Publications (25) View all
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Article: The impact of demographic change on the estimated future burden of infectious diseases: examples from hepatitis B and seasonal influenza in the Netherlands.
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ABSTRACT: BACKGROUND: For accurate estimation of the future burden of communicable diseases, the dynamics of the population at risk -- namely population growth and population ageing -- need to be taken into account. Accurate burden estimates are necessary for informing policy-makers regarding the planning of vaccination and other control, intervention, and prevention measures. Our aim was to qualitatively explore the impact of population ageing on the estimated future burden of seasonal influenza and hepatitis B virus (HBV) infection in the Netherlands, in the period 2000--2030. METHODS: Population-level disease burden was quantified using the disability-adjusted life years (DALY) measure applied to all health outcomes following acute infection. We used national notification data, pre-defined disease progression models, and a simple model of demographic dynamics to investigate the impact of population ageing on the burden of seasonal influenza and HBV. Scenario analyses were conducted to explore the potential impact of intervention-associated changes in incidence rates. RESULTS: Including population dynamics resulted in increasing burden over the study period for influenza, whereas a relatively stable future burden was predicted for HBV. For influenza, the increase in DALYs was localised within YLL for the oldest age-groups (55 and older), and for HBV the effect of longer life expectancy in the future was offset by a reduction in incidence in the age-groups most at risk of infection. For both infections, the predicted disease burden was greater than if a static demography was assumed: 1.0 (in 2000) to 2.3-fold (in 2030) higher DALYs for influenza; 1.3 (in 2000) to 1.5-fold (in 2030) higher for HBV. CONCLUSIONS: There are clear, but diverging effects of an ageing population on the estimated disease burden of influenza and HBV in the Netherlands. Replacing static assumptions with a dynamic demographic approach appears essential for deriving realistic burden estimates for informing health policy.BMC Public Health 12/2012; 12(1):1046. · 2.00 Impact Factor -
Article: Monitoring van vaccinatiegraad en bijwerkingen van het HPV-vaccinatieprogramma.
Infectieziekten Bulletin. 10/2012; 23(8):259-64. -
Article: Vaccine uptake determinants in The Netherlands.
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ABSTRACT: 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.The European Journal of Public Health 03/2013; · 2.73 Impact Factor -
Article: Acceptance of vaccination during pregnancy: experience with 2009 influenza A (H1N1) in the Netherlands.
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ABSTRACT: In 2009, the Dutch government advised pregnant women to get vaccinated against influenza A (H1N1). A study was set up to gain insight into vaccination coverage and reasons why pregnant women seek vaccination or not. We invited 14,529 pregnant women to complete an internet survey on vaccination during pregnancy in general and against 2009 influenza A (H1N1). Differences in background characteristics between unvaccinated and vaccinated women were investigated. Prediction analyses were carried out to determine which survey statement had the greatest impact on vaccination status or intention to get vaccinated during pregnancy. Of the 2993 included respondents, 63% reported to be vaccinated against 2009 influenza A (H1N1). Vaccination coverage was higher among older birth cohorts, women who had been pregnant before, women with underlying medical conditions, and women who reported no defined 'life philosophy'. Protection of the child (after birth), the government's advice and possible harmful effects of the vaccine for the unborn child had the greatest predictive value for vaccination status. With regards vaccination during future pregnancies, 39% had a positive intention to obtain vaccination and 45% were neutral. The government's advice was the strongest predictor for intention. Furthermore, women expressed concern over lack of sufficient knowledge about vaccine safety. A considerable number of pregnant women in the Netherlands reported to be vaccinated against 2009 influenza A (H1N1). The challenge for the government in the future will be to provide pregnant women and health care professionals with sufficient and clear information about disease severity and the benefits and safety of vaccination.Vaccine 02/2012; 30(18):2892-9. · 3.77 Impact Factor -
Article: Comparing pandemic to seasonal influenza mortality: moderate impact overall but high mortality in young children.
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ABSTRACT: We assessed the severity of the 2009 influenza pandemic by comparing pandemic mortality to seasonal influenza mortality. However, reported pandemic deaths were laboratory-confirmed - and thus an underestimation - whereas seasonal influenza mortality is often more inclusively estimated. For a valid comparison, our study used the same statistical methodology and data types to estimate pandemic and seasonal influenza mortality. We used data on all-cause mortality (1999-2010, 100% coverage, 16.5 million Dutch population) and influenza-like-illness (ILI) incidence (0.8% coverage). Data was aggregated by week and age category. Using generalized estimating equation regression models, we attributed mortality to influenza by associating mortality with ILI-incidence, while adjusting for annual shifts in association. We also adjusted for respiratory syncytial virus, hot/cold weather, other seasonal factors and autocorrelation. For the 2009 pandemic season, we estimated 612 (range 266-958) influenza-attributed deaths; for seasonal influenza 1,956 (range 0-3,990). 15,845 years-of-life-lost were estimated for the pandemic; for an average seasonal epidemic 17,908. For 0-4 yrs of age the number of influenza-attributed deaths during the pandemic were higher than in any seasonal epidemic; 77 deaths (range 61-93) compared to 16 deaths (range 0-45). The ≥75 yrs of age showed a far below average number of deaths. Using pneumonia/influenza and respiratory/cardiovascular instead of all-cause deaths consistently resulted in relatively low total pandemic mortality, combined with high impact in the youngest age category. The pandemic had an overall moderate impact on mortality compared to 10 preceding seasonal epidemics, with higher mortality in young children and low mortality in the elderly. This resulted in a total number of pandemic deaths far below the average for seasonal influenza, and a total number of years-of-life-lost somewhat below average. Comparing pandemic and seasonal influenza mortality as in our study will help assessing the worldwide impact of the 2009 pandemic.PLoS ONE 01/2012; 7(2):e31197. · 4.09 Impact Factor
