Figures about new intensive care admissions are made available as open data by Stichting NICE (the National Intensive Care Evaluation Registry). The description of this dataset can be found here. Using the data, we calculate the average admissions over the past three days. Thus, this does not include the number for the current day. The average is obtained by adding up each day’s values (the figures for one day, two days and three days ago), dividing the total by three and rounding off the result to one decimal place.

ICU occupancy rates are obtained daily via open data provided by the LCPS. The description of this dataset can be found here. The data includes the number of ICU beds occupied by COVID-19 patients and the number of ICU beds occupied by all 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. The total ICU occupancy numbers are not available prior to the 1st of June because certain quality checks have not been performed before this date. Therefore that data might be flawed and is not published by LCPS.

Every day RIVM makes open data available on new hospital admissions, not including ICU admissions. The description of this data set can be found here. RIVM uses data collected by Stichting NICE (the National Intensive Care Evaluation Registry), an organisation, established by the professional association of ICU doctors, which registers available data from ICUs nationwide.

The admissions are not necessarily reported on the day of admission. The dashboard shows the number of admissions reported in one day. This figure is deemed to provide a good reflection of the current developments, as recordings of one day of admissions are illustrated.

The dashboard previously used data from the Osiris database, which is provided primarily by the municipal health services (GGDs). However it has come to light that hospital admissions tend to be significantly underreported in the Osiris database because GGDs are not always informed when COVID 19 patients are admitted to hospital. The NICE data is more complete, but its definition of ‘hospital admission’ is also broader. Whereas the Osiris database includes only patients admitted to hospital due to COVID 19, the NICE database also includes hospital patients who have COVID 19 but who were admitted for another reason.

There are currently three hospitals who do not share their data on COVID 19 hospital admissions with Stichting NICE: Tergooi hospitals, Hospital Amstelland and Flevoziekenhuis. COVID 19 hospital admissions these two hospitals are therefore not included in the daily hospital admission figures published on the dashboard. On a national level this has little impact on the numbers, on the regional level the impact on the number is significant.

Non ICU hospital occupancy rates are made available as open data by LCPS (the national coordination centre for patient distribution). The description of this data set can be found here. Occupancy rates from before 1 June 2020 are not available because certain quality checks were not performed before this date. As a result, the data could be flawed and LCPS therefore does not include it in the open data.

LCPS has also been collecting data on new hospital admissions since October 2020. Despite this, the dashboard uses the data from NICE, and not from LCPS. This is because LCPS provides only aggregated figures. The data is not disaggregated by patients’ age or sex, for example. It is therefore too limited to be of use for the dashboard, and cannot be used by RIVM.

Differences in the two registration systems are a result of what exactly they register, i.e. occupancy (capacity) versus patient counts. An increase in occupancy does not fully reflect changes in patient counts. When a patient is discharged from hospital, their bed does not become available immediately, for example. It’s also possible that a single bed may have several occupants over the course of a day. The data sets contain different information and are used for distinct purposes. These figures are not interchangeable as such.

The number of positive tests (confirmed cases) is supplied daily via open data by the National Institute for Public Health and the Environment (RIVM). The description of this dataset can be found here. The figures show the daily positive tests reported to RIVM in the preceding 24 hours, up to 10:00 on the day of publication. The date attributed to positive tests is the date on which RIVM was notified. This is not the same as the day on which people were tested.

Doctors and laboratories in the Netherlands are required by law to report cases of certain infectious diseases to the municipal health service (GGD). However, coronavirus tests are increasingly being carried out by commercial organisations and individuals, and the results are not always reported to the GGD. Moreover, tests that do not meet the standards of the National Diagnostic Chain Coordination Team (LCDK) or RIVM are not counted (https://www.rijksoverheid.nl/onderwerpen/coronavirus-covid-19/testen/soorten-testen/ontwikkeling-van-sneltesten-op-corona). In other words, the figure for daily positive tests published on the dashboard may not be 100% accurate. This must be kept in mind when interpreting the figures.

Test results are transferred from laboratories to the GDD and RIVM using different IT systems and is partly done manually, which delays the process somewhat. The GGD needs to question infected persons or their relatives to collect important data, so there is a time lag between a test result becoming known and RIVM being notified. A rise in the number of infected persons or a technical malfunction can lead to notification backlogs. So the data provided for the previous 24-hour period does not include all newly confirmed cases at the moment that RIVM accesses the data file. However, the data is always corrected with any late notifications that come in. Delays in reporting can skew the daily figures for positive tests. The moving average filters out daily fluctuations and thus provides a better picture of the trend in the number of infections.

Sometimes RIVM has to correct data that has already been published. These are not content-related corrections, but concern minor procedural errors, such as a typo in a GGD questionnaire, or the wrong selection of an answer category. These corrections are also processed in the open data file and incorporated in the dashboard.

Based on the absolute numbers, we calculate the relative number of positive people in proportion to the number of inhabitants. We do this by dividing the number of positive people by the number of inhabitants of the Netherlands. We present this as the number of positively tested persons per 100,000 inhabitants. The number of inhabitants nationally, per safety region and per municipality is based on this CBS classification.

The age distribution is determined on the basis of another open data file from the RIVM. This is because no ages are registered in the municipal file. Small differences may therefore arise between the table as shown in the 'weekly update of the epidemiological situation of COVID-19 in the Netherlands' on the RIVM website and as shown on the dashboard. The age distribution shown in the number of positively tested persons only concerns the cases reported since the penultimate update of the dashboard. The population size per age group is determined on the basis of this CBS classification.

A system of alert values has been set up. They signal when a situation has become alarming and needs urgent attention. The alert value for the number of confirmed cases a day is 7 per 100,000 inhabitants. This is the stage at which the number of infections is increasing too fast to keep the virus under control. The same alert value is also used in Germany.

The percentage of positive tests is based solely on tests carried out by the GGD for which the result is known. This is because the GGD is the only organisation that reports negative test results as well as positive ones. Negative results of any tests not carried out by the GGD are not reported to the GGD or to RIVM. RIVM provides the Ministry of Health, Welfare and Sport with daily data relating to the GGD test centres (for example number of people tested and average processing time).

The reproduction number (R) shows the number of people who are infected, on average, by one person with COVID-19. These figures are supplied weekly (on Tuesdays) as open data by the National Institute for Public Health and the Environment (RIVM). The description of this data set can be found here. The reproduction number (R) is not an exact value but a reliable estimate.

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, an estimate can be made of this date. Depicting the number of COVID-19 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 estimate R, it is also necessary to know the length of time between the first day of symptoms of a new COVID-19 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 COVID-19 cases reported to the municipal health service (GGD). This information is then used to calculate the reproduction number.

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. Estimates 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. Estimates using more recent data are less reliable because the data is not yet complete. It is, for instance, impossible to know how many newly confirmed cases will result in hospital admissions in the days ahead.

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.

The National Institute for Public Health and the Environment (RIVM) provides the Ministry of Health, Welfare and Sport with information about the COVID-19 situation in nursing homes on a daily basis via open data. The description of this dataset can be found here. This data cannot always be clearly linked to a specific safety region. As a result, the total sum of numbers at the safety-region level may be less than the numbers at the national level. The number of deaths of nursing home residents is based on the date of death. However, when the date of death is unknown that death is not included in this statistic in the dashboard.

The method used to estimate the numbers of nursing homes and nursing home residents infected with coronavirus has been improved. Since 1 July 2020, for every person newly infected with coronavirus, the municipal health services (GGDs) have noted whether that person lives in a nursing home. Until the end of September 2020, no use was made of this data and a different method was used to calculate infection numbers, which led to a significant overestimate of the number of infected nursing homes. As of 29 September 2020, the estimates on the dashboard from 1 July 2020 onwards have been recalculated using the this data and therefore now give a much better picture of the actual number of infected nursing homes and nursing home residents.

Old definition of a nursing home resident: A person was counted as a nursing home resident if, according to the central database OSIRIS: on the basis of their postcode, they can be linked to a registered nursing home or residential care home for the elderly, a setting (place where infection may have occurred) labelled as a ‘nursing home’ or something similar, or if there is any other term that links them in the database to a nursing home or residential care home for the elderly. In addition, the person:

• must be over 70 years old
• must not be a health worker, and
• must not be employed.

New definition of a nursing home resident: As of 1 July 2020, every time a person tests positive for COVID-19, the GGD asks whether that person is a resident of a nursing home or residential care home for the elderly. This information is used in the new definition. A person is considered to be a nursing home resident if, according to the data in OSIRIS:

• This person is a resident of a nursing home or a residential care home for the elderly.
• If it is not known whether the person lives in a nursing home or residential care home for the elderly, the old definition is used.

The total number of nursing homes per safety region is provided by RIVM. Any nursing homes with the same postcode are counted as one nursing home. This is because the number of infected nursing homes is also determined by postcode. It is necessary to know the total number of nursing homes per safety region in order to calculate what percentage of nursing homes in the safety region is infected. The total number of nursing homes nationwide is the sum of the total number of nursing homes in all safety regions.

The number of infectious people is published via open data by the RIVM on a weekly basis (on Tuesdays). The description of this dataset can be found here. A person who carries coronavirus can infect other people within a certain time frame. How long someone is infectious for differs from person to person. Using a range of data sources regarding the number of people infected with the virus in a specific time frame, it is possible to estimate the number of infectious people in the Netherlands. See RIVM for more information regarding the method. There is no alert value for the number of infectious people as this number is an estimate based on a calculation.

The calculation method of the number of infectious people has been changed since 13 October. Between 1 June till 13 October this number was calculated based on the results of the first Pienter Corona research, the number of hospital admissions and the number of confirmed cases. From 13 October onwards, this number is calculated based on the results of the second Pienter Corona research and the number of hospital admissions. In this second research, a larger group of people have been examined. Besides, more insight in the infectiousness of people has been gained.

Information from general practitioners (GP) is published via open data by Nivel on a weekly basis (on Thursdays). The description of this dataset can be found here. A representative sample of around 350 GP practices across the Netherlands provide data once a week to Nivel. They record reported and observed symptoms and diagnoses of the consulting patients they see. Using this data, Nivel determines how many patients saw their GP in the past week for the first time for symptoms that could indicate COVID-19. Nivel determines this on the basis of the diagnostic codes reported by GPs (‘acute upper respiratory system infection’, ‘other respiratory infection(s)’, ‘influenza’, ‘pneumonia’, ‘other viral disease(s)’, ‘other infectious disease’, ‘fever’, ‘shortness of breath’, ‘coughing’) and any additional information provided that could indicate COVID-19.

To improve this indicator’s accuracy, Nivel also recalculates the data for the preceding weeks, so they include information that only became available at a later time. The open data reports the numbers per week.

Information on sewage water is made available via open data by the RIVM. The description of this dataset can be found here. Human excrement flushed down the toilet can contain pathogens (viruses and bacteria that can make people sick), which can be measured in wastewater. These tests measure the concentration of coronavirus particles in wastewater that may (but do not always) come from the excrement of infected individuals. Measurements are collected at more than 300 wastewater treatment plants around the country. At least once a week at each location, researchers from the RIVM test a sample of wastewater collected over a 24-hour period. The weekly number of locations with new data varies however, because not every test is completed successfully. The open data shows at which locations tests were done on a given date.

As of 3 November 2020, the dashboard no longer shows the number of virus particles in one millilitre of wastewater. Instead it shows the number of virus particles per 100,000 inhabitants. 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. RIVM now also corrects for the volume of water flowing into the plant at the time of sampling, which is called the flow rate. Rainwater, for example, has a diluting effect. However, it can only retrospectively correct the data from 7 September 2020, which means that data from before that date is no longer shown on the dashboard. This coincides with the fact that the number of testing locations was increased from roughly 80 to 318 on 7 September 2020.

If the number of virus particles in a sample is too low to be measured, the value is recorded as 0. Sometimes RIVM will indicate that a measurement isn’t representative. These measurements are filtered out when data is entered in the dashboard. The current study makes trends visible, such as an increase or decrease in the number of virus particles. But more research is needed before any conclusions can be drawn about these trends.

The weekly average is calculated by first determining the average of all measurements taken at a sampling site in a given week, and then using this to determine the average of all sampling sites for that week per municipality, safety region or for the country as a whole. A week runs from Monday to Sunday. The weekly average is calculated on the following Tuesday, so that the week is complete and the RIVM has time to receive and analyse the samples, and report on them. Please note that additional data relating to the preceding week or even the weeks before that may be received after Tuesday. This is why the open data file is read every day and the weekly averages recalculated. Any corrections relating to previous weeks are also entered in the dashboard. The graph shows the value of the sample for each location and the date on which it was collected.

Wastewater treatment plants are allocated to a safety region based on their catchment area, that is, the area from which wastewater flows to that plant to be treated. RIVM indicates what percentage of a location falls under a certain safety region. This distribution is not yet entirely accurate and will be finetuned in the coming period. The catchment area of some locations fall under more than one safety region. In that case, the location can be found on the dashboard under the safety region in which the biggest share of its catchment area falls. Locations are linked to municipalities on the basis of their postcode, using Statistics Netherlands’ distribution of postcodes per municipality. Sometimes this did not result in a match. In these exceptional cases, the location’s coordinates were looked up on a map to see which municipality it falls under. Please note that the link to a particular municipality may not be entirely accurate because a wastewater treatment plant’s catchment area may not coincide exactly with municipal boundaries. We are working to make a more accurate link between sewage treatment plant locations and municipalities.

The legend of the national map has been revised on the x of November. This shows differences between security region more clearly.

This data is updated every three weeks and is published as an open data file by the National Institute for Public Health and the Environment (RIVM). The description of this data set can be found here. The information on the Coronavirus Dashboard is also updated on the day the new file is released. The data file contains information on the Dutch public’s behaviour in relation to the COVID-19 rules and is based on findings obtained by means of a survey.

Data is collected online via computer-assisted web interviewing (CAWI). This method involves posting a programmed questionnaire online. Invitations to complete the questionnaire are then sent by email, explaining the purpose of the survey and referring to RIVM as the commissioning authority. The questionnaire was drawn up by RIVM’s Corona Behavioural Unit.

Participants are selected from the Kantar Consumer Panel (TNS NIPObase) and are aged 16 and over. For each safety region, invitations are sent to a representative sample according to gender, age (5 categories) and highest level of education completed (3 categories) (based on marginal totals). Assuming a 50% response rate, a gross sample of n=9,780 is drawn.

People in the study sample have one week to fill in the questionnaire online. After this, data collection is closed and responses are checked for reliability. To make the survey findings more representative for the entire Dutch population, the results are weighted in two steps on the basis of Statistics Netherlands’ population figures:

1. Firstly, the sample in each safety region is weighted according to the actual population distribution by age, sex and level of education for the region in question.
2. Secondly, each safety region is given a weight in the total, according to its share of the Dutch population.

The data set is then sent to RIVM which uses a standardised method to calculate values for the indicators included in the open data file.

The dashboard only shows data from the behavioural study that has been measured consistently over time. Differences compared to previous measurements are reported only if the way in which the measurements were taken was similar. Take the use of face masks on public transport, for example. The method used to measure this changed between rounds 3 and 4. The results of previous survey rounds therefore cannot be compared to that of round 4, and these earlier results are no longer presented together in the same historical chart. Regional differences are visible only if the group of respondents for a given question is representative for the overall population of a region. The complete set of survey results for each round is available on the RIVM website.

Every day the National Institute for Public Health and the Environment (RIVM) provides open data about the COVID-19 situation in disability care homes. A description of the data set can be found here.

This data cannot always be clearly linked to a specific safety region. As a result, the total sum of numbers at safety-region level may be less than the numbers at national level. The number of deaths is based on the date of death. However, when the date of death is unknown that death is not included in this statistic in the dashboard.

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 number of locations in each safety region is provided by RIVM. Care homes with the same postcode are counted as one location, which is identical to the method used to determine the number of infected locations. The number of locations in each safety region is needed in order to calculate the percentage of infected locations in that region. The total number of locations in the Netherlands is calculated by adding up the numbers for all of the safety regions.

As with nursing homes, information about disability care homes is based on records kept by the municipal health services (GGDs). As of 1 July 2020, every time a person tests positive for COVID-19, the GGD asks whether that person is a resident of a disability care home. A person is considered to be a disability care home resident if this is evident from information in OSIRIS (the database used by RIVM for this purpose). If it is unknown whether someone is a disability care home resident, their postcode can be used to link them to a registered disability care home or a setting (place where the infection may have occurred) labelled as a ‘care home’ or something similar.

Every day the National Institute for Public Health and the Environment (RIVM) provides open data about the COVID-19 situation among over-70s living at home. A description of the data set can be found here. This data cannot always be clearly linked to a specific safety region. As a result, the total sum of numbers at safety-region level may be less than the numbers at national level. The number of deaths is based on the date of death. However, when the date of death is unknown that death is not included in this statistic in the dashboard.

For its calculations RIVM uses test results and mortality data which it receives from the municipal health service (GGD). When people get tested for coronavirus, the GGD also records certain personal details, such as their age and whether 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:

• Amongst nursing home residents
• Amongst care workers
• Amongst people that can be linked to a care home via their address
• Amongst people that can be linked to a care home because of the setting of their infection.

The population of over-70s living at home is highly diverse in terms of their health and living situation. Many over-70s are active and in good health. But others live with at least one chronic disease and/or have physical or cognitive limitations, and are less active. It is not possible at this time to distinguish between COVID-19 infections among active and inactive over-70s living at home because information about activity levels is not recorded when people get tested for coronavirus.

The dashboard also shows the number of daily confirmed cases per 100,000 for over-70s living at home. The total number of over-70s living at home is based on data collected by Statistics Netherlands on the number of over-70s living in a private household (Households: size, composition, position, 1 January; cbs.nl). This group consists of roughly 2.3 million people.