Covid-19 – fast indicators
New data sources and methods can provide more timely indicators for economic and social trends during COVID-19 than Statistics Denmark’s usual publications, which comply with established international guidelines and are subject to a more exhaustive quality assurance.
We call this type of statistics experimental statistics, because sources, methods and documentation may deviate from the standard and develop along the way.
COVID-19 has created a substantial demand for timely data to reflect its impact on society. Experimental statistics are not part of the official production of statistics but can be very valuable, when you want a timely, innovative and reliable trend of development. We also focus on the effect of COVID-19 in a number of Statistics Denmark’s regular publications, which are part of the official production of statistics.
This page provides an overview of Statistics Denmark’s current experimental statistics. Nationalbanken (the central bank of Denmark) and other partners cooperate closely with Statistics Denmark to find new statistical data that helps reflect the situation with COVID-19. From each set of statistics, you can access information about uncertainties that you should pay attention to if you want to use it for information on social conditions.
The experimental statistics include data and processes, which to a certain extent are based on manual work routines at Statistics Denmark and our data suppliers. There may therefore be deviations from the planned publication times, eg in connection with holidays and illness and the like.
Statistical subjects
Here you can find links to the experimental statistics we have published. The statistics are in Danish. If you need further information, please contact the contact person indicated for each set of statistics.
Deaths ->
- Death toll per day
- Death toll per day - age groups
Community transmission ->
- Cases of COVID-19, tests and recovered from infection
- Number of persons testet for COVID-19 in 2020
- Deaths with COVID-19 infection
- Deaths with COVID-19 infection per day
- Development in number of persons hospitalised in connection with COVID-19
- Number of persons partly and fully vaccinated
- Cases of COVID-19 in proportion to number of persons in the age group
- Cases of COVID-19 in proportion to number of persons in the municipality
- New possible outbreaks of COVID-19 in primary schools
Business ->
- The effect of COVID-19 on industries
- Electricity consumption of the business sector
- Bankruptcies
- Start-ups
- Wage compensation by industry
- Compensation - self-employment by industry
Consumer spending ->
- Electricity consumption of households
- COVID-19 consumption indicator: Total consumption
- COVID-19 consumption indicator: Consumer spending in supermarkets
- COVID-19 consumption indicator: Consumer spending in restaurants
- COVID-19 consumption indicator: Consumer spending, hairdressers and beauty salons
Labour market ->
- Number of registered unemployed persons
- Weekly number of new unemployed persons registered
- Daily number of new unemployed persons registered
- Number of persons affected by notices of large-scale redundancies
- Unemployed persons and new vacancy advertisements at Jobnet
Transport ->
- Daily road traffic throughout the country
- Private vehicle traffic across the Great Belt Bridge
- Lorry traffic across the Great Belt Bridge
- Index for metro passengers
- Departures as of date from Copenhagen Airport (commercial passenger aircraft)
- Number of cargo and container ships in port per day
- Port calls in the statistics of harbours
External trade ->
- Indicator of trade in goods with non-EU countries
What are experimental statistics?
Experimental statistics are statistics that are in development, so that methods and sources may change in the process towards the final form of the statistics based on experiences, e.g. in the form of feedback from users.
In what ways do they differ from Statistics Denmark’s usual statistics?
In general, any statistics published by Statistics Denmark are official statistics. However, experimental statistics are not regarded as official statistics until they have been thoroughly tested to the point where they obtain a permanent form and a new status as official statistics.
It appears from the individual sets of statistics whether they have experimental status. The statistical documentation explains specifically what the experimental status of the individual set of statistics involves. It could be e.g. that the methods are not quite thoroughly tested, that new data sources are being tested, or that in its preliminary form, it only covers part of the intended area.
Which experimental statistics does Statistics Denmark publish?
Experimental statistics are gradually being developed to meet the demand of users. This page presents an overview of these, but in general, the individual sets of statistics can be found under the relevant subject pages or subjects in Statbank Denmark.
Is the uncertainty higher, and should you take special precautions when using it?
Limitations and reservations vary between the different sets of statistics and appear from the statistical documentation for each set of statistics.
Why does Statistics Denmark publish experimental statistics?
The purpose of experimental statistics is to respond to user requests for timely indicators of the development of society. Using more and more new sources and methods, we can create timely statistics in areas where the official and quality-checked statistics often have a time lag of months or perhaps years. Publishing the statistics in a preliminary form allows us to get feedback from the users, before we have found the final form, and thus gives us a more relevant product. At the same time, it gives the users an opportunity to become familiar with the statistics.
For instance, the experimental statistics could be a key indicator of a phenomenon that we describe through official statistics (e.g. the consumption of electricity in manufacturing as an indicator for production). In other contexts, indicators can be official statistics, e.g. Consumer expectations.
