Christiaan Marais

University of Antwerp, Antwerpen, VLG, Belgium

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Publications (6)17.89 Total impact

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    ABSTRACT: To identify key determinants explaining country-year variations in antibiotic use and resistance. Ambulatory antibiotic use data [in defined daily doses per 1000 inhabitants per day (DIDs)] for 19 European countries from 1999 to 2007 were collected, along with 181 variables describing countries in terms of their agriculture, culture, demography, disease burden, education, healthcare organization and socioeconomics. After assessing data availability, overlap and relevance, multiple imputation generalized estimating equations were applied with a stepwise selection procedure to select significant determinants of global antibiotic use (expressed in DIDs), relative use of subgroups (amoxicillin and co-amoxiclav) and resistance of Escherichia coli and Streptococcus pneumoniae. Relative humidity, healthcare expenditure proportional to gross domestic product, feelings of distrust, proportion of population aged >65 years and availability of treatment guidelines were associated with higher total antibiotic use expressed in DIDs. Restrictions on marketing activities towards prescribers, population density, number of antibiotics, educational attainment and degree of atheism were associated with a lower number of total DIDs used. Relative prescribing of amoxicillin and co-amoxiclav was mainly determined by healthcare system choices [e.g. general practitioner (GP) registration and restricted marketing]. Specific antibiotic use was found to be a significant determinant of resistance for some but not all drug/organism combinations. Incentives to stimulate GP gatekeeping were associated with lower levels of resistance, and life expectancy at age 65+ and atheism were associated with more resistance. Myriad factors influence antibiotic use and resistance at the country level and an important part of these can be modified by policy choices.
    Journal of Antimicrobial Chemotherapy 09/2013; · 5.34 Impact Factor
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    ABSTRACT: SUMMARY Varicella-zoster virus causes chickenpox (CP) and after reactivation herpes zoster (HZ). Vaccines are available against both diseases warranting an assessment of the pre-vaccination burden of disease. We collected data from relevant Belgian databases and performed five surveys of CP and HZ patients. The rates at which a general practitioner is visited at least once for CP and HZ are 346 and 378/100 000 person-years, respectively. The average CP and HZ hospitalization rates are 5·3 and 14·2/100 000 person-years respectively. The direct medical cost for HZ is about twice as large as the direct medical cost for CP. The quality-adjusted life years lost for ambulatory CP patients consulting a physician is more than double that of those not consulting a physician (0·010 vs. 0·004). In conclusion, both diseases cause a substantial burden in Belgium.
    Epidemiology and Infection 01/2012; 140(11):2096-109. · 2.87 Impact Factor
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    ABSTRACT: Dengue is a vector-borne disease recognized as the major arbovirose with four immunologically distant dengue serotypes coexisting in many endemic areas. Several mathematical models have been developed to understand the transmission dynamics of dengue, including the role of cross-reactive antibodies for the four different dengue serotypes. We aimed to review deterministic models of dengue transmission, in order to summarize the evolution of insights for, and provided by, such models, and to identify important characteristics for future model development. We identified relevant publications using PubMed and ISI Web of Knowledge, focusing on mathematical deterministic models of dengue transmission. Model assumptions were systematically extracted from each reviewed model structure, and were linked with their underlying epidemiological concepts. After defining common terms in vector-borne disease modelling, we generally categorised fourty-two published models of interest into single serotype and multiserotype models. The multi-serotype models assumed either vector-host or direct host-to-host transmission (ignoring the vector component). For each approach, we discussed the underlying structural and parameter assumptions, threshold behaviour and the projected impact of interventions. In view of the expected availability of dengue vaccines, modelling approaches will increasingly focus on the effectiveness and cost-effectiveness of vaccination options. For this purpose, the level of representation of the vector and host populations seems pivotal. Since vector-host transmission models would be required for projections of combined vaccination and vector control interventions, we advocate their use as most relevant to advice health policy in the future. The limited understanding of the factors which influence dengue transmission as well as limited data availability remain important concerns when applying dengue models to real-world decision problems.
    PLoS ONE 01/2012; 7(11):e49085. · 3.73 Impact Factor
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    ABSTRACT: To assess the cost-effectiveness of vaccinating all or subgroups of adults aged 60 to 85 years against herpes zoster. A deterministic compartmental static model was developed (in freeware R), in which cohorts can acquire herpes zoster according to their age in years. Surveys and database analyses were conducted to obtain as much as possible Belgian age-specific estimates for input parameters. Direct costs and Quality-Adjusted Life-Year (QALY) losses were estimated as a function of standardised Severity Of Illness (SOI) scores (i.e. as a function of the duration and severity of herpes zoster disease). Uncertainty about the average SOI score for a person with herpes zoster, the duration of protection from the vaccine, and the population that can benefit from the vaccine, exerts a major impact on the results: under assumptions least in favour of vaccination, vaccination is not cost-effective (i.e. incremental cost per QALY gained >€48,000 for all ages considered) at the expected vaccine price of €90 per dose. At the same price, but under assumptions most in favour of vaccination, vaccination is found to be cost-effective (i.e. incremental cost per QALY gained <€5500 for all ages considered). Vaccination of age cohort 60 seems more cost-effective than vaccination of any older age cohort in Belgium. If the vaccine price per dose drops to €45, HZ vaccination of adults aged 60-64 years is likely to be cost-effective in Belgium, even under assumptions least in favour of vaccination. Unlike previous studies, our analysis acknowledged major methodological and model uncertainties simultaneously and presented outcomes for 26 different target ages at which vaccination can be considered (ages 60-85).
    Vaccine 11/2011; 30(3):675-84. · 3.77 Impact Factor
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    ABSTRACT: To explore the impact of applying different non-standardized analytical choices for quality of life measurement to obtain quality-adjusted life years (QALYs). In addition to more widely discussed issues such as the choice of instrument (e.g. EQ-5D or SF-6D?) researchers must also choose between different recall periods, scoring algorithms and interpolations between points of measurement. A prospective survey was made among 114 Belgian patients with acute hepatitis A illness. Using non-parametric tests and generalized linear models (GLM's), we compared four different methods to estimate QALY losses, two based on the EQ-5D (administered during the period of illness without recall period) and two based on the SF-6D (administered after illness with 4 weeks recall period). We found statistically significant differences between all methods, with the non-parametric SF-6D-based method yielding the highest median QALY impact (0.032 QALYs). This is more than five times as high as the EQ-5D-based method with linear health improvement, which yields the lowest median QALY impact (0.006 QALYs). Economic evaluations of health care technologies predominantly use QALYs to quantify health benefits. Non-standardised analytical choices can have a decision-changing impact on cost-effectiveness results, particularly if morbidity takes up a substantial part of the total QALY loss. Yet these choices are rarely subjected to sensitivity analysis. Researchers and decision makers should be aware of the influence of these somewhat arbitrary choices on their results.
    Value in Health 02/2011; 14(2):282-90. · 2.19 Impact Factor
  • reports 151 01/2010; KCE.