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.

2020-04-02

Summary

The prediction of the total number of diagnosed infections has risen since March 30th, and forecasts of the burden on the health care system have likewise been affected. To be prepared for the possibility of further changes in the age distribution, another prediction follows which assumes that the age distribution will be more unfavorable. The results can be read further down in the report.

The main results of the prediction model, with data through 1st of April, 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 2500 individuals, according to the pessimistic forecast.
  • It is expected that the number of diagnosed individuals with an active disease will peak in the first week of April and will at that time probably be about 1200, but could be as many as 1700 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 180 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 26 individuals will become seriously ill (i.e. hospitalized in intensive care units), but this number might turn out to be as high as 40, 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.

 

The analytical work continues and the prediction model will be updated regularly with new data. 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 Poisson distribution of the number of already diagnosed COVID-19 infections 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 some point stop, as the epidemic reaches its peak 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.
    • 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 diagnosed infections

Cumulative confirmed infections in total

Active diagnosed infections each day

Hospitalization

Cumulative hospitalizations

Cumulative total of hospitalizations

Hospitalizations each day

Number of individuals in hospitals in total

Intensive care

Cumulative intensive care admissions

Cumulative total of individuals in intensive care

Number of individuals in intensive care each day

Total number of individuals in intensive care

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:
                                                                                                               Tíðni

Land Fyrsta athugun Fjöldi daga Upphaf
Armenia 2020-03-27 7 0.1112339 0.1930534
Aruba 2020-03-24 9 0.1128732 0.5173354
Australia 2020-03-26 8 0.1110573 0.1974353
Austria 2020-03-17 17 0.1134549 1.1960779
Bahrain 2020-03-14 20 0.1279573 0.3467035
Belgium 2020-03-18 16 0.1077186 1.2101225
Canada 2020-03-27 7 0.1074014 0.2564750
Chile 2020-03-29 5 0.1007280 0.1599300
Croatia 2020-03-26 8 0.1012032 0.2331548
Cyprus 2020-03-25 9 0.1051247 0.2712897
Czech Republic 2020-03-23 11 0.1089884 0.3357592
Denmark 2020-03-13 21 0.1171196 0.5382999
Ecuador 2020-03-29 5 0.1056196 0.1587460
Estonia 2020-03-16 18 0.1289935 0.5876371
Finland 2020-03-23 11 0.1131566 0.2613809
France 2020-03-17 17 0.1018429 0.8750075
French Polynesia 2020-03-27 7 0.1074164 0.1324802
Germany 2020-03-20 14 0.1692828 0.8803233
Greece 2020-03-29 5 0.1013037 0.1312843
Guam 2020-03-23 11 0.1613925 0.4602676
Iceland 2020-03-05 28 0.1091346 3.8904997
Iran 2020-03-12 22 0.1085463 0.5740050
Ireland 2020-03-20 14 0.1140810 0.7059915
Israel 2020-03-22 12 0.1036461 0.6562686
Italy 2020-03-09 25 0.1218000 1.8261579
Latvia 2020-03-25 9 0.1033175 0.2339067
Lithuania 2020-03-27 7 0.1083480 0.2105357
Luxembourg 2020-03-16 18 0.1250550 3.7662673
Montenegro 2020-03-27 7 0.1066901 0.1958639
Netherlands 2020-03-19 15 0.1199617 0.7962740
North Macedonia 2020-03-28 6 0.1051137 0.1699098
Norway 2020-03-13 21 0.1154520 0.8672846
Panama 2020-03-25 9 0.1043227 0.3101422
Portugal 2020-03-22 12 0.1251688 0.8068501
Qatar 2020-03-14 20 0.1129917 0.2948377
Singapore 2020-03-27 7 0.1023373 0.1722850
Slovenia 2020-03-16 18 0.1053566 0.4045887
South Korea 2020-03-04 30 0.1040111 0.1947475
Spain 2020-03-15 19 0.1230936 2.1853454
Sweden 2020-03-16 18 0.1028259 0.4929069
Switzerland 2020-03-14 20 0.1304798 1.9868787
United Kingdom 2020-03-25 9 0.1196058 0.4364568
United States 2020-03-23 11 0.1069880 0.6585965

 

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