Publications by authors named "Jan van de Kassteele"

36 Publications

Excess Deaths during Influenza and Coronavirus Disease and Infection-Fatality Rate for Severe Acute Respiratory Syndrome Coronavirus 2, the Netherlands.

Emerg Infect Dis 2021 02 4;27(2):411-420. Epub 2021 Jan 4.

Since the 2009 influenza pandemic, the Netherlands has used a weekly death monitoring system to estimate deaths in excess of expectations. We present estimates of excess deaths during the ongoing coronavirus disease (COVID-19) epidemic and 10 previous influenza epidemics. Excess deaths per influenza epidemic averaged 4,000. The estimated 9,554 excess deaths (41% in excess) during the COVID-19 epidemic weeks 12-19 of 2020 appeared comparable to the 9,373 excess deaths (18%) during the severe influenza epidemic of 2017-18. However, these deaths occurred in a shorter time, had a higher peak, and were mitigated by nonpharmaceutical control measures. Excess deaths were 1.8-fold higher than reported laboratory-confirmed COVID-19 deaths (5,449). Based on excess deaths and preliminary results from seroepidemiologic studies, we estimated the infection-fatality rate to be 1%. Monitoring of excess deaths is crucial for timely estimates of disease burden for influenza and COVID-19. Our data complement laboratory-confirmed COVID-19 death reports and enable comparisons between epidemics.
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http://dx.doi.org/10.3201/eid2702.202999DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7853586PMC
February 2021

Proximity to livestock farms and exposure to livestock-related particulate matter are associated with lower probability of medication dispensing for obstructive airway diseases.

Int J Hyg Environ Health 2021 Jan 28;231:113651. Epub 2020 Oct 28.

National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720, BA, Bilthoven, the Netherlands.

Objectives: The aim of this study is to assess whether medication use for obstructive airway diseases is associated with environmental exposure to livestock farms. Previous studies in the Netherlands at a regional level suggested that asthma and chronic obstructive pulmonary disease (COPD) are less prevalent among persons living near livestock farms.

Methods: A nationwide population-based cross-sectional study was conducted among 7,735,491 persons, with data on the dispensing of drugs for obstructive airway diseases in the Netherlands in 2016. Exposure was based on distances between home addresses and farms and on modelled atmospheric particulate matter (PM) concentrations from livestock farms. Data were analysed for different regions by logistic regression analyses and adjusted for several individual-level variables, as well as modelled PM concentration of non-farm-related air pollution. Results for individual regions were subsequently pooled in meta-analyses.

Results: The probability of medication for asthma or COPD being dispensed to adults and children was lower with decreasing distance of their homes to livestock farms, particularly cattle and poultry farms. Increased concentrations of PM from cattle were associated with less dispensing of medications for asthma or COPD, as well (meta-analysis OR for 10th-90th percentile increase in concentration of PM from cattle farms, 95%CI: 0.92, 0.86-0.97 for adults). However, increased concentrations of PM from non-farm sources were positively associated (meta-analysis OR for 10th-90th percentile increase in PM-concentration, 95%CI: 1.29, 1.09-1.52 for adults).

Conclusions: The results show that the probability of dispensing medication for asthma or COPD is inversely associated with proximity to livestock farms and modelled exposure to livestock-related PM in multiple regions within the Netherlands. This finding implies a notable prevented risk: under the assumption of absence of livestock farms in the Netherlands, an estimated 2%-5% more persons (an increase in tens of thousands) in rural areas would receive asthma or COPD medication.
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http://dx.doi.org/10.1016/j.ijheh.2020.113651DOI Listing
January 2021

Trade-off between local transmission and long-range dispersal drives infectious disease outbreak size in spatially structured populations.

PLoS Comput Biol 2020 07 6;16(7):e1008009. Epub 2020 Jul 6.

Centre for Infectious Disease Control, National Institute for Public Health and the Environment, The Netherlands.

Transmission of infectious diseases between immobile hosts (e.g., plants, farms) is strongly dependent on the spatial distribution of hosts and the distance-dependent probability of transmission. As the interplay between these factors is poorly understood, we use spatial process and transmission modelling to investigate how epidemic size is shaped by host clustering and spatial range of transmission. We find that for a given degree of clustering and individual-level infectivity, the probability that an epidemic occurs after an introduction is generally higher if transmission is predominantly local. However, local transmission also impedes transfer of the infection to new clusters. A consequence is that the total number of infections is maximal if the range of transmission is intermediate. In highly clustered populations, the infection dynamics is strongly determined by the probability of transmission between clusters of hosts, whereby local clusters act as multiplier of infection. We show that in such populations, a metapopulation model sometimes provides a good approximation of the total epidemic size, using probabilities of local extinction, the final size of infections in local clusters, and probabilities of cluster-to-cluster transmission. As a real-world example we analyse the case of avian influenza transmission between poultry farms in the Netherlands.
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http://dx.doi.org/10.1371/journal.pcbi.1008009DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7365471PMC
July 2020

The association between influenza infections in primary care and intensive care admissions for severe acute respiratory infection (SARI): A modelling approach.

Influenza Other Respir Viruses 2020 09 12;14(5):575-586. Epub 2020 Jun 12.

Centre for Infectious Disease Control Netherlands, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands.

Background: The burden of severe influenza virus infections is poorly known, for which surveillance of severe acute respiratory infection (SARI) is encouraged. Hospitalized SARI patients are however not always tested for influenza virus infection. Thus, to estimate the impact of influenza circulation we studied how influenza in primary care relates to intensive care unit (ICU) admissions using a modelling approach.

Methods: We used time-series regression modelling to estimate a) the number of SARI admissions to ICU associated with medically attended influenza infections in primary care; b) how this varies by season; and c) the time lag between SARI and influenza time series. We analysed weekly adult ICU admissions (registry data) and adult influenza incidence (primary care surveillance data) from July 2007 through June 2016.

Results: Depending on the year, 0% to 12% of annual SARI admissions were associated with influenza (0-554 in absolute numbers; population rate: 0/10 000-0.39/10 000 inhabitants), up to 27% during influenza epidemics. The average optimal fitting lag was +1 week (SARI trend preceding influenza by 1 week), varying between seasons (-1 to +4) with most seasons showing positive lags.

Conclusion: Up to 12% of yearly SARI admissions to adult ICU are associated with influenza, but with large year-to-year variation and higher during influenza epidemics. In most years, SARI increases earlier than medically attended influenza infections in the general population. SARI surveillance could thus complement influenza-like illness surveillance by providing an indication of the season-specific burden of severe influenza infections and potential early warning of influenza activity and severity.
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http://dx.doi.org/10.1111/irv.12759DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7431650PMC
September 2020

Ambulance dispatch calls attributable to influenza A and other common respiratory viruses in the Netherlands (2014-2016).

Influenza Other Respir Viruses 2020 07 14;14(4):420-428. Epub 2020 May 14.

Centre for Infectious Disease Control Netherlands (CIb), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands.

Background: Ambulance dispatches could be useful for syndromic surveillance of severe respiratory infections. We evaluated whether ambulance dispatch calls of highest urgency reflect the circulation of influenza A virus, influenza B virus, respiratory syncytial virus (RSV), rhinovirus, adenovirus, coronavirus, parainfluenzavirus and human metapneumovirus (hMPV).

Methods: We analysed calls from four ambulance call centres serving 25% of the population in the Netherlands (2014-2016). The chief symptom and urgency level is recorded during triage; we restricted our analysis to calls with the highest urgency and identified those compatible with a respiratory syndrome. We modelled the relation between respiratory syndrome calls (RSC) and respiratory virus trends using binomial regression with identity link function.

Results: We included 211 739 calls, of which 15 385 (7.3%) were RSC. Proportion of RSC showed periodicity with winter peaks and smaller interseasonal increases. Overall, 15% of RSC were attributable to respiratory viruses (20% in out-of-office hour calls). There was large variation by age group: in <15 years, only RSV was associated and explained 11% of RSC; in 15-64 years, only influenza A (explained 3% of RSC); and in ≥65 years adenovirus explained 9% of RSC, distributed throughout the year, and hMPV (4%) and influenza A (1%) mainly during the winter peaks. Additionally, rhinovirus was associated with total RSC.

Conclusion: High urgency ambulance dispatches reflect the burden of different respiratory viruses and might be useful to monitor the respiratory season overall. Influenza plays a smaller role than other viruses: RSV is important in children while adenovirus and hMPV are the biggest contributors to emergency calls in the elderly.
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http://dx.doi.org/10.1111/irv.12731DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7298355PMC
July 2020

Tracing the Origin of Food-borne Disease Outbreaks: A Network Model Approach.

Epidemiology 2020 05;31(3):327-333

Department of Statistics, Informatics and Modelling, National Institute for Public Health and the Environment, Bilthoven, Netherlands.

Background: Food-borne disease outbreaks constitute a large health burden on society. One of the challenges when investigating such outbreaks is to trace the origin of the outbreak. In this study, we consider a network model to determine the spatial origin of the contaminated food product that caused the outbreak.

Methods: The network model we use replaces the classic geographic distance of a network by an effective distance so that two nodes connected by a long-range link may be more strongly connected than their geographic distance would suggest. Furthermore, the effective distance transforms complex spatial patterns into regular topological patterns, creating a means for easier identification of the origin of the spreading phenomenon. Because detailed information on food distribution is generally not available, the model uses the gravity model from economics: the flow of goods from one node to another increases with population size and decreases with the geographical distance between them.

Results: This effective distance network approach has been shown to perform well in a large Escherichia coli O104:H4 outbreak in Germany in 2011. In this article, we apply the same method to various food-borne disease outbreaks in the Netherlands. We found the effective distance network approach to fail in certain scenarios.

Conclusions: Great care should be taken as to whether the underlying network model correctly captures the spreading mechanism of the outbreak in terms of spatial scale and single or multiple source outbreak.
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http://dx.doi.org/10.1097/EDE.0000000000001169DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7144751PMC
May 2020

Use of Ambulance Dispatch Calls for Surveillance of Severe Acute Respiratory Infections.

Emerg Infect Dis 2020 01;26(1):148-150

Ambulance dispatches for respiratory syndromes reflect incidence of influenza-like illness in primary care. Associations are highest in children (15%-34% of respiratory calls attributable to influenza), out-of-office hours (9%), and highest urgency-level calls (9%-11%). Ambulance dispatches might be an additional source of data for severe influenza surveillance.
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http://dx.doi.org/10.3201/eid2601.181520DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6924878PMC
January 2020

Nowcasting the Number of New Symptomatic Cases During Infectious Disease Outbreaks Using Constrained P-spline Smoothing.

Epidemiology 2019 09;30(5):737-745

From the National Institute for Public Health and the Environment-RIVM, Bilthoven, the Netherlands.

During an infectious disease outbreak, timely information on the number of new symptomatic cases is crucial. However, the reporting of new cases is usually subject to delay due to the incubation period, time to seek care, and diagnosis. This results in a downward bias in the numbers of new cases by the times of symptoms onset towards the current day. The real-time assessment of the current situation while correcting for underreporting is called nowcasting. We present a nowcasting method based on bivariate P-spline smoothing of the number of reported cases by time of symptoms onset and delay. Our objective is to predict the number of symptomatic-but-not-yet-reported cases and combine these with the already reported symptomatic cases into a nowcast. We assume the underlying two-dimensional reporting intensity surface to be smooth. We include prior information on the reporting process as additional constraints: the smooth surface is unimodal in the reporting delay dimension, is (almost) zero at a predefined maximum delay and has a prescribed shape at the beginning of the outbreak. Parameter estimation is done efficiently by penalized iterative weighted least squares. We illustrate our method on a large measles outbreak in the Netherlands. We show that even with very limited information the method is able to accurately predict the number of symptomatic-but-not-yet-reported cases. This results in substantially improved monitoring of new symptomatic cases in real time.
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http://dx.doi.org/10.1097/EDE.0000000000001050DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6684223PMC
September 2019

"Sickenin' in the rain" - increased risk of gastrointestinal and respiratory infections after urban pluvial flooding in a population-based cross-sectional study in the Netherlands.

BMC Infect Dis 2019 May 2;19(1):377. Epub 2019 May 2.

Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Antonie van Leeuwenhoeklaan 9, 3721MA, Bilthoven, Utrecht, the Netherlands.

Background: Climate change is expected to increase the chance of extreme rainfall events in the Northern Hemisphere and herewith, there is an increased chance of urban pluvial flooding. Urban pluvial flooding often consists of street flooding and/or flooding of combined sewerage systems, leading to contamination of the floodwater with several gastrointestinal and/or respiratory pathogens. An increase in flooding events therefore pose a health risk to those exposed to urban floodwater. We studied the association between exposure to pluvial floodwater and acute gastroenteritis (AGE) and acute respiratory infection (ARI).

Methods: We performed a retrospective, cross-sectional survey during the summer of 2015 in 60 locations in the Netherlands with reported flooding. Two weeks after the flooding, questionnaires were sent to households in these locations, collecting data on self-reported AGE and ARI and information on floodwater exposure in the previous 2 weeks. Multivariable generalized estimating equations (GEE) regression models, accounting for the clustered data structure, were used to identify risk factors for AGE and ARI.

Results: In total, 699 households with 1,656 participants (response rate 21%) returned the questionnaire. Contact with floodwater was significantly associated with AGE (aOR 4.2, 95%CI 2.1-8.4) and ARI (aOR 3.3, 95%CI 2.0-5.4). Risk factors for AGE were skin contact with floodwater (aOR 4.0, 95%CI 1.8-9.0), performing post-flooding cleaning operations (aOR 8.6, 95%CI 3.5-20.9) and cycling through floodwater (aOR 2.3, 95%CI 1.0-5.0). Skin contact with floodwater (aOR 3.6, 95%CI 1.9-6.9) and performing post-flooding cleaning operations (aOR 5.5, 95%CI 3.0-10.3) were identified as risk factors for ARI.

Conclusions: Results suggest an association between direct exposure to pluvial floodwater and AGE and ARI. As it is predicted that the frequency of pluvial flooding events will increase in the future, there is a need for flood-proof solutions in urban development and increased awareness among stakeholders and the public about the potential health risks. Future prospective studies are recommended to confirm our results.
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http://dx.doi.org/10.1186/s12879-019-3984-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6498475PMC
May 2019

Maternal pertussis vaccination and its effects on the immune response of infants aged up to 12 months in the Netherlands: an open-label, parallel, randomised controlled trial.

Lancet Infect Dis 2019 04 27;19(4):392-401. Epub 2019 Mar 27.

Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, Netherlands. Electronic address:

Background: Maternal tetanus, diphtheria, and acellular pertussis (Tdap) vaccination offers protection for neonates against clinical pertussis until primary vaccinations, but maternal antibodies also interfere with infants' immune responses to primary vaccinations. We investigated the effect of maternal Tdap vaccination on the pertussis antibody responses of infants starting primary vaccinations at age 3 months.

Methods: In an open-label, parallel, randomised, controlled trial, pregnant women aged 18-40 years with a low risk of pregnancy complications were recruited through independent midwives at 36 midwife clinics in the Netherlands and received Tdap vaccination either at 30-32 weeks of pregnancy (maternal Tdap group) or within 48 h after delivery (control group). All term-born infants were vaccinated with the diphtheria, tetanus, and pertussis-inactivated poliomyelitis-Haemophilus influenzae type B-hepatitis B six-in-one vaccine and a ten-valent pneumococcal vaccine at 3 months, 5 months, and 11 months. Randomisation was done using a number generator in a 1:1 ratio and with sealed envelopes. Participants and clinical trial staff were not masked, but laboratory technicians were unaware of study group assignments. The primary endpoint was serum IgG pertussis toxin antibody concentrations at age 3 months. Cord blood and infant blood samples were collected at age 2 months, 3 months, 6 months, 11 months, and 12 months. Analysis was done by modified intention to treat with all randomly assigned participants in case a laboratory result was available. This trial is registered with ClinicaltTrialsRegister.eu (EudraCT 2012-004006-9) and trialregister.nl (NTR number NTR4314). The trial is now closed to new participants.

Findings: Between Jan 16, 2014, and March 4, 2016, 118 pregnant women were enrolled into our study, with 58 in the maternal Tdap group and 60 in the control group. The geometric mean concentration (GMC) of pertussis toxin antibodies were higher in infants in the maternal Tdap group than in the control group infants at age 3 months (GMC ratio 16·6, 95% CI 10·9-25·2) and also significantly higher compared with control infants at age 2 months. After primary vaccinations, antibody concentrations for pertussis toxin, filamentous haemagglutinin, and pertactin were significantly lower at all timepoints in infants of the maternal Tdap group than in infants in the control group. No safety issues after maternal Tdap vaccination were encountered.

Interpretation: In view of the high pertussis toxin antibody concentrations at age 3 months, maternal vaccination supports a delay of the first pertussis vaccination in infants until at least age 3 months. Maternal antibody interference affects antibody concentrations after primary and booster vaccinations. The clinical consequences of this interference remain to be established.

Funding: The Dutch Ministry of Health, Welfare, and Sport.
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http://dx.doi.org/10.1016/S1473-3099(18)30717-5DOI Listing
April 2019

Immunogenicity of Influenza Vaccines: Evidence for Differential Effect of Secondary Vaccination on Humoral and Cellular Immunity.

Front Immunol 2018 29;9:3103. Epub 2019 Jan 29.

Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, Netherlands.

While currently used influenza vaccines are designed to induce neutralizing antibodies, little is known on T cell responses induced by these vaccines. The 2009 pandemic provided us with the opportunity to evaluate the immune response to vaccination in a unique setting. We evaluated both antibody and T cell responses in a cohort of public health care workers (18-52 years) during two consecutive influenza seasons from 2009 to 2011 and compared the MF59-adjuvanted pandemic vaccine with the unadjuvanted seasonal subunit vaccine that included the pandemic strain [The study was registered in the Netherlands Trial Register (NTR2070)]. Antibody responses were determined in serum by a hemagglutination inhibition assay. Vaccine-specific T cell responses were evaluated by detecting IFN-γ producing peripheral blood mononuclear cells using whole influenza virus or vaccine-specific peptide pools as stimulating antigens. Mixed effects regression models were used to correct the data for influenza-specific pre-existing immunity due to previous infections or vaccinations and for age and sex. We show that one dose of the pandemic vaccine induced antibody responses sufficient for providing seroprotection and that the vaccine induced T cell responses. A second dose further increased antibody responses but not T cell responses. Nonetheless, both could be boosted by the seasonal vaccine in the subsequent season. Furthermore, we show that the seasonal vaccine alone is capable of inducing vaccine-specific T cell responses, despite the fact that the vaccine did not contain an adjuvant. In addition, residual antibody levels remained detectable for over 15 months, while T cell levels in the blood had contracted to baseline levels by that time. Hereby, we show that pandemic as well as seasonal vaccines induce both humoral and cellular responses, however, with a different profile of induction and waning, which has its implications for future vaccine design.
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http://dx.doi.org/10.3389/fimmu.2018.03103DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6362424PMC
October 2019

Prevention of hospital infections by intervention and training (PROHIBIT): results of a pan-European cluster-randomized multicentre study to reduce central venous catheter-related bloodstream infections.

Intensive Care Med 2018 01 16;44(1):48-60. Epub 2017 Dec 16.

Infection Control and World Health Organization Collaborating Center on Patient Safety, The University of Geneva Hospitals and Faculty of Medicine, Rue Gabrielle Perret-Gentil 4, 1211, Geneva, Switzerland.

Purpose: To test the effectiveness of a central venous catheter (CVC) insertion strategy and a hand hygiene (HH) improvement strategy to prevent central venous catheter-related bloodstream infections (CRBSI) in European intensive care units (ICUs), measuring both process and outcome indicators.

Methods: Adult ICUs from 14 hospitals in 11 European countries participated in this stepped-wedge cluster randomised controlled multicentre intervention study. After a 6 month baseline, three hospitals were randomised to one of three interventions every quarter: (1) CVC insertion strategy (CVCi); (2) HH promotion strategy (HHi); and (3) both interventions combined (COMBi). Primary outcome was prospective CRBSI incidence density. Secondary outcomes were a CVC insertion score and HH compliance.

Results: Overall 25,348 patients with 35,831 CVCs were included. CRBSI incidence density decreased from 2.4/1000 CVC-days at baseline to 0.9/1000 (p < 0.0001). When adjusted for patient and CVC characteristics all three interventions significantly reduced CRBSI incidence density. When additionally adjusted for the baseline decreasing trend, the HHi and COMBi arms were still effective. CVC insertion scores and HH compliance increased significantly with all three interventions.

Conclusions: This study demonstrates that multimodal prevention strategies aiming at improving CVC insertion practice and HH reduce CRBSI in diverse European ICUs. Compliance explained CRBSI reduction and future quality improvement studies should encourage measuring process indicators.
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http://dx.doi.org/10.1007/s00134-017-5007-6DOI Listing
January 2018

Identifying the source of food-borne disease outbreaks: An application of Bayesian variable selection.

Stat Methods Med Res 2019 04 15;28(4):1126-1140. Epub 2017 Dec 15.

1 Department of Statistics, Informatics and Modelling, RIVM, Bilthoven, Netherlands.

Early identification of contaminated food products is crucial in reducing health burdens of food-borne disease outbreaks. Analytic case-control studies are primarily used in this identification stage by comparing exposures in cases and controls using logistic regression. Standard epidemiological analysis practice is not formally defined and the combination of currently applied methods is subject to issues such as response misclassification, missing values, multiple testing problems and small sample estimation problems resulting in biased and possibly misleading results. In this paper, we develop a formal Bayesian variable selection method to account for misclassified responses and missing covariates, which are common complications in food-borne outbreak investigations. We illustrate the implementation and performance of our method on a Salmonella Thompson outbreak in the Netherlands in 2012. Our method is shown to perform better than the standard logistic regression approach with respect to earlier identification of contaminated food products. It also allows relatively easy implementation of otherwise complex methodological issues.
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http://dx.doi.org/10.1177/0962280217747311DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6448052PMC
April 2019

A summary index for antimicrobial resistance in food animals in the Netherlands.

BMC Vet Res 2017 Oct 24;13(1):305. Epub 2017 Oct 24.

National Institute for Public Health and the Environment, PO Box 1, 3720 BA, Bilthoven, the Netherlands.

Background: The Dutch government has set targets for reduction of antimicrobial usage in food animals, stipulating a 50% reduction in usage (on a weight basis) in 2013 as compared to 2009 and a 70% decrease in 2015. A monitoring program has been instituted to evaluate the impact on antimicrobial resistance (AMR). The Dutch Ministry of Public Health Welfare and Sports has expressed the need for a summary index to present the results of the monitoring data concisely to policy makers.

Methods: We use data on AMR in bacteria from randomly collected samples from broiler chickens, fattening pigs, veal calves and dairy cows. Escherichia coli was selected for resistance monitoring because they are intrinsically susceptible to the antibiotics included in the test panel (ciprofloxacin, cefotaxime, tetracycline and ampicillin) and they are present in all samples, which facilitates proper randomization and trend analysis. The AMR summary index was calculated for each animal species as a weighted average over the four antibiotics, taking into account their clinical relevance. Weights were obtained by conjoint analysis, a pairwise comparison study involving infectious diseases professionals with clinical and public health backgrounds, with data analysis by conditional logistic regression. The AMR summary index was then computed by Monte Carlo simulation, accounting for sampling and regression uncertainty.

Results: The highest weights (0.35) were given to ciprofloxacin and cefotaxime followed by ampicillin (0.23) and tetracycline (0.07). Throughout the years, the AMR index was highest in broiler chickens, followed by pigs and veal calves, while the lowest values were consistently recorded in dairy cows. In all animal species, the index in 2014 was significantly lower than in 2009.

Conclusions: We demonstrate that high-dimensional data on surveillance of antimicrobial resistance can be summarized in an index for evaluating trends between and within food animal species by a process involving decision makers and scientists to select and weight the most relevant antibiotics.
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http://dx.doi.org/10.1186/s12917-017-1216-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5655976PMC
October 2017

Infectious reactivation of cytomegalovirus explaining age- and sex-specific patterns of seroprevalence.

PLoS Comput Biol 2017 Sep 26;13(9):e1005719. Epub 2017 Sep 26.

Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands.

Human cytomegalovirus (CMV) is a herpes virus with poorly understood transmission dynamics. Person-to-person transmission is thought to occur primarily through transfer of saliva or urine, but no quantitative estimates are available for the contribution of different infection routes. Using data from a large population-based serological study (n = 5,179), we provide quantitative estimates of key epidemiological parameters, including the transmissibility of primary infection, reactivation, and re-infection. Mixture models are fitted to age- and sex-specific antibody response data from the Netherlands, showing that the data can be described by a model with three distributions of antibody measurements, i.e. uninfected, infected, and infected with increased antibody concentration. Estimates of seroprevalence increase gradually with age, such that at 80 years 73% (95%CrI: 64%-78%) of females and 62% (95%CrI: 55%-68%) of males are infected, while 57% (95%CrI: 47%-67%) of females and 37% (95%CrI: 28%-46%) of males have increased antibody concentration. Merging the statistical analyses with transmission models, we find that models with infectious reactivation (i.e. reactivation that can lead to the virus being transmitted to a novel host) fit the data significantly better than models without infectious reactivation. Estimated reactivation rates increase from low values in children to 2%-4% per year in women older than 50 years. The results advance a hypothesis in which transmission from adults after infectious reactivation is a key driver of transmission. We discuss the implications for control strategies aimed at reducing CMV infection in vulnerable groups.
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http://dx.doi.org/10.1371/journal.pcbi.1005719DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5630159PMC
September 2017

Predicting the risk of Lyme borreliosis after a tick bite, using a structural equation model.

PLoS One 2017 24;12(7):e0181807. Epub 2017 Jul 24.

Centre for Infectious Disease Control Netherlands, National Institute for Public Health and the Environment, Bilthoven, the Netherlands.

Background: Understanding and quantification of the risk of Lyme borreliosis after a tick bite can aid development of prevention strategies against Lyme borreliosis.

Methods: We used 3,525 single tick bite reports from three large prospective studies on the transmission risk of tick-borne pathogens to humans, with 50 reports of Lyme borreliosis during the follow-up period, among 1,973 reports with known outcome. A structural equation model was applied to estimate the risk of Lyme borreliosis after a tick bite, and quantify the influence of: developmental stage of the tick, detection of Borrelia burgdorferi s.l. DNA in the tick by PCR, tick engorgement, patient-estimated duration of tick attachment, and patient age.

Results: The overall risk of developing Lyme borreliosis after a tick bite was 2.6% (95%CI 1.4-5.1). The risk increased with: - Tick engorgement: 1.4% (95%CI 0.7%-2.3%) for low engorgement to 5.5% (95%CI 2.8%-9.2%) for substantially engorged ticks;- Rising patient-estimated tick attachment duration: 2.0% (95%CI 1.3%-2.8%) after <12 hours, to 5.2% (95%CI 3.0%-8.9%) after ≥4 days;- Detection of Borrelia burgdorferi s.l. DNA in ticks: 6.7% (95%CI 3.6%-13.5%), versus 1.4% (95%CI 0.7%-2.9%) when ticks tested negative.The highest observed risk of Lyme borreliosis was 14.4% (95%CI 6.8%-24.6%) after one tick bite of a substantially engorged tick that tested positive for Borrelia burgdorferi s.l. DNA, which corresponds to one new case of Lyme borreliosis per 7 (95%CI 4-15) of such tick bites.

Conclusions: An individual's risk of Lyme borreliosis after a tick bite can be predicted with tick engorgement, patient-estimated duration of tick attachment, and detection of Borrelia burgdorferi s.l. DNA in the tick.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0181807PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5524385PMC
September 2017

Estimating the prevalence of 26 health-related indicators at neighbourhood level in the Netherlands using structured additive regression.

Int J Health Geogr 2017 07 1;16(1):23. Epub 2017 Jul 1.

National Institute for Public Health and the Environment - RIVM, PO Box 1, 3720BA, Bilthoven, The Netherlands.

Background: Local policy makers increasingly need information on health-related indicators at smaller geographic levels like districts or neighbourhoods. Although more large data sources have become available, direct estimates of the prevalence of a health-related indicator cannot be produced for neighbourhoods for which only small samples or no samples are available. Small area estimation provides a solution, but unit-level models for binary-valued outcomes that can handle both non-linear effects of the predictors and spatially correlated random effects in a unified framework are rarely encountered.

Methods: We used data on 26 binary-valued health-related indicators collected on 387,195 persons in the Netherlands. We associated the health-related indicators at the individual level with a set of 12 predictors obtained from national registry data. We formulated a structured additive regression model for small area estimation. The model captured potential non-linear relations between the predictors and the outcome through additive terms in a functional form using penalized splines and included a term that accounted for spatially correlated heterogeneity between neighbourhoods. The registry data were used to predict individual outcomes which in turn are aggregated into higher geographical levels, i.e. neighbourhoods. We validated our method by comparing the estimated prevalences with observed prevalences at the individual level and by comparing the estimated prevalences with direct estimates obtained by weighting methods at municipality level.

Results: We estimated the prevalence of the 26 health-related indicators for 415 municipalities, 2599 districts and 11,432 neighbourhoods in the Netherlands. We illustrate our method on overweight data and show that there are distinct geographic patterns in the overweight prevalence. Calibration plots show that the estimated prevalences agree very well with observed prevalences at the individual level. The estimated prevalences agree reasonably well with the direct estimates at the municipal level.

Conclusions: Structured additive regression is a useful tool to provide small area estimates in a unified framework. We are able to produce valid nationwide small area estimates of 26 health-related indicators at neighbourhood level in the Netherlands. The results can be used for local policy makers to make appropriate health policy decisions.
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http://dx.doi.org/10.1186/s12942-017-0097-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5493876PMC
July 2017

Determinants of Rotavirus Transmission: A Lag Nonlinear Time Series Analysis.

Epidemiology 2017 07;28(4):503-513

From the aCenter for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands; bJulius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands; and cDepartment of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands.

Rotavirus is a common viral infection among young children. As in many countries, the infection dynamics of rotavirus in the Netherlands are characterized by an annual winter peak, which was notably low in 2014. Previous study suggested an association between weather factors and both rotavirus transmission and incidence. From epidemic theory, we know that the proportion of susceptible individuals can affect disease transmission. We investigated how these factors are associated with rotavirus transmission in the Netherlands, and their impact on rotavirus transmission in 2014. We used available data on birth rates and rotavirus laboratory reports to estimate rotavirus transmission and the proportion of individuals susceptible to primary infection. Weather data were directly available from a central meteorological station. We developed an approach for detecting determinants of seasonal rotavirus transmission by assessing nonlinear, delayed associations between each factor and rotavirus transmission. We explored relationships by applying a distributed lag nonlinear regression model with seasonal terms. We corrected for residual serial correlation using autoregressive moving average errors. We inferred the relationship between different factors and the effective reproduction number from the most parsimonious model with low residual autocorrelation. Higher proportions of susceptible individuals and lower temperatures were associated with increases in rotavirus transmission. For 2014, our findings suggest that relatively mild temperatures combined with the low proportion of susceptible individuals contributed to lower rotavirus transmission in the Netherlands. However, our model, which overestimated the magnitude of the peak, suggested that other factors were likely instrumental in reducing the incidence that year.
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http://dx.doi.org/10.1097/EDE.0000000000000654DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5457827PMC
July 2017

A Bivariate Mixture Model for Natural Antibody Levels to Human Papillomavirus Types 16 and 18: Baseline Estimates for Monitoring the Herd Effects of Immunization.

PLoS One 2016 18;11(8):e0161109. Epub 2016 Aug 18.

Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands.

Post-vaccine monitoring programs for human papillomavirus (HPV) have been introduced in many countries, but HPV serology is still an underutilized tool, partly owing to the weak antibody response to HPV infection. Changes in antibody levels among non-vaccinated individuals could be employed to monitor herd effects of immunization against HPV vaccine types 16 and 18, but inference requires an appropriate statistical model. The authors developed a four-component bivariate mixture model for jointly estimating vaccine-type seroprevalence from correlated antibody responses against HPV16 and -18 infections. This model takes account of the correlation between HPV16 and -18 antibody concentrations within subjects, caused e.g. by heterogeneity in exposure level and immune response. The model was fitted to HPV16 and -18 antibody concentrations as measured by a multiplex immunoassay in a large serological survey (3,875 females) carried out in the Netherlands in 2006/2007, before the introduction of mass immunization. Parameters were estimated by Bayesian analysis. We used the deviance information criterion for model selection; performance of the preferred model was assessed through simulation. Our analysis uncovered elevated antibody concentrations in doubly as compared to singly seropositive individuals, and a strong clustering of HPV16 and -18 seropositivity, particularly around the age of sexual debut. The bivariate model resulted in a more reliable classification of singly and doubly seropositive individuals than achieved by a combination of two univariate models, and suggested a higher pre-vaccine HPV16 seroprevalence than previously estimated. The bivariate mixture model provides valuable baseline estimates of vaccine-type seroprevalence and may prove useful in seroepidemiologic assessment of the herd effects of HPV vaccination.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0161109PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4990197PMC
July 2017

Improved correlation of human Q fever incidence to modelled C. burnetii concentrations by means of an atmospheric dispersion model.

Int J Health Geogr 2015 Apr 1;14:14. Epub 2015 Apr 1.

Centre for Infectious Disease Control (CIb), National Institute for Public Health and the Environment (RIVM), P.O. Box 1, 3720, BA, Bilthoven, The Netherlands.

Background: Atmospheric dispersion models (ADMs) may help to assess human exposure to airborne pathogens. However, there is as yet limited quantified evidence that modelled concentrations are indeed associated to observed human incidence.

Methods: We correlated human Q fever (caused by the bacterium Coxiella burnetii) incidence data in the Netherlands to modelled concentrations from three spatial exposure models: 1) a NULL model with a uniform concentration distribution, 2) a DISTANCE model with concentrations proportional to the distance between the source and residential addresses of patients, and 3) concentrations modelled by an ADM using three simple emission profiles. We used a generalized linear model to correlate the observed incidences to modelled concentrations and validated it using cross-validation.

Results: ADM concentrations generally correlated the best to the incidence data. The DISTANCE model always performed significantly better than the NULL model. ADM concentrations based on wind speeds exceeding threshold values of 0 and 2 m/s performed better than those based on 4 or 6 m/s. This might indicate additional exposure to bacteria originating from a contaminated environment.

Conclusions: By adding meteorological information the correlation between modelled concentration and observed incidence improved, despite using three simple emission profiles. Although additional information is needed - especially regarding emission data - these results provide a basis for the use of ADMs to predict and to visualize the spread of airborne pathogens during livestock, industry and even bio-terroristic related outbreaks or releases to a surrounding human population.
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http://dx.doi.org/10.1186/s12942-015-0003-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4440286PMC
April 2015

Estimating seroprevalence of human papillomavirus type 16 using a mixture model with smoothed age-dependent mixing proportions.

Epidemiology 2015 Jan;26(1):8-16

aCentre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands; bDepartment of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands; cDepartment of Statistics, Mathematical Modelling and Data Logistics, National Institute for Public Health and the Environment, Bilthoven, The Netherlands; and dHubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA.

Background: The presence in serum of antibodies to viral antigens is generally considered a well-defined marker of past infection or vaccination. However, analyses of serological data that use a cut-off value to classify individuals as seropositive are prone to misclassification bias, in particular when studying infections with a weak serological response, such as the sexually transmitted human papillomavirus (HPV).

Methods: We analyzed the serological concentrations of HPV type 16 (HPV16) antibodies in the general Dutch population in 2006-2007, before the introduction of mass vaccination against HPV. We used a 2-component mixture model to represent persons who were seronegative or seropositive for HPV16. Component densities were assumed to be log-normally distributed, with parameters possibly dependent on sex. The age-dependent mixing proportions were smoothed using penalized splines to obtain a flexible seroprevalence profile.

Results: Our results suggest that HPV16 seropositivity is associated with higher antibody concentrations in women as compared with men. Seroprevalence shows an increase starting from adolescence in men and women alike, coinciding with the age of sexual debut. Seroprevalence stabilizes in men around age 40, whereas it has a decreasing trend from age 50 onwards in women. Analyses that rely on a cut-off value to classify persons as seropositive yield substantially different seroprevalence profiles, leading to a qualitatively different interpretation of HPV16 infection dynamics.

Conclusions: Our results provide a benchmark for examining the effect of HPV16 vaccination in future serological surveys. Our method may prove useful for estimating seroprevalence of other infections with a weak serological response.
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http://dx.doi.org/10.1097/EDE.0000000000000196DOI Listing
January 2015

Loss of multi-epitope specificity in memory CD4(+) T cell responses to B. pertussis with age.

PLoS One 2013 31;8(12):e83583. Epub 2013 Dec 31.

Centre for Immunology of Infectious Diseases and Vaccines, National Institute for Public Health and the Environment, Bilthoven, The Netherlands.

Pertussis is still occurring in highly vaccinated populations, affecting individuals of all ages. Long-lived Th1 CD4(+) T cells are essential for protective immunity against pertussis. For better understanding of the limited immunological memory to Bordetella pertussis, we used a panel of Pertactin and Pertussis toxin specific peptides to interrogate CD4(+) T cell responses at the epitope level in a unique cohort of symptomatic pertussis patients of different ages, at various time intervals after infection. Our study showed that pertussis epitope-specific T cell responses contained Th1 and Th2 components irrespective of the epitope studied, time after infection, or age. In contrast, the breadth of the pertussis-directed CD4(+) T cell response seemed dependent on age and closeness to infection. Multi-epitope specificity long-term after infection was lost in older age groups. Detailed knowledge on pertussis specific immune mechanisms and their insufficiencies is important for understanding resurgence of pertussis in highly vaccinated populations.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0083583PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3877060PMC
August 2014

Lung cancer risk and past exposure to emissions from a large steel plant.

J Environ Public Health 2013 13;2013:684035. Epub 2013 Nov 13.

National Institute for Public Health and the Environment, P.O. Box 1, 3720 BA Bilthoven, The Netherlands.

We studied the spatial distribution of cancer incidence rates around a large steel plant and its association with historical exposure. The study population was close to 600,000. The incidence data was collected for 1995-2006. From historical emission data the air pollution concentrations for polycyclic aromatic hydrocarbons (PAH) and metals were modelled. Data were analyzed using Bayesian hierarchical Poisson regression models. The standardized incidence ratio (SIR) for lung cancer was up to 40% higher than average in postcodes located in two municipalities adjacent to the industrial area. Increased incidence rates could partly be explained by differences in socioeconomic status (SES). In the highest exposure category (approximately 45,000 inhabitants) a statistically significant increased relative risk (RR) of 1.21 (1.01-1.43) was found after adjustment for SES. The elevated RRs were similar for men and women. Additional analyses in a subsample of the population with personal smoking data from a recent survey suggested that the observed association between lung cancer and plant emission, after adjustment for SES, could still be caused by residual confounding. Therefore, we cannot indisputably conclude that past emissions from the steel plant have contributed to the increased risk of lung cancer.
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http://dx.doi.org/10.1155/2013/684035DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3845394PMC
July 2014

Vaccine uptake determinants in The Netherlands.

Eur J Public Health 2014 Apr 26;24(2):304-9. Epub 2013 Mar 26.

1 Department of Epidemiology and Surveillance (EPI), Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands.

Background: Combining existing data on background characteristics with data from immunization registers might give insight into determinants of vaccine uptake, which can help to improve communication strategies and invitation policy of National Immunisation Programmes.

Methods: The study population consisted of children born in 2005 as registered in the Dutch national immunization register Præventis. A hierarchical logistic regression model was used to quantify associations between individual vaccination status and proxy variables for ethnic background (individual level), socio-economic status (postcode level) and religious objection to vaccination (municipal level).

Results: Most children whose both parents were not born in The Netherlands had a somewhat lower full vaccine uptake, for example, children whose both parents were born in Turkey [odds ratio = 0.7 (0.6-0.8)] or in Morocco [odds ratio = 0.8 (0.7-0.9)]. The partial uptake was also relatively high (3.7-8.0%) compared with children whose both parents were born in The Netherlands (3.1%). Municipalities with higher religious objection to vaccination and postcode areas with lower socio-economic status were also associated with a lower full uptake.

Conclusions: Despite the high vaccination coverage in The Netherlands, we were able to identify determinants of vaccine uptake by combining existing data sets. This might be an example for other countries. The impact of ethnic background and socio-economic status is not as well known in The Netherlands as the effect of religious objection to vaccination, and deserves more attention. Groups that have a relatively high partial uptake deserve special attention because they do not reject vaccination in general.
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http://dx.doi.org/10.1093/eurpub/ckt042DOI Listing
April 2014

Smooth incidence maps give valuable insight into Q fever outbreaks in The Netherlands.

Geospat Health 2012 Nov;7(1):127-34

Centre for Infectious Disease Control, National Institute for Public Health and the Environment, PO Box 1, 3720 BA Bilthoven, The Netherlands.

From 2007 through 2009, The Netherlands faced large outbreaks of human Q fever. Control measures focused primarily on dairy goat farms because these were implicated as the main source of infection for the surrounding population. However, in other countries, outbreaks have mainly been associated with non-dairy sheep and The Netherlands has many more sheep than goats. Therefore, a public discussion arose about the possible role of non-dairy (meat) sheep in the outbreaks. To inform decision makers about the relative importance of different infection sources, we developed accurate and high-resolution incidence maps for detection of Q fever hot spots. In the high incidence area in the south of the country, full postal codes of notified Q fever patients with onset of illness in 2009, were georeferenced. Q fever cases (n = 1,740) were treated as a spatial point process. A 500 x 500 m grid was imposed over the area of interest. The number of cases and the population number were counted in each cell. The number of cases was modelled as an inhomogeneous Poisson process where the underlying incidence was estimated by 2-dimensional P-spline smoothing. Modelling of numbers of Q fever cases based on residential addresses and population size produced smooth incidence maps that clearly showed Q fever hotspots around infected dairy goat farms. No such increased incidence was noted around infected meat sheep farms. We conclude that smooth incidence maps of human notifications give valuable information about the Q fever epidemic and are a promising method to provide decision support for the control of other infectious diseases with an environmental source.
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http://dx.doi.org/10.4081/gh.2012.111DOI Listing
November 2012

Mortality attributable to 9 common infections: significant effect of influenza A, respiratory syncytial virus, influenza B, norovirus, and parainfluenza in elderly persons.

J Infect Dis 2012 Sep 21;206(5):628-39. Epub 2012 Jun 21.

Centre for Infectious Disease Control Netherlands, National Institute for Public Health and the Environment, PO Box 1, 3720 BA Bilthoven, The Netherlands.

Background: Because there may be substantial hidden mortality caused by common seasonal pathogens, we estimated the number of deaths in elderly persons attributable to viruses and bacteria for which robust weekly laboratory surveillance data were available.

Methods: On weekly time series (1999-2007) we used regression models to associate total death counts in individuals aged 65-74, 75-84, and ≥85 years (a population of 2.5 million) with pathogen circulation-influenza A (season-specific), influenza B, respiratory syncytial virus (RSV), parainfluenza, enterovirus, rotavirus, norovirus, Campylobacter, and Salmonella-adjusted for extreme outdoor temperatures.

Results: Influenza A and RSV were significantly (P < .05) associated with mortality in all studied age groups; influenza B and parainfluenza were additionally associated in those aged ≥75 years, and norovirus was additionally associated in those aged ≥85 years. The proportions of deaths attributable to seasonal viruses were 6.8% (≥85 years), 4.4% (75-84 years), and 1.4% (65-74 years), but with great variations between years. Influenza occasionally showed lower impact than some of the other viruses.

Conclusions: The number of different pathogens associated with mortality in the older population increases with increasing age. Besides influenza A and RSV, influenza B, parainfluenza and norovirus may also contribute substantially to elderly mortality.
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http://dx.doi.org/10.1093/infdis/jis415DOI Listing
September 2012

Mumps vaccine effectiveness in primary schools and households, the Netherlands, 2008.

Vaccine 2012 Apr 27;30(19):2999-3002. Epub 2012 Feb 27.

Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, the Netherlands.

To estimate the mumps vaccine effectiveness (VE) during a large genotype D mumps outbreak, we conducted a cross-sectional study in eight primary schools and associated households in the Netherlands. Questionnaires were used to collect information on the occurrence of mumps. Multivariate analyses were used to estimate VE. Among schoolchildren we estimated the VE against mumps. Among household contacts where the schoolchild was the index case we estimated the VE against mumps and against mumps infectiousness. In total 1175 children and 2281 household contacts participated in the study. The mumps attack rate among schoolchildren was 17%. The mumps VE in schoolchildren was 92% [95% confidence interval (CI) 83-96%] and 93% [85-97%] for one and two doses of the measles, mumps, rubella (MMR) vaccine, respectively. The adjusted mumps VE among household contacts was 67% [65-95%] and 11% [-4 to 88%] against mumps and mumps infectiousness, respectively. Our study indicates that the mumps component of the MMR vaccine offered adequate protection against mumps among schoolchildren. The relatively low VE among household contacts is of concern.
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http://dx.doi.org/10.1016/j.vaccine.2012.02.035DOI Listing
April 2012

New statistical technique for analyzing MIC-based susceptibility data.

Antimicrob Agents Chemother 2012 Mar 9;56(3):1557-63. Epub 2012 Jan 9.

Expertise Centre for Methodology and Information Services, National Institute for Public Health and the Environment, Bilthoven, The Netherlands.

Seventeen laboratories participated in a cooperative study to validate the regional susceptibility testing of Neisseria gonorrhoeae in The Netherlands. International reference strains were distributed. Each laboratory determined the MICs of ciprofloxacin, penicillin, and tetracycline, for each strain by Etest. To explore a more transparent assessment of quality and comparability, a statistical regression model was fitted to the data that accounted for the censoring of the MICs. The mean MICs found by all of the laboratories except three were closer than one 2-fold dilution step to the overall mean, and the mean MICs of each antimicrobial agent were close to the MICs for the international reference strains. This approach provided an efficient tool to analyze the performance of the Dutch decentralized gonococcal resistance monitoring system and confirmed good and comparable standards.
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http://dx.doi.org/10.1128/AAC.05777-11DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3294928PMC
March 2012

Effect of ammonia in cigarette tobacco on nicotine absorption in human smokers.

Food Chem Toxicol 2011 Dec 6;49(12):3025-30. Epub 2011 Oct 6.

National Institute of Public Health and the Environment (RIVM), PO Box 1, 3720 BA Bilthoven, The Netherlands.

The function of ammonia as tobacco additive is subject of scientific debate. It is argued that ammonia, by increasing the proportion of free nicotine, increases the absorption of nicotine in smokers. As a result of the addition of ammonia to cigarettes, smokers get exposed to higher internal nicotine doses and become more addicted to the product. On two occasions, the nicotine absorption in blood was measured after smoking a commercial cigarette of either brand 1 or brand 2, which differed 3.8-fold in ammonium salt content. Using a standardized smoking regime (six puffs, 30 s puff interval, 7 s breath hold before exhalation), 51 regular smokers smoked brand 1 (Caballero Smooth Flavor; 0.89 mg ammonium per gram tobacco) and brand 2 (Gauloise Brunes; 3.43 mg ammonium per gram tobacco). Puff volumes and cardiovascular parameters were monitored during and following smoking, respectively. Measurement of serum nicotine level in the blood samples collected over time following smoking of the two brands, showed that total amount of nicotine absorbed did not differ between the two brands. Present results demonstrate that smoking tobacco containing a higher amount of the tobacco additive ammonium does not increase the absorption of nicotine in the smoker's body.
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http://dx.doi.org/10.1016/j.fct.2011.09.037DOI Listing
December 2011

Pertussis in infancy and the association with respiratory and cognitive disorders at toddler age.

Vaccine 2011 Oct 9;29(46):8275-8. Epub 2011 Sep 9.

Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, The Netherlands.

Pertussis in unvaccinated infants can run a severe course and is often accompanied by complications. In this pilot study, we studied whether there is an association between pertussis hospitalisation in infancy and, respiratory symptoms, growth and cognitive development in early childhood. A group of 89 children aged 13-45 months and hospitalised for laboratory confirmed pertussis within the first six months of their life were compared with 172 children without a history of pertussis. Risk ratios (RR) with 95% confidence intervals (CI) of the association between health outcomes and pertussis in infancy were calculated. Weight-for-length and length-for-age z-scores were calculated to investigate growth. Van Wiechen scores were compared to study cognitive development. Children with a history of pertussis in infancy had a greater chance on "asthma symptoms" (RR 2.8 95%CI 1.1-7.0) on toddler age and were more likely to report "respiratory infections" (RR 3.3 95%CI 1.6-6.6). In addition, children with a history of pertussis in infancy had significantly lower weight-for-height in the first 40 months of life. No significant differences in cognitive development were found. We found an association between severe pertussis in infancy and respiratory symptoms on toddler age. The mechanisms that may underlie this association require further investigation.
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http://dx.doi.org/10.1016/j.vaccine.2011.08.112DOI Listing
October 2011