Coronadashboard data explained

Where do these figures come from?
RIVM delivers weekly data on the number of vaccine doses administered. This data is not currently available as an open data file.

The figures on coronadashboard.nl on the total vaccination coverage in the Netherlands (18 years and older / 12 years and older) come from a different source than the figures on the vaccination coverage per age group and the vaccination coverage per municipality.

The figures on the total vaccination coverage in the Netherlands are the figures that RIVM provides to the European Center for Disease Control (ECDC). These data are not yet available as an open data file.

The figures on vaccination coverage by age group are not yet available as an open data file.

The figures on vaccination coverage per municipality are available as an open data file.

How are these figures determined?

Vaccine doses administered
The number of doses administered is drawn from data that the municipal health services (GGDs) pass on to RIVM. RIVM records the number of doses administered by GGD vaccination centres, hospitals, healthcare institutions and general practitioners (GPs) in its central COVID Vaccination Information and Monitoring System (CIMS). However, the CIMS data is still incomplete, as GPs and institutions have not yet reported a small proportion of the doses that have been administered to RIVM.

Despite the incomplete data, we want to depict the number of vaccine doses administered and the number of people vaccinated as accurately as possible. To this end, the dashboard shows RIVM’s estimates of the number of vaccine doses administered in healthcare institutions and GP practices, and the number of people vaccinated. The estimates are based on the number of vaccine doses that have been delivered to the locations where injections are given.

The calculated number of doses administered in general practices is currently unchanged, as the RIVM is recalculating this number. Once the calculation is complete, the number of doses administered in general practices will be updated.

Vaccination coverage
So far, RIVM bases its figures on the total national vaccination coverage on the calculated number of doses administered. This is because the reported vaccinations in the registration system CIMS were not complete enough earlier. As the vaccination coverage is partly based on calculations, the actual coverage may be slightly different.

The figures for vaccination coverage by age group and vaccination coverage per municipality come from CIMS. RIVM registers in CIMS how many people have started and how many people have completed the primary course of vaccinations.

A primary course has started when someone has had the first corona vaccination. A primary course is completed when someone has had the last necessary dose. Depending on the type of vaccine, this may be immediately after the first dose (Janssen vaccine), after the second dose (other vaccines) or after a corona infection and one dose (other than Janssen). If someone has had the last necessary dose, this person is fully vaccinated. Persons with a immune disorder are being offered a third dose. For this group, the third dose is part of the primary course of vaccines. These people also receive a booster.

On the dashboard we show how many people have had one shot and how many people have had the primary course of vaccinations. Third shots are not included in the booster vaccination rate.

We also show what percentage of all adults (18+) have received a booster jab. The booster turnout for the group aged 12 and older is shown as of 24 March 2022. A very high booster turnout in young people aged 12 to 17 is not a government goal. Young people will be offered a booster jab but the decision to get one is theirs (and/or their parents or guardians).

From 22 March 2022, we also show the number of repeat corona jabs. Repeat jabs are offered to groups of people (over-60's, people with a severe immune disorder, people with Down syndrome and people in care homes).

If the vaccination coverage is very high or very low in a certain population group, this can be traced back to individuals. For reasons of privacy, the dashboard in those cases therefore shows 'more than 95%' or 'less than 5%' instead of an exact percentage.

Vaccination coverage by age group and per municipality and number of fully vaccinated people actually higher
The vaccination coverage by age group and per municipality is in reality higher than shown on the dashboard. The reason for this is that CIMS only lists the vaccinations given to people who have given permission to register their vaccination.

Waiting time after last vaccine dose
The dashboard counts someone as having had the primary course of corona jabs immediately after the last vaccine dose was administered. The dashboard therefore does not take into account the waiting time after the last dose. In the Netherlands, there is a waiting period of four weeks for the Janssen vaccine and a waiting period of two weeks for other vaccines. Only then does the vaccination provide sufficient protection against COVID-19 and does it count as a valid corona certificate.

Changes in the figures

New calculation method RIVM
As of 19 January 2021 RIVM publishes a weekly update on the vaccination figures of the Dutch population. These vaccination figures were previously based on the number of vaccinations that the Dutch Public Health Service (GGD) has registered in the CoronIT registration system. These CoronIT figures were supplemented by the number of vaccines that have been delivered to general practitioners, hospitals and institutions (i.e. other than the GGD).

Until 24 May 2022, the vaccination coverage based on these supplied vaccines had to be estimated up to a degree. That's because the registrations in CoronIT weren't fully complete. RIVM is now able to better calculate the vaccination data. This new method uses the national COVID vaccination Information and Monitoring System (CIMS) as a basis for the vaccination figures. RIVM supplements the registered vaccinations in CIMS with the GGD vaccination data. The figures coming from other parties than the GGD (like hospitals) are supplemented and calculated on the basis of the GGD data. In addition, we take into account that one vaccination after a corona infection also counts as having completed the primary series of corona jabs.

In addition, RIVM now uses more up-to-date population figures. Until 24 May 2022, RIVM worked with the population figures of 1 January 2020, this being consistent with how the European Centre for Disease Control (ECDC) uses population figures. The population figures are now updated quarterly by RIVM. Also, RIVM substracts vaccinated people who have died or emigrated. As a result, the vaccination rate of the Dutch population had to be slightly adjusted downward.

The main causes for the downward adjustment are that deceased and emigrated persons are no longer added to the figures, and that the population data are updated more frequently. The new calculation method, which no longer uses estimates based on vaccinations supplied to hospitals, institutions and general practitioners, contributes less to the downward adjustment.

RIVM's calculation method with regard to population figures has consequences for the graph 'Vaccinations over time'. This graph shows the number of vaccinations in the past. Because RIVM is adjusting the figures retroactively, as of 1 January 2020, the new RIVM vaccination figures deviate from the figures shown in the graph. Therefore, the chart is currently not being updated.

Correction number of fully vaccinated people
From November 11, 2021, people who have had corona and one vaccine dose count as having completed the primary course of corona jabs in the 'Vaccinated people' graph. Until this date, they counted among not having completed the primary course.

Vaccination coverage
People who have had one shot after having had corona will also count as having completed the primary course from 22 September 2021 in the figures per municipality and per age group. As a result, these numbers have increased. In addition, a number of Janssen vaccinations that had been counted too much were removed from the data on the same date. As a result, the vaccination rate per age group has decreased somewhat.

Improved data
The GGD has removed appointments that were cancelled or that did not result in vaccination from its data set. It has also corrected the data for people who received doses of two different vaccines. Around 160,000 doses have been removed from the data set. The improved data set includes the data up to and including 8 August 2021. The figures on the dashboard were updated on 10 August 2021.

Administred vaccine doses
From 11 November 2021, it will no longer be possible to estimate how many vaccines have been administered for a first or second vaccination for vaccinations administered by providers other than the GGD (for example, institutions or hospitals). The reason for this is that the estimate of the number of administered first and second shots is based on the number of vaccines applied. With the spread vaccines, no distinction is made between the vaccines for the first and second shots and the vaccines used for the booster shot. It is therefore assumed that no more first and second shots will be administered by other providers as of 11 November 2021.

Where do these figures come from?
Data on deliveries and doses in stock is provided by the National Institute for Public Health and the Environment (RIVM). This is not yet available as an open data file.

How are these figures determined?
Deliveries
The ‘Deliveries’ graph on the dashboard shows the number of doses that the Netherlands has received and expects to receive. RIVM assumes that each vaccine vial contains a specific number of doses – BioNTech/Pfizer: 6.9 doses per vial; Moderna: 10 doses per vial; AstraZeneca: 11 doses per vial; and Janssen: 5 doses per vial. This may differ from the manufacturer’s instructions for some vaccines.

These figures include the vaccine doses for the Dutch Caribbean and the vaccine doses that the Netherlands donates to other countries.

Doses in stock per type of vaccine
In the graph ‘Doses in stock per type of vaccine,’ the dashboard shows the total and available stock per type of vaccine at the central storage site. The total stock covers stock that is available and stock that is not yet available. The stock that is not yet available comprises vaccines that still have to be checked.

The size of the stock fluctuates: shortly after a new delivery, the total stock of a vaccine is relatively high; just before the next delivery is released from quality control, the available stock is low.

These figures include the vaccine doses for the Dutch Caribbean and the vaccine doses that the Netherlands donates to other countries.

Where do these figures come from?
Number of hospital admissions
The figures on number of hospital admissions are supplied by the National Institute for Public Health and the Environment (RIVM). This data is available in the form of an open data file.

Occupancy of regular hospital beds
Figures on occupancy of regular hospital beds, excluding ICU beds, are provided by the LCPS. This data is available in the form of an open data file. As of 1 July 2021, the LCPS bases the weekend figures on (historical) data known to the LCPS.

How are these figures determined?
Number of hospital admissions
RIVM uses data collected by Stichting NICE (the National Intensive Care Evaluation Registry). Stichting NICE registers the number of COVID-19 patients in the ICU and regular wards. The number of hospital admissions refers to patients admitted to regular wards as well as those admitted directly to the ICU.

The dashboard shows the average number of people with COVID-19 admitted daily to hospital, including the ICU. It is a seven-day rolling average. Because the data for the most recent days is incomplete, they are not used in calculating the seven-day rolling average. The graph ‘Hospital admissions over time’ shows the actual number of hospital admissions (including ICU admissions) by admission date, as well as the seven-day rolling average.

Residence of patients admitted to hospital
The map shows numbers per municipality/safety region based on date of admission. Although there are often reporting delays, they are offset by the admission numbers from previous days, which are included. Therefore the map still provides a good overall picture of daily hospital admissions.

Other data on hospital admissions
LCPS has also been collecting data on new hospital admissions since October 2020, but we only use the NICE data. This is because LCPS provides only aggregated figures, which give no information about patients’ age or sex, for example. This data is therefore too limited to be of use for the dashboard, and cannot be used by RIVM.

Occupancy of regular hospital beds
The LCPS registers the number of beds on regular hospital wards that are occupied by COVID-19 patients. Figures from before 1 June 2020 may be less reliable, as the LCPS was still in the process of setting up its registration system at that time.

Changes in the figures
Up to 16 December 2020 the dashboard used data from the OSIRIS database, which is provided primarily by the municipal health services (GGDs). However, OSIRIS suffers from significant underreporting of hospital admissions as the GGDs are no longer always informed when COVID-19 patients are admitted to hospital. The NICE data set is more complete, but its definition of ‘hospital admission’ is also broader. Whereas the OSIRIS data set includes only patients admitted to hospital due to COVID-19, the NICE data set also includes hospital patients who have COVID-19 but who were admitted for another reason.

Correction
Due to a correction in the registration system of the Albert Schweitzer Hospital (region Dordrecht), 355 hospital admissions spread over the period from January 1, 2021 to July 27, 2021 were incorrectly reported. The numbers are lower in reality. The numbers are retroactively updated on the dashboard on July 28, 2021.

Location of admitted patients
Untill 24 November 2021, the figures were based on the reporting date (hospital admissions reported to the NICE Foundation in one day). From 25 November 2021, the dashboard uses figures based on admission date (the date the patient was admitted to hospital)

Differences between the figures
There are differences between the LCPS and NICE registration systems. The LCPS system focuses on bed occupancy (capacity), the NICE system focuses on patients. An increase in occupancy does not fully reflect the number of new patients. When a patient is discharged from hospital, the bed does not immediately become available. It is also possible that one bed may have several occupants over the course of a day. Each of these data sets contains different information and is used for different purposes. These figures are therefore not directly interchangeable.

Where do these figures come from?
ICU admissions
The figures on new admissions to ICU are supplied by RIVM.This data is available in the form of an open data file.

ICU bed occupancy
The figures on ICU bed occupancy are supplied by the LCPS. This data is available in the form of an open data file. As of 1 July 2021, the LCPS bases the weekend figures on (historical) data known to the LCPS.

How are these figures determined?
ICU admissions
RIVM bases its calculations on information that is collected by Stichting NICE (the National Intensive Care Evaluation Registry). Stichting NICE registers the COVID-19 patients admitted to Intensive Care Units (ICU) and hospital wards. ICU admissions reported via RIVM also include any admissions of Dutch patients to ICUs in German hospitals, as the main purpose of this figure is to track the spread of COVID-19 and the effect on the course of the disease.

The dashboard shows the average number of people with COVID-19 admitted daily to the ICU. It is a seven-day rolling average. Because the data for the most recent days is incomplete, they are not used in calculating the seven-day rolling average. The graph ‘ICU admissions over time’ shows the actual number of ICU admissions by admission date, as well as the seven-day rolling average.

ICU bed occupancy
The LCPS data set includes both the number of ICU beds occupied by COVID-19 patients, and the number of ICU beds occupied by other patients. The percentage of ICU beds occupied by COVID-19 patients is calculated by dividing the number of ICU beds occupied by COVID-19 patients by the total number of occupied ICU beds. ICU bed occupancy does not include any Dutch patients in German ICUs, as the main purpose of this figure is to show the capacity of Dutch ICUs.

Figures from before 1 June 2020 may be less reliable as the LCPS was still in the process of setting up its registration system at that time.

Changes in the figures
Due to a correction in the registration system of the Albert Schweitzer Hospital (region Dordrecht), 30 ICU admissions spread over the period from January 1, 2021 to July 27, 2021 were incorrectly reported. The numbers are lower in reality. The numbers are retroactively updated on the dashboard on July 28, 2021.

Where do these figures come from?
The figures on the number of positive tests (confirmed cases) are supplied by the National Institute for Public Health and the Environment (RIVM). This data is available as open data.

How are these figures determined?
The figure shows the number of positive tests reported to RIVM in the preceding 24 hours, up to 10.00 on the day of publication of the figures. The date attributed to positive tests is the date on which RIVM was notified by the municipal health authority (GGD). This is not the same as the date on which people are tested.

Doctors and laboratories are required to report cases of infectious disease to the GGD. However, coronavirus tests are also carried out by commercial organisations and individuals. The results of these tests are not always reported to the GGD, or the notification is not counted as the test used does not meet RIVM standards. Commercial testing organisations are required to report positive test results to the GGD. This means that the daily number of confirmed cases reported on the dashboard may not give the complete picture. This should be kept in mind when interpreting these figures.

Part of the notification process is done manually. Sometimes the GGDs will not have reported all newly confirmed cases at the moment that RIVM compiles the figures for the preceding 24 hours. Missing notifications are passed on at a later time. Missing or delayed notifications can skew the daily figures. The rolling average filters out this type of fluctuation, and therefore often gives a better picture of the number of infections.

Changes in the figures
RIVM can also retrospectively correct data that has already been published. These corrections are processed in the open data file and incorporated into the dashboard. The data file registers cases at safety region and municipality level. In order to calculate data at national level we add all notified cases together. Some notified cases cannot be linked to a particular municipality/safety region, as this information is missing from the data file. These cases cannot therefore be shown at those levels, but they are included in the national figures.

Growth rate
The growth rate (or G rate) is a percentage that expresses the change in the number of positive tests in the last 7 days relative to the number of positive tests in the preceding 7 days. To calculate the growth rate, data must be available for 14 consecutive days (the previous 7 days + the 7 days preceding that).

The growth rate is calculated by the Ministry of Health, Welfare and Sport based on data from RIVM. All historical growth rates are recalculated daily, so that any corrections made by RIVM to the number of positive tests are incorporated into the historical trend of the growth rate. The growth rate is calculated in line with the method used by research institute IPSE Studies. The growth rate was introduced by the Dutch newspaper de Volkskrant.

Where do these figures come from?
The National Institute for Public Health and the Environment (RIVM) supplies open data on positive test results via GGD test locations.

How are the figures determined?
The percentage of tests that have a positive result is based on tests conducted by the GGD and for which the results are known. The seven-day rolling average is calculated with a two-day delay. This is because the results of tests conducted in the last 48 hours may not yet be available. This way we can be sure that most of the results are available and that the percentage of positive tests is accurately represented.

Changes in the figures
As of 1 July 2021 people who are planning to travel abroad can also be tested at GGD test centres. Before 10 August these people’s test results were included in the same data set as the results of people being tested by the GGD for other reasons. As of 10 August travellers’ test results are no longer included. Around 200,000 test results have been removed from the data set. The figures on the dashboard for the period between 1 July and 10 August have been adjusted accordingly. As a result, the percentage of positive test results in that period is higher than previously indicated. The increase is 2 to 3 percentage points, depending on the day.

On 7 September, 2021, we added an additional notification in the graph "Percentage of GGD positive test results, over time". The percentage of positive tests is no longer clear and unambiguous to interpret and compare over time. This is partly due to a recent increase in testing at walk-in test sites not requiring an appointment for students during introduction weeks, testing of returning travellers, and testing for confirmation after a positive self-test.

Where do these figures come from?
Twice a week (on Tuesdays and Fridays), the National Institute for Public Health and the Environment (RIVM) supplies open data on the reproduction number. The reproduction number (R) is not an exact value but a reliable calculation.

How are the figures determined?
RIVM uses the reported number of daily positive test results to calculate R. In most cases, the day on which symptoms first presented is known. In other cases, this date can be estimated. If someone has no symptoms, RIVM will use the date on which they would normally have experienced symptoms for the first time.

Depicting the number of coronavirus cases according to the first day of symptoms gives a clear picture of whether the number of transmissions is increasing, at its peak or decreasing. In order to calculate R, it is also necessary to know the length of time between the first day of symptoms of a new case and the first day of symptoms of the person who infected them. This has been calculated to be 4 days on average, based on coronavirus cases reported to the municipal health service (GGD). This information is then used to calculate the reproduction number.

How up to date are the figures?
The most up-to-date value of R provided on the coronavirus dashboard at any given time is always from at least two weeks ago. Calculations of R using data from less than 14 days ago could provide an indication of what the definitive value may be, but are not reliable predictors. The more recent the day, the less reliable the figure is since not all the data for that day is available yet.

Changes in the figures
Until 11 June 2020 R was calculated on the basis of COVID-19 hospital admissions as large-scale testing was not yet underway. Until 2 November 2020, the graph showing the progression of R over time did not give a value of R for the most recent two weeks but did give a projection of this value in the form of a bandwidth. As of 3 November, the dashboard graph no longer displays this bandwidth.

Where do these figures come from?
Number of COVID-19 deaths
The mortality figures are supplied by the National Institute for Public Health and the Environment (RIVM). This data is available in the form of an open data file.

How are these figures determined?
Number of COVID-19 deaths
This is the number of COVID-19 patients whose deaths have been reported to RIVM in the past 24 hours. The date shown is the date on which RIVM was notified by the municipal health authority (GGD). This may not be the same as the date on which deaths occurred. The actual number of deceased COVID-19 patients is higher than the number of deaths reported by RIVM because there is no requirement to report COVID-19-related deaths.

Where do these figures come from?
General data on mortality is provided by the national office Statistics Netherlands (CBS).

How are the figures determined?
Statistics Netherlands (CBS) weekly publishes the total number of deaths on Friday and compares this number with the expected number of deaths. Excess mortality occurs when more people die than expected. So expected mortality is the mortality you would expect if there had been no corona epidemic. This takes into account aging, migration, et cetera, and compares it with the seasonal pattern from the 2015-2019 period. The predicted number of deaths per week have been taken from the mortality projections made once every year by Statistics Netherlands.

The expected number of deaths has a bandwidth with an upper and lower limit (interval). Statistics Netherlands only speaks of excess mortality if the number of deaths is above the interval. Within the interval, it may be an ordinary fluctuation.

Changes in news item
As of 9 July, Statistics Netherlands (CBS) will no longer publish the news item about mortality on a weekly base. From that date, the news item will be published monthly. New figures will still appear weekly.

Diffent grouping Weesp
Weesp will merge with the municipality of Amsterdam, as a result of which Weesp will no longer fall under the Gooi en Vechtstreek safety region as of March 24, 2022, but under the Amsterdam-Amstelland safety region. As explained above, when determining the expected mortality for the coming year, mortality in recent years is considered. In order to be able to compare the actual mortality in both safety regions with the expected mortality, Weesp has already been assigned to the Amsterdam-Amstelland safety region on the dashboard from the beginning of 2022.

Where do the figures come from?
The figures on coronavirus variants are supplied by the National Institute for Public Health and the Environment (RIVM) as open data.

How are the figures determined?
The National Institute for Public Health and the Environment (RIVM) has been studying coronavirus variants in the Netherlands through pathogen surveillance since late 2020. Every week RIVM analyses about 1,500 random test samples containing coronavirus that it receives from various labs across the country.
On the basis of this analysis, RIVM can determine what percentage of infections each variant is responsible for and, from there, predict the speed at which the different variants are likely to spread. This enables RIVM to estimate what percentage of future infections will be caused by which variant. As new data arrives each week, it is checked against these predictions. This helps make future predictions more and more reliable. The figures shown on the Dashboard are not RIVM’s predictions, but rather the data from the pathogen surveillance. Preparing and analysing the samples and processing the data takes time. The figures for the most recent weeks are therefore incomplete and, because of this, we do not show them on the Dashboard. As a result, the percentage for a given variant as reported by RIVM often differs from what is shown on the Dashboard at that time. The media also tends to report RIVM’s predictions.

The data gathered from pathogen surveillance is updated every Friday. Figures may change from week to week compared to what was previously published, generally as a result of changes to the date a sample was collected or other changes related to the sample in the registration system. Data from the most recent weeks is incomplete and is updated in future publications as more information becomes available. In other words, the data on the dashboard is updated retroactively.

Variants on the dashboard
The table on the dashboard shows the variants of concern and the variants of interest. The European Centre for Disease Prevention and Control (ECDC) and the World Health Organization (WHO) consider a variant to be a variant of concern if it spreads more easily, makes people more sick or if vaccines are less effective against the variant. A variant of interest is a variant that has been traced to multiple infections in a particular setting or cluster, or that has been detected in multiple countries.

The graph on the dashboard only shows the ECDC variants of concern. These variants are monitored because of their potential risk. RIVM follows the ECDC and the WHO guidelines in this respect. The variants that are not shown separately in the graph are listed in the category 'other variants'.

Chart adjustments
As of 3 September 2021 the European Centre for Disease Prevention and Control (ECDC) and the World Health Organization (WHO) are no longer designating the Alpha variant as a ‘variant of concern’, but as a ‘variant of interest’. Since that date, the National Institute for Public Health and the Environment (RIVM) has included data on the Alpha variant in the data set as a ‘variant of interest’. On the graph ‘Coronavirus variants over time’, variants of interests are included in the group ‘other coronavirus variants’. The Alpha variant was therefore not shown separately on the graph between 3 September and 28 October 2021. However, because the Alpha variant was previously a ‘variant of concern’ and was the dominant variant for almost 6 months, an exemption has now been made for this variant. As of 28 October the Alpha variant is shown separately in the graph again.

Where do these figures come from?
RIVM provides these figures as open data.

How are the figures determined?
The GGD carries out contact tracing in relation to people who have tested positive for coronavirus. This includes looking at the setting in which someone may have become infected. RIVM has defined 21 possible settings. For the overview on the dashboard these 21 settings have been grouped into eight categories. The overview below shows the eight categories and the settings they cover.

1. At home and visiting

2. Work

3. School and childcare

4. Healthcare

5. Gatherings

6. Travel

7. Restaurant, café or bar

8. Other

If many people test positive in a safety region, this can put severe pressure on the contact tracing process. This may mean that the GGD cannot carry out regular contact tracing and that there is therefore insufficient data for that region. In this case there will be no information on the dashboard for that region for that particular period.

Changes to the data on contact tracing
As of 5 November, 2021, GGDs have adopted a new, tailored approach to contact tracing. With tailored contact tracing, sufficient information on possible transmission settings is more often available and can therefore be presented on the dashboard.

Like in the 'old' system, tailored contract tracing also has a customized phase model. This means that if there are many infections, the BCO moves to a different phase and is performed in a less extensive manner. With tailored contract tracing, the GGD works with the color codes green, orange and red. In phase green, BCO is executed in a normal manner. Orange means that BCO is carried out to a limited extent. In phase red, the person who has tested positive is only called with the result and no further data is available.

In contrast to the old system, if one of the 25 GGD-regions is in the green or orange phase, there is currently enough data available to display information about BCO on the dashboard.

Read the GGD press release on tailored contact tracing (in Dutch).

Where do these figures come from?
The figures on nursing home care are provided by the National Institute for Public Health and the Environment (RIVM). RIVM supplies the figures as an open data file.

How are these figures determined?
Residents testing positive
RIVM counts a person as a nursing home resident if, according to the OSIRIS central database, they are resident in a nursing home or a similar residential care centre for the elderly. When someone tests positive for coronavirus, the municipal health service (GGD) asks if that person is resident in a nursing home or residential care home for the elderly. If this information is unavailable, RIVM determines whether the person is a nursing home resident using the old definition (see below under ‘Changes in the figures’).

Infected locations
RIVM has determined the total number of nursing home locations per safety region using the list provided by Zorgkaart Nederland. RIVM counts nursing homes with the same postcode as one nursing home location. The same method is used to determine the number of infected locations. It is necessary to know the total number of nursing home locations per safety region in order to calculate the percentage of nursing home locations that are infected. To calculate the total number of nursing home locations nationwide, we add up the totals of all safety regions.

Deceased residents
We show the number of deaths among nursing home residents by the date of death. If we do not know the date of death, which is sometimes the case, we do not show the death on the dashboard.

National figures
Sometimes the data provided cannot be linked to a specific safety region. This means that the numbers at national level may sometimes be higher than the total of the numbers at safety region level.

Average over 7 days
The graph showing the number of confirmed cases among nursing home residents and the graph showing the number of residents who have died shows the average over 7 days.

Changes in the figures
The definition RIVM used up to the end of September 2020 to determine if someone who had tested positive was a nursing home resident (see below under ‘Old definition’) resulted in an incomplete number of infected nursing home locations. From 1 July 2020, the GGDs register whether a newly-infected person is a nursing home resident. RIVM has recalculated the figures on the dashboard from 1 July 2020 onwards using this data, which now gives a much better picture of the actual number of infected nursing homes and nursing home residents. For reports of confirmed cases amongst residents without a stated first day of illness, the RIVM determines a calculated first day of illness. This calculation method has been adjusted from 16 July 2021. The figures for the number of infected locations have been retroactively adjusted on the dashboard.

As of November 2021, due to the scaled-down contact tracing, it is not standard checked if people live in an institution. This leads to an incomplete number of positively tested nursing home residents and infected nursing home locations.

Old definition
According to the old definition, a person was considered a nursing home resident if they met one of the following conditions:

In addition, the person:

Where do these figures come from?
The figures on disability care are provided by the National Institute for Public Health and the Environment (RIVM). RIVM supplies the figures as an open data file.

How are these figures determined?
Confirmed cases among residents
From 1 July 2020, the GGDs registers whether a newly-infected person is resident in a disability care home. RIVM considers a person to be a disability care home resident if they are registered as such in the central OSIRIS database. If this is not known, RIVM counts the person as a disability care home resident if they are not a health worker and:

Locations
The word ‘locations’ refers to the 2,586 care homes in the Netherlands that are registered by Zorgkaart Nederland as providing residential care to people with disabilities. The total number of locations per safety region is provided by RIVM. Locations with the same postcode are counted as one location. The same method is used to determine the number of infected locations. It is necessary to know the total number of locations per safety region in order to calculate the percentage of locations that are infected. To calculate the total number of locations nationwide, we add up the totals of all safety regions.

Deceased residents
We show the number of deaths among disability care home residents by the date of death. If we do not know the date of death, which is sometimes the case, we do not show the death on the dashboard.

National figures
Sometimes the data provided cannot be linked to a specific safety region. This means that the numbers at national level may sometimes be higher than the total numbers at safety region level.

Average over 7 days
The graph showing the number of confirmed cases among residents and the graph showing the number of deaths among residents shows the average over 7 days.

Changes in the figures
For reports of confirmed cases amongst residents without a stated first day of illness, the RIVM determines a calculated first day of illness. This calculation method has been adjusted from 16 July 2021. The figures for the number of infected locations have been retroactively adjusted on the dashboard.

As of November 2021, due to the scaled-down contact tracing, it will not be standard practice to check whether people live in an institution. This leads to an underreporting of the number of positively tested residents of disability care homes.

Where do these figures come from?
The figures on people over 70 living at home are provided by the National Institute for Public Health and the Environment (RIVM). RIVM supplies the figures as an open data file.

How are these figures determined?
For its calculations RIVM uses the test results and mortality data that it receives from the municipal health service (GGD). When someone newly tests positive for coronavirus, the GGD records a number of details, including the person’s age and if they live in a nursing home or disability care home. RIVM calculates the number of new cases among over 70s living at home by first determining the total number of new cases in this age group and then subtracting the number of infections among:

We show the number of deaths among over 70s by the date of death. If we do not know the date of death, which is sometimes the case, we do not show the death on the dashboard.

Number of confirmed cases among the over 70s per 100,000
In order to compare groups of people with one another, we convert some figures to figures per 100,000 people. Likewise for the over 70s living at home. Statistics Netherlands collect data on the number of persons aged 70 and older who live at home (cbs.nl: 'StatLine - Huishoudens; personen naar geslacht, leeftijd en regio, 1 januari' in Dutch only). In the Netherlands, this group comprises around 2.3 million people.

National figures
Sometimes the data provided cannot be linked to a specific safety region. This means that the numbers at national level may sometimes be higher than the total of the numbers at safety region level.

Average over 7 days
The graph showing the number of confirmed cases among people over 70 living at home and the graph showing the number of deaths of people aged over 70 shows the average over 7 days.

Where do these figures come from?
The figures for wastewater testing are supplied by the National Institute for Public Health and the Environment (RIVM) as open data.

How are the figures determined?
Wastewater samples are collected at wastewater treatment plants across the country, so that data is available for all of the Netherlands. The samples of untreated wastewater are kept chilled during transport to RIVM. RIVM researchers analyse the samples and determine how many coronavirus particles each sample contains. Four times a week on average for each location, researchers test one sample of wastewater collected over a 24-hour period.

It takes several days before the outcome of an analysis is known. That is why the dashboard does not show measurements from the most recent days. The number of samples that can be analysed successfully differs from one week to the next. The open data file shows the date and location of successful measurements. If the number of virus particles in a sample is too low to be measured, the value is recorded as 0.

This monitoring method is still being developed.

Assisted by the water authorities, Statistics Netherlands (CBS) has calculated the number of inhabitants served by each wastewater treatment plant, so that RIVM can determine the number of virus particles per 100,000 inhabitants.

Changes in the figures
A measurement of 26 August 2021 from sampling location Dinther with a very high result, was published on the dashboard on 31 August 2021. This measurement also caused a large increase in the national figures. Because the value was so extreme and RIVM, after quality checks and research, has not found an explanation, RIVM has removed the measurement from the data on 1 September 2021. RIVM has conducted further research into other measurements from the same period. The results of samples taken on 25 August 2021 and on 30 August 2021 are available on the dashboard.

From 4 March 2021 the dashboard also shows wastewater monitoring results for municipalities that do not have their own wastewater treatment plant. This is possible by using the measurements from all wastewater treatment plants that serve a municipality. Other figures were adjusted at the same time. To find out how the figures are calculated, see ‘How are the figures determined?’.

In 2020 two sampling locations were ended. Sampling for their catchment areas was taken over by two other locations. In the week of 5 October, the location at Aalst was taken over by Zaltbommel, and in the week of 7 December, the location at Lienden was taken over by Tiel. So the figures calculated for the locations at Zaltbommel and Tiel before that time are based on a lower number of inhabitants. You can find these numbers, as well as those of Aalst and Lienden, in a table compiled in 2020 by Statistics Netherlands (CBS).

Sewage data Woerden
From February 3, 2022, the Coronadashboard will no longer show sewage water measurement for the municipality of Woerden. The Ministry of Health, Welfare and Sport and the National Institute for Public Health and the Environment (RIVM) have decided this because the measurements of the municipality of Woerden consistently showed extremely high values. This trend was not seen in other indicators, such as the number of positive tests. The RIVM has therefore conducted further research to determine the deviation. The sewer system has been examined at various locations in the municipality. No explanation has been found so far, but the investigation continues. It has become clear that the deviation cannot be explained by the number of infected people in the municipality.

Removal of four extremely high measurement results from the dataset.
The sewage measurements of sewage treatment plant Dokhaven of 21 February 2021, the plant at Veenendaal of 21 March 2021, a plant at Ameland of 22 July 2021 and a plant at Beilen of 8 November 2020 have been removed from the Corona dashboard on 3 February 2022.

The results of these measurements were very high and strongly deviated from regional and national trends in sewage research. Other indicators, such as the number of positive tests, also showed a different picture. In new measurements with new samples, the values appeared to fall within the limits of what is normally seen.

RIVM has therefore decided, together with the Ministry of Health, Welfare and Sport, to extract the measurements of the aforementioned data from the open data. The RIVM has established a protocol on how to deal with these kinds of high values from now on.

Where do these figures come from?
Once every three weeks the National Institute for Public Health and the Environment (RIVM) delivers the results of a behavioural survey. This data is available in the form of an open data file.

How are these figures determined?
Every three weeks the RIVM conducts a survey to determine the extent to which people comply with and support the coronavirus measures. Around 5,000 people aged 16 and over participate in this survey.

Changes in the figures
Since the 12th round of the survey, which was conducted from 11 to 17 May 2021, the RIVM has amended the questions about two rules.

Curfew
The curfew was lifted on 28 April 2021. Accordingly, RIVM no longer measures compliance with and support for this rule. On the dashboard we show the figures relating to the curfew up to 26 April.

Stay at home if you have symptoms
Up to and including the 11th round of the survey, RIVM may have incorrectly included some people in the group that ignored the basic rule of staying at home if they had symptoms. These were people who had symptoms suggestive of COVID-19 and who did leave their homes, but only after they had tested negative. In other cases, people may have had an urgent medical reason for leaving their homes without first testing negative. While these individuals may not have stayed at home, they did in fact correctly observe the rule. RIVM has therefore rephrased the question relating to this rule.

Because RIVM has rephrased the question, we only show the data based on the new question on the dashboard. The older data is still available in the RIVM’S open data file.

Work from home if possible
The rule ‘work from home if possible’ was not measured in the 14th round (29 June - 5 July 2021) and the 15th round of the survey (13-19 July 2021), because the measure was temporarily abolished. The rule has been measured again from 16th round of the survey (3-9 August 2021). As of round 19 (5-11 October 2021) the rule ‘work from home if possible’ has been changed to the urgent advice ‘work from home, and at the office when needed’. On the dashboard this has been shortened to: 'work at home if possible'.

Stay 1.5 metres from others
As of round 19 (5-11 October 2021) the physical distancing rule ‘stay 1.5 metres from others’ has been changed to the urgent advice ‘give others enough space’.

Avoid busy places
As of round 19 (5-11 October 2021), the coronavirus rule ‘avoid busy places’ is no longer included in the survey because it has been lifted.

Ensure a good flow of fresh air in house
As of round 19 (5-11 October) the new basic rule ‘ensure a good flow of fresh air in house’ has been added to the list of coronavirus rules in the survey.

Where do these figures come from?
The data for the CoronaMelder app come from the Ministry of Health, Welfare and Sport. This data is available as open data.

How are these figures determined?
Alerts for infection
The dashboard shows how many CoronaMelder users who tested positive alerted other app users that they may be infected. This figure, taken from the GGD portal, is based on the number of codes shared each day.

Number of downloads
We also show how many people have downloaded the CoronaMelder app. This figure is calculated by adding together the daily statistics for downloads via:

Where do the figures come from?
Confirmed cases
The National Institute for Public Health and the Environment (RIVM) supplies the figures as open data.

Hospital and ICU admissions
RIVM supplies these figures as open data. For each age group, the graph shows the total number of admissions per week (source NICE, processed by RIVM).

Deaths
The graph showing age distribution at national level is based on a RIVM open data file.

Age distribution of the Dutch population
Figures on the age distribution of the population come from open data from Statistics Netherlands (CBS).

How are these figures arrived at?
Confirmed cases
The figures in the graph showing positive tests per age group come from a different data source than the figures on confirmed cases. because there are no ages in the dataset on positive tests. Different dates are used in the two datasets.

The dates used in the age distribution data set are:

The data set uses the date reported by RIVM. This date is usually later than the actual date of the positive test result. This explains why there are differences between the graph that shows the total number of confirmed cases and the graph that shows positive cases per age group. The figures in the age distribution graph are seven-day rolling averages. In addition, sometimes the age of someone who tests positive is unknown.

The graph showing the age distribution of positive tests gives averages over the preceding 7 days. In order to be able to compare age groups, we calculate numbers per 100,000 people.

Hospital and ICU admissions
The data contains the weekly totals of the admissions that took place in that week per age group (source NICE Foundation, edited by RIVM). The graphs for hospital and ICU admissions show these weekly totals. To be able to compare age groups, we calculate numbers per 1,000,000 people from a specific age group. We determine the population size per age group on the basis of the CBS classification.

Deaths
Distribution according to age Everyone under the age of 50 is placed in the same age group, as the low numbers of deaths in this age group, in combination with the breakdown of COVID-19 deaths elsewhere on the dashboard, would otherwise enable tracing of the data to individuals.

Example
On 1 October 2020, the 7-day average of the number of positive tests in people aged 90 and older was 26.14. There are a total of 129,831 people aged 90 and older in the Netherlands. So the number of positive tests per 100,000 in the 90 and older age group is 100,000 / 129,831 * 26.14 = 20.13.

Calculating this for each age group and depicting the figures in one graph creates a clear picture of each age group, and allows us to compare the groups with one another.

The national average shown in the age graph is the average of all those cases whose age is known. For example, comparing the 90+ age group with the national average, the national average is made up of all age groups, including the 90+ group.

In the age distribution graph, the data from the last few days is not yet complete. RIVM supplements the data retrospectively and may also make corrections.

Where do the numbers come from?
The population numbers per municipality come from the national office Statistics Netherlands (CBS), reference date 1 January 2021.

• View the figures from Statistics Netherlands (CBS) on the population numbers

How are these figures arrived at?
To be able to compare municipalities, we convert some figures into figures per 100,000 people. We do this so we can compare larger municipalities and smaller municipalities. If we did not do that, municipalities such as Amsterdam and Rotterdam would always have high figures, because many more people live there compared to smaller municipalities.

Example:
In Katwijk, a total of 47 people had a positive test result on 3 May 2021.
According to figures from Statistics Netherlands, 65,995 people live in Katwijk.
The calculation we make is 47 / 65,995 * 100,000 ≈ 71.2.
On 3 May, 71.2 people per 100,000 people had a positive test result in Katwijk.

In Amsterdam, a total of 455 people had a positive test result on 3 May 2021.
According to figures from Statistics Netherlands, 873,338 people live in Amsterdam.
We make the same calculation: 455 / 873,338 * 100,000 = 52.1.
So, 52.1 people per 100,000 people in Amsterdam had a positive test result on 3 May.

Amsterdam has more inhabitants than Katwijk, but by converting to positive test results per 100,000 people, we can compare the two municipalities. On May 3, 2021, more people per 100,000 inhabitants had had a positive test result in Katwijk that day than in Amsterdam.

Because the number per 100,000 people is a calculation, it is possible the number has a decimal point.

Small differences compared to calculating yourself
At 'average number of positively tested people over the past 7 days' is a rounded number, based on this rounded number the average number of positive tests per 100,000 inhabitants is calculated. When instead of this rounded number, the open data is used to calculate the numbers per 100,000 inhabitants, small differences can arise.

Where do the numbers come from?
The population numbers per municipality come from the national office Statistics Netherlands (CBS), reference date 1 January 2021.

• View the figures from Statistics Netherlands (CBS) on the population numbers

How are these figures arrived at?
To find out what the situation is like in a safety region, we look at how many people from a safety region were admitted to hospital in the past 7 days per 1 million inhabitants. We do this so we can better compare large and small safety regions with one another. If we didn’t do this, densely populated safety regions such as the safety region Utrecht would have higher figures, because more people live there than in less densely populated safety regions.

Example:
In the safety region Groningen, a total of 38 people were hospitalized in the period from 3 to 9 May 2021.
According to figures from the CBS, there were 586,937 people living in the safety region Groningen on that date.
The calculation we then make is 38 / 586,937 * 1.000,000 ≈ 64.7.
So on from 3 to 9 May, a total of 64.7 people per 1.000,000 inhabitants were hospitalized in the safety region Groningen.

In the safety region Utrecht, a total of 71 people were hospitalized in the period from 3 to 9 May 2021.
According to figures from the CBS, there were 1.361,153 people living in the safety region Utrecht on that date.
The calculation we then make is 71 / 1.361,153 * 1.000,000 = 52.1.
So on from 3 to 9 May, a total of 52.1 people per 1.000,000 inhabitants were hospitalized in the safety region Utrecht.

More people live in the safety region Utrecht than in the safety region Groningen, but by calculating the hospitalizing’s per 1.000,000 people we are able to compare the two safety regions. From 3 to 9 May 2021 more people per 1.000.000 inhabitants in the safety Groningen were admitted to hospital than in the safety region Utrecht.

Because the number per 1.000,000 people is a calculated rate and therefore does not express an exact number of people, it can be rounded off to the nearest tenth (one decimal place).

On the dashboard we use ‘value of’ to indicate the date to which the figures refer, while ‘obtained on’ is used to refer to the date on which we received the data. This clearly shows how up-to-date the data is, in particular for indicators that look back over time.

An example of a subject where ‘obtained on’ tells us more about how current the data is than ‘value of’ is the reproduction number (R). RIVM publishes this number twice a week, but the R is always for a date two weeks in the past.

So, for example, this will appear on the dashboard: ‘Value for Thursday 13 May obtained on Friday 28 May’.

On 1 January 2021 a number of municipalities were merged, forming new municipalities. As of 7 January, RIVM has processed the data it provides for the Coronavirus Dashboard in accordance with these new municipal boundaries. We have modified the municipal and safety region maps on the dashboard to reflect the boundary changes. We have added the 2020 figures from municipalities that no longer exist to the figures of the municipalities that they have been merged with.

Changes in the figures
Some of the figures on the Dashboard are calculations per 100,000 or 1 million people. We present them in this way so it is possible to compare municipalities or safety regions with different populations. All 2020 figures are based on population data from the national office Statistics Netherlands (CBS), using 1 January 2020 as reference date.

The 2021 figures are based on population data from Statistics Netherlands using 1 January 2021 as reference date. Until 17 August 2021, however, the figures from 1 January to 17 August calculated per 100,000 or 1 million people had been based on CBS population data from 1 January 2020. As of 17 August all 2021 figures are now based on the new data from Statistics Netherlands using 1 January 2021 as reference date. The figures on the Dashboard from 1 January 2021 onwards were retroactively updated on 17 August. The corrected figures may be slightly higher or lower, depending on the population data of the municipality or safety region in question. Any differences are minor.

Where did these figures come from?
Until 9 July the National Institute for Public Health and the Environment (RIVM) supplied data on the number of infectious people twice a week. This data is available as open data.

How are the figures determined?
Someone who is infected with coronavirus can transmit the virus to other people. How long they are infectious for differs from one person to another. The precise number of infectious people is unknown, but RIVM calculates the range within which this number probably lies using data from the Pienter Corona study and the number of hospital admissions.

Changes in the figures
From 1 June 2020 until 12 October 2020 the number of infected people was estimated on the basis of data from the first round of the Pienter Corona study, the number of hospital admissions and the number of confirmed cases. As of 13 October 2020, this figure is estimated using data from the second round of the Pienter Corona study and the number of hospital admissions. In the second round of this study, a larger group of people was tested to find out if they were infected with coronavirus, and more insight was gained into the degree of people’s infectiousness.

From 9 July 2021, RIVM will no longer calculate the number of infectious people for the time being. This figure is based on the number of hospital admissions. More and more people have been vaccinated and fewer people are hospitalized as a result. The difference between the number of infections among people and the number of hospital admissions is increasing. Therefore, the number of infectious people is no longer calculated.

Where do these figures come from?
Until 1 Sepember 2021, the Netherlands Institute for Health Services Research (NIVEL) reported on thursday of each week, the figures from general practitioners on patients with COVID-19-like symptoms. This data is available in the form of an open data file.

How were these figures determined?
Once a week, a representative sample of around 350 GP practices across the Netherlands provided data concerning the symptoms of patients they have seen to NIVEL’s Primary Care Database. Using this data, NIVEL determined the number of patients who have reported COVID-19-like symptoms in the past week. NIVEL determined this on the basis of the diagnostic codes reported by GPs and any additional information provided that is suggestive of COVID-19. These diagnostic codes are:

In order to achieve greater accuracy, each week NIVEL also recalculated the data from the preceding weeks. It also included data that was only published at a later date.