

The following is a simulation of development based on the fact that transmission is proportionally more prevalent in older age groups than it currently does:

Hospitalizations

Cumulative

Active

Intensive care

Cumulative

Active each day

Distribution by age

Diagnosed infections

Cumulative

Active

Hospitalizations

Cumulative

Active

Intensive care

Cumulative

Active

Annex

Information on data for prediction model:

Rate Country First inspection Number of days Beginning Now Albania 2020-04-04 31 0.1055220 0.2759538 Armenia 2020-03-27 39 0.1112339 0.8066995 Australia 2020-03-26 40 0.1110573 0.2698467 Austria 2020-03-17 49 0.1134549 1.7416887 Azerbaijan 2020-04-12 23 0.1052975 0.1922825 Bahamas 2020-04-09 26 0.1027005 0.2131036 Bahrain 2020-03-14 52 0.1279573 2.0613318 Barbados 2020-03-30 36 0.1149726 0.2856894 Belarus 2020-04-09 26 0.1127755 1.7672740 Belgium 2020-03-18 48 0.1077186 4.3248619 Bosnia And Herzegovina 2020-03-31 35 0.1069373 0.5625568 Brazil 2020-04-13 22 0.1050417 0.4792572 Bulgaria 2020-04-15 20 0.1018554 0.2311389 Canada 2020-03-27 39 0.1074014 1.5897443 Cape Verde 2020-04-16 19 0.1000118 0.3000355 Chile 2020-03-29 37 0.1007280 1.0375137 Colombia 2020-04-26 9 0.1021465 0.1523259 Costa Rica 2020-04-10 25 0.1067842 0.1464073 Croatia 2020-03-26 40 0.1012032 0.5074687 Cuba 2020-04-22 13 0.1003222 0.1454981 Cyprus 2020-03-25 41 0.1051247 0.7392643 Denmark 2020-03-13 53 0.1171196 1.6498968 Djibouti 2020-04-08 27 0.1242861 1.1421998 Dominican Republic 2020-04-01 34 0.1032689 0.7406678 Ecuador 2020-03-29 37 0.1056196 1.7001597 Equatorial Guinea 2020-04-25 10 0.1563438 0.2323033 Estonia 2020-03-16 50 0.1289935 1.2823917 Finland 2020-03-23 43 0.1131566 0.9497201 France 2020-03-17 49 0.1018429 2.0157769 French Polynesia 2020-03-27 39 0.1074164 0.2076717 Georgia 2020-04-21 14 0.1005813 0.1473692 Germany 2020-03-20 46 0.1692828 1.9537928 Greece 2020-03-29 37 0.1013037 0.2507291 Hungary 2020-04-09 26 0.1011908 0.3133816 Iceland 2020-03-05 60 0.1091346 5.3062994 Iran 2020-03-12 54 0.1085463 1.1750019 Ireland 2020-03-20 46 0.1140810 4.4047152 Israel 2020-03-22 44 0.1036461 1.9024865 Italy 2020-03-09 57 0.1218000 3.4800452 Jamaica 2020-04-26 9 0.1034502 0.1590759 Japan 2020-04-25 10 0.1016236 0.1186896 Kazakhstan 2020-04-21 14 0.1050593 0.2136763 Kuwait 2020-04-05 30 0.1138556 1.1844311 Kyrgyzstan 2020-04-24 11 0.1022468 0.1293671 Latvia 2020-03-25 41 0.1033175 0.4609955 Lebanon 2020-04-24 11 0.1003543 0.1075016 Lithuania 2020-03-27 38 0.1083480 0.5250710 Luxembourg 2020-03-16 50 0.1250550 6.2105244 Malaysia 2020-04-04 31 0.1043200 0.1971219 Maldives 2020-04-21 14 0.1299550 0.9925549 Malta 2020-03-19 47 0.1089988 1.0831751 Mauritius 2020-03-31 35 0.1067935 0.2786642 Mexico 2020-04-25 10 0.1008971 0.1839773 Moldova 2020-04-02 33 0.1046185 1.0192263 Montenegro 2020-03-27 39 0.1066901 0.5127495 Morocco 2020-04-25 10 0.1030386 0.1344327 Netherlands 2020-03-19 47 0.1199617 2.3729714 New Zealand 2020-03-30 36 0.1154072 0.2377138 North Macedonia 2020-03-28 38 0.1051137 0.7252363 Norway 2020-03-13 53 0.1154520 1.4517954 Oman 2020-04-12 23 0.1097491 0.5161824 Panama 2020-03-25 41 0.1043227 1.6948318 Peru 2020-04-09 26 0.1335570 1.4127149 Poland 2020-04-06 29 0.1082671 0.3614095 Portugal 2020-03-22 43 0.1251688 2.4790276 Puerto Rico 2020-04-03 32 0.1077245 0.6163479 Qatar 2020-03-14 52 0.1129917 5.4910424 Romania 2020-03-31 35 0.1008027 0.6797470 Russia 2020-04-13 22 0.1081083 0.9233216 Saudi Arabia 2020-04-11 24 0.1065409 0.7882159 Serbia 2020-04-01 34 0.1025964 1.0788585 Singapore 2020-03-27 39 0.1023373 3.1364478 Slovakia 2020-04-08 27 0.1064685 0.2580166 Slovenia 2020-03-16 50 0.1053566 0.6922749 Spain 2020-03-15 49 0.1230936 4.6529953 Sweden 2020-03-16 50 0.1028259 2.2236107 Switzerland 2020-03-14 52 0.1304798 3.4711597 Turkey 2020-03-30 36 0.1104764 1.5107945 Ukraine 2020-04-17 18 0.1014238 0.2707892 United Arab Emirates 2020-04-03 32 0.1048050 1.4495633 United Kingdom 2020-03-25 41 0.1196058 2.7631945 United States 2020-03-23 43 0.1069880 3.5191871 Uruguay 2020-04-03 32 0.1037053 0.1892115

The head of the prediction model on behalf of University of Iceland’s Health Sciences Institute is Dr. Thor Aspelund. The prediction model is conducted by scientists from the University of Iceland, the Directorate of Health, and the National Hospital. Contact us: covid@hi.is