The most important results from the study are presented on this page. The results have been updated until round 9 (end of 2022).

General information

The PIENTER Corona Study was launched in April 2020. As shown in Figure 1 below, a new round of research took place every few months after that. Round 9 took place in November and December 2022. The study group was expanded by adding new participants in round 2 and in round 6. Several thousand blood samples were examined in each round. The number of blood samples examined in round 9 was about 5,700.

In each round, slightly more than half of the blood samples generally came from women. Also, there are usually slightly more older participants than younger ones. This is taken into account in our analyses.

Timeline and (approximate) total number of blood samples per research round in rounds 1 through

Skip chart Timeline and (approximate) total number of blood samples per research round and go to datatable

Figure 1: Timeline and (approximate) total number of blood samples per research round in rounds 1 through 9.
*New participants were invited in round 2 and round 6.

Number of participants by age and region

The average age of the participants in the PIENTER Corona Study is about 50 years old. The youngest participant is 1 year old and the oldest participant is 92 years old. The figure below shows the current age distribution of the participants for each region in the Netherlands. The age groups of 70-74 years and 75-79 years had the most participants, and the age groups are evenly distributed across the regions.

Graph of Number of participants by age and region

Figure 2: Age distribution of participants (round 9 – November/December 2022). The regions shown consist of the following provinces: North = Groningen, Friesland, Drenthe and Overijssel; Midwest = North Holland and Flevoland; Midwest = Utrecht and Gelderland; Southwest = South Holland and Zeeland; Southeast = North Brabant and Limburg. LVC sample = Low Vaccination Coverage, consisting of a few municipalities in the Netherlands where general vaccination coverage (against infectious diseases covered by the National Immunisation Programme) is lower compared to the rest of the Netherlands.

The number of participants per municipality since round 6 (after the last expansion) is shown in Figure 3. The larger the blue dot, the more people from this municipality are participating. The distribution of blood samples for each municipality shows some correlation to the population distribution in the Netherlands: more people from the Randstad conurbation took part in the study. The research results are analysed with due consideration of differences in the participants’ gender, age, region and ethnic background.

Number of participants per municipality (round 6 – November/December 2021)

Figure 3: Number of participants per municipality (after the last expansion in round 6 – November/December 2021).

People who have antibodies

The research results show what percentage of the general population in the Netherlands is estimated to have generated antibodies against the coronavirus (SARS-CoV-2) that causes COVID-19. This allows us to estimate the number of people who have built up immunity to the virus due to infection, and (since the vaccination campaign started in 2021) also due to vaccination. The percentage of people who have antibodies is called seroprevalence.

During the first round of research in the spring of 2020, this was just under 3%. In the second round in summer 2020, it rose to 4.5%, reaching approximately 5% during the third round of the study in autumn 2020. In February 2021, seroprevalence had risen to over 14%. At that time, about 2% of the participants had antibodies resulting from vaccination and about 12% had had a coronavirus infection. In summer 2021 (round 5), nearly 65% of the population had antibodies against the coronavirus in their blood, and about 20% had evidence of previous infection. In autumn 2021 (round 6), more than 85% of the population had antibodies. At that time, over 25% of the total population turned out to have evidence of a previous infection in their blood. In spring 2022 (round 7), about 95% of the population had antibodies; this percentage remained consistently high throughout the year. At that time, slightly more than 60% of the population was found to have evidence of a previous infection in their blood. In summer 2022 (round 8), nearly three-quarters of the population had had at least one infection. By the end of 2022 (round 9), this percentage had increased to over 85%.

The percentage of people with antibodies has increased since the first rounds. This is mainly because of the vaccination programme that started in early 2021, as well as an increase in infections, particularly involving the Delta and Omicron variants of the virus. After the Omicron variant arrived, there were hardly any differences between men and women, or between people from different ethnic backgrounds. Previous regional differences have also disappeared almost entirely.

Age distribution of people who have antibodies

Figure 4 shows the percentage of participants with antibodies distributed across the age groups in the population (from 1 up to 92 years old) since the first wave in 2020. The research results from the PIENTER Corona Study are then extrapolated to the general population of the Netherlands. An estimate is provided for the percentage of the Dutch population that has been in contact with the coronavirus in each age group.

Vaccination against SARS-CoV-2 started in January 2021 in the Netherlands. Therefore, since the fourth round in February 2021, immunity resulting from infection and/or from vaccination has been investigated. This research is done by looking at different types of antibodies in combination with information from the questionnaire and information about infections from previous rounds. In addition, some people also become infected after vaccination, especially since the Omicron variant.

Percentage of people who have antibodies by age over time

Figure 4: Percentage of people who have antibodies by age over time (rounds 2-9). The dotted lines (light green to dark purple) show the percentage of people who have antibodies due to infection in round 2 (June/July 2020) up to and including round 9 (November/December 2022). The orange line shows total seroprevalence after infection and vaccination in round 9 (November/December 2022).

As seen in rounds 4–8, the antibody results from the ninth round (November/December 2022) show a combination of vaccination and infections in the population (Figure 4, orange line). At the start of 2021, the older age groups and vulnerable people were the first to be invited for a COVID-19 vaccination. The younger age groups followed later. In general, vaccination coverage is high among adults and quite a bit lower among children under 12. In all age groups over 12 years, the percentage of people with antibodies (resulting from infection and/or vaccination, orange line in Figure 4) was 95% or higher in round 9.

From round 2 through round 6, there was a similar trend in the percentage of people who showed evidence of infection (Figure 4, from light green to dark green dotted line). In every round, young adults showed the highest percentage of infections, relatively speaking, followed by people aged 50-59 years; this percentage was lowest in the oldest age groups.

In the seventh round (Figure 4, light brown dotted line), there was a major increase in the percentage of infections compared to the previous round, caused by the Delta and Omicron variants of the coronavirus SARS-CoV-2. The strongest increase occurred in people under 50, was clearly visible in children, and then gradually declined in older people. Round 8 shows a 10-15% increase in infections across all ages (reddish-brown dotted line). Overall, young people were still the age group with the highest percentage of infections (up to 95%). In round 9, the percentage of people who showed evidence of one or more infections in the blood rose among all adults by about 15% (Figure 4, dark purple dotted line). Nearly everyone under 50 years old had been infected at least once by then. Despite the increase in infections, the oldest age groups still show the lowest percentage, relatively speaking. Among 80-year-olds, for example, about two in three people have had a SARS-CoV-2 infection at some point in time.

Mucosal antibodies

The SARS-CoV-2 virus enters the body through the upper respiratory tract, including the nose. Antibodies in the blood offer effective protection against severe COVID-19, but are less effective against infection in the respiratory tract at the entry point for the virus. Antibodies in the respiratory system do help protect against infection. These are called mucosal antibodies. In round 8, a number of PIENTER Corona Study participants were also asked to provide a nasal swab (similar to taking a COVID-19 self-test). These samples taken from the nose were checked for mucosal antibodies against SARS-CoV-2.

The body produces various types of antibodies. These tests looked at the IgG type that is common in blood, and to a lesser extent also in the nose, as well as the IgA type that is important in mucous membranes such as the nose. About 93% of all participants who provided a nasal swab and about 98% of these participants aged 12 years and older had nasal IgG-type antibodies (Figure 5A). People who had been vaccinated were just as likely to have nasal IgG antibodies as people who had been vaccinated and had an infection. About 24% of all participants had type IGA antibodies. That percentage rises to about 33% if people had had a SARS-CoV-2 infection (Figure 5B). Young children are less likely to have nasal antibodies than children aged 12 years and older. After vaccination, IgG antibodies are produced and can be found in the nose, but nasal IgA antibodies are not usually found after vaccination. After a SARS-CoV-2 infection, both IgG and IgA antibodies are found in about 33% of participants. The amount of nasal IgG and IgA antibodies is higher in people who have had a previous infection (Figure 5C-D). In addition, people with more antibodies were less likely to become infected with the virus in the next round. Mucosal antibodies make the virus less able to bind to human cells and help the body clear the virus.

Graphs of Mucosal antibodies in nasal fluid from participants in round 8 – June/July 2022, distinguishing between people who had had a previous infection (red) and people who showed no evidence of previous infection (blue). BAU / AU are the units used to measure antibody concentrations.

Figure 5: Mucosal antibodies in nasal fluid from participants in round 8 – June/July 2022, distinguishing between people who had had a previous infection (red) and people who showed no evidence of previous infection (blue). BAU / AU are the units used to measure antibody concentrations.

(A) Percentage of participants with mucosal S1 IgG antibodies by age;
(B) Percentage of participants with mucosal S1 IgA antibodies by age;
(C) Mucosal S1 IgG antibody concentrations by age;
(D) Mucosal S1 IgA antibody concentrations by age;
(E) Total mucosal S1 IgG antibody concentrations;
(F) Total mucosal S1 IgA antibody concentrations.

The results of the PIENTER Corona Study are presented in scientific articles for publication, so they can be read by everyone. As a result, other countries can also benefit from the research and use key findings in formulating their public health policies. When articles are published online, they will be posted on this page.

Age-specific severity of SARS-CoV-2 infections over time (based on data from rounds 1–5): 
de Boer PT, van de Kassteele J, Vos ERA, et al. Age-specific severity of SARS-CoV-2 in February 2020 – June 2021 in the Netherlands.  medRxiv 2023.02.09.23285703.

Contact patterns in the population of the Netherlands (based on data from rounds 1, 2, 4 and 5): 
Backer JA, Bogaardt L, Beutels P, et al. Dynamics of non-household contacts during the COVID-19 pandemic in 2020 and 2021 in the Netherlands.  Scientific Reports 13, 5166 (2023).

Effect of the COVID-19 lockdowns on antibodies against respiratory syncytial virus (RSV) (using data from rounds 2, 4 and 5):
den Hartog G, van Kasteren PB, Schepp RM, et al. Decline of RSV-specific antibodies during the COVID-19 pandemic. Lancet Infect Dis. 2023 Jan;23(1):23-25.

Modelling the impact of vaccinating adolescents and children (using contact data from 2020 and 2021):
Ainslie KEC, Backer JA, de Boer PT, et al. A scenario modelling analysis to anticipate the impact of COVID-19 vaccination in adolescents and children on disease outcomes in the Netherlands, summer 2021. Euro Surveill. 2022 Nov;27(44):2101090.

The burden of disease from acute COVID-19 (using data from round 3):
McDonald SA, Lagerweij GR, de Boer P, et al. The estimated disease burden of acute COVID-19 in the Netherlands in 2020, in disability-adjusted life-years. European Journal of Epidemiology.  2022 Aug 11;1-13.

The antibody response after vaccination (using data from round 5):
van den Hoogen LL, Verheul MK, Vos ERA et al. SARS-CoV-2 Spike S1-specific IgG kinetic profiles following mRNA or vector-based vaccination in the general Dutch population show distinct kinetics.  Scientific Reports. 2022 Apr 8;12(1):5935.

Use of antibodies to identify breakthrough infections after vaccination (using data from round 4):
van den Hoogen LL, Smits G, van Hagen CCE, et al. Seropositivity to Nucleoprotein to detect mild and asymptomatic SARS-CoV-2 infections: A complementary tool to detect breakthrough infections after COVID-19 vaccination?  Vaccine. 2022 Apr 1;40(15):2251-2257.

Duration of immunity and binding strength of SARS-CoV-2 antibodies more than six months after infection (based on data from rounds 1-3):
den Hartog G, Vos ERA, van den Hoogen LL, et al. Persistence of antibodies to SARS-CoV-2 in relation to symptoms in a nationwide prospective study.  Clinical Infectious Diseases. 2021 Dec 16;73(12):2155-2162

The effect of social distancing measures on SARS-CoV-2 infection after the first wave (based on data from round 2):
Vos ERA, van Boven M, den Hartog G, et al. Associations between measures of social distancing and SARS-CoV-2 seropositivity: a nationwide population-based study in the Netherlands. Clinical Infectious Diseases. 2021 Dec 16;73(12):2318-2321.

An algorithm to determine optimal vaccine allocation (using data from round 2):
Miura F, Leung KY, Klinkenberg D, et al. Optimal vaccine allocation for COVID-19 in the Netherlands: A data-driven prioritization. PLoS Comput Biol. 2021 Dec 13;17(12):e1009697.

Comparison of seroprevalence among children in hospital and children in the general population (using data from round 3):
Rotee ILM, Ong DSY, Koeleman JGM, et al. Trends in SARS-CoV-2 seroprevalence amongst urban paediatric patients compared with a nationwide cohort in the Netherlands. J Clin Virol Plus. 2021 Dec;1(4):100045.

Preprint about the possibility of intradermal administration of COVID-19 vaccinations for dose sparing (using comparative data from round 5 and round 6): 
Roozen GVT, Prins MLM, van Binnendijk R, et al. Tolerability, safety and immunogenicity of intradermal delivery of a fractional dose mRNA-1273 SARS-CoV-2 vaccine in healthy adults as a dose sparing strategy. medRxiv 2021.07.27.21261116.
An abbreviated version was published previously: Roozen GVT, Prins MLM, van Binnendijk R, et al. Safety and Immunogenicity of Intradermal Fractional Dose Administration of the mRNA-1273 Vaccine: A Proof-of-Concept Study. Ann Intern Med. 2022 Dec;175(12):1771-1774.

Estimated asymptomatic SARS-CoV-2 infections in the population (based on data from the PIENTER3 study, and from PIENTER Corona Study rounds 1 and 2): McDonald SA, Miura F, Vos ERA, et al. Estimating the asymptomatic proportion of SARS-CoV-2 infection in the general population: Analysis of nationwide serosurvey data in the Netherlands.  European Journal of Epidemiology. 2021 Jul;36(7):735-739.

Evaluation of the effect of measures aimed at reducing school-related and non-school-related contact (using data from rounds 1 and 2):
Rozhnova G, van Dorp CH, Bruijning-Verhagen P, et al. Model-based evaluation of school- and non-school-related measures to control the COVID-19 pandemic. Nat Commun. 2021 Mar 12;12(1):1614.

The effect of social distancing on contact patterns in the population (based on data from rounds 1 and 2):
Backer JA, Mollema L, Vos ER, et al. Impact of physical distancing measures against COVID-19 on contacts and mixing patterns: repeated cross-sectional surveys, the Netherlands, 2016–17, April 2020 and June 2020.  Eurosurveillance. 2021 Feb;26(8):2000994.

Analysis of SARS-CoV-2 seroprevalence and risk factors, as well as symptoms in relation to antibody levels after infection during the first wave (based on data from round 1):
Vos ERA, den Hartog G, Schepp RM, et al. Nationwide seroprevalence of SARS-CoV-2 and identification of risk factors in the general population of the Netherlands during the first epidemic wave. Journal of Epidemiology and Community Health. 2020 Nov 28;75(6):489–95. 

Laboratory method for measuring SARS-CoV-2 antibodies:
den Hartog G, Schepp RM, Kuijer M, et al. SARS-CoV-2–Specific Antibody Detection for Seroepidemiology: A Multiplex Analysis Approach Accounting for Accurate Seroprevalence. The Journal of Infectious Diseases. 2020 Oct 1;222(9):1452-1461.

RIVM previously published an article on the scientific background of the PIENTER3 study:
Verberk JDM, Vos RA, Mollema L, et al. Third national biobank for population-based seroprevalence studies in the Netherlands, including the Caribbean Netherlands. BMC Infectious Diseases. 2019 May;19(1):470.