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.
New hospital admissions are made available as open data by the Stichting NICE (the National Intensive Care Evaluation Registry). The description of this dataset can be found here. The average number of daily hospital admissions is calculated using the figures for one day ago, two days ago and three days ago. Data for the present day is not included in this calculation, as the present day is not yet over and registration data is therefore incomplete. Although hospitals strive to register COVID-19 patients as fast as possible, there is usually some delay. As a result, the figures for the previous several days tend to be incomplete. That is why data on the dashboard is refreshed daily.
Previously, new hospital admissions on a national level were based on open data from RIVM. The description of this dataset can be found here. This dataset uses the Osiris database. However, this database suffers from significant underreporting. The NICE database is more complete and uses a broader definition of hospital admission. RIVM figures include only those patients admitted to hospital because of COVID-19, whereas NICE figures also include patients who were admitted to the hospital for another reason but also have COVID-19.
NICE figures cannot currently be broken down by safety region or municipality. Data at these levels is therefore still taken from the Osiris database. Work is being done to provide NICE figures for hospital admissions at safety region and municipal levels.
Hospital occupancy rates (non-ICU) are obtained daily via open data from LCPS. The description of this dataset can be found here. The total 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.
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.
The database provides figures per safety region and municipality. National figures are obtained by adding up all the notifications. In some cases, notifications cannot be linked to a particular municipality/safety region. These cannot therefore be shown at that level, but they are included in the national figures. We calculate the relative rate of infection in the following way. First, we divide the Netherlands’ total population by 100,000. We then divide the number of daily positive tests by the outcome of that division. This gives us the number of daily positive tests per 100,000 inhabitants. This makes it possible to compare individual municipalities and safety regions. The number of inhabitants is based on data supplied by Statistics Netherlands CBS-indeling. The division of new cases by age group is based on the national figures because ages are not recorded in the file containing municipal data. The table on the RIVM website may therefore not always match the table on the dashboard.
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 weekly data relating to the GGD test centres (for example number of people tested and average processing time).
The reproduction number is supplied every Tuesday as open data by the National Institute for Public Health and the Environment (RIVM). The description of this dataset can be found here. The reproduction number (R) is not an exact value, but a reliable estimate. The value of R is based on (1) the number of ICU and hospital admissions, and (2) the day on which these ICU and hospital patients developed symptoms. 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 3 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 will no longer display 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.
A representative sample of around 350 GP practices across the Netherlands provide data once a week to the Netherlands Institute for Health Services Research (Nivel) Primary Care Database. 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 Nivel Primary Care Database provides this information once a week (Thursdays) and delivers this information in JSON format to the Ministry of Health, Welfare and Sport. The source file gives the numbers per week. On the dashboard, these are shown as the weekly figures indicated by the date of the last day (Sunday) of each week. The weekly values in the file are copied directly onto the dashboard.
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.
The tiles on the dashboard show the term "value of" to indicate the date to which the number refers, while ‘obtained’ is used to refer to the date when the information was received. The purpose of providing this information is to give users a better idea of how up-to-date the data is, which is especially relevant for retrospective indicators. For instance, RIVM publishes the reproduction number (R) once a week, but the most recent R is always for a date two weeks in the past. ‘Value of’ is followed by that date two weeks ago, and ‘obtained’ by the date on which the most recent R was published (the current week).
This dashboard was developed in a short amount of time. So far, we have therefore not been able to publish the code for inputting the data and constructing the .JSON files. However, this will be done soon. The web application code was published on Github on 5 June 2020. The data calculations are available via Github as well.