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Title
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Sample size calculation for estimating key epidemiological parameters using serological data and mathematical modelling
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Author
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Abstract
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| BackgroundOur work was motivated by the need to, given serum availability and/or financial resources, decide on which samples to test in a serum bank for different pathogens. Simulation-based sample size calculations were performed to determine the age-based sampling structures and optimal allocation of a given number of samples for testing across various age groups best suited to estimate key epidemiological parameters (e.g., seroprevalence or force of infection) with acceptable precision levels in a cross-sectional seroprevalence survey.MethodsStatistical and mathematical models and three age-based sampling structures (survey-based structure, population-based structure, uniform structure) were used. Our calculations are based on Belgian serological survey data collected in 2001-2003 where testing was done, amongst others, for the presence of Immunoglobulin G antibodies against measles, mumps, and rubella, for which a national mass immunisation programme was introduced in 1985 in Belgium, and against varicella-zoster virus and parvovirus B19 for which the endemic equilibrium assumption is tenable in Belgium.ResultsThe optimal age-based sampling structure to use in the sampling of a serological survey as well as the optimal allocation distribution varied depending on the epidemiological parameter of interest for a given infection and between infections.ConclusionsWhen estimating epidemiological parameters with acceptable levels of precision within the context of a single cross-sectional serological survey, attention should be given to the age-based sampling structure. Simulation-based sample size calculations in combination with mathematical modelling can be utilised for choosing the optimal allocation of a given number of samples over various age groups. |
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Language
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English
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Source (journal)
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BMC medical research methodology. - London
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Publication
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London
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2019
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ISSN
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1471-2288
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DOI
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10.1186/S12874-019-0692-1
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Volume/pages
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19
(2019)
, 12 p.
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Article Reference
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51
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ISI
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000460770100002
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Pubmed ID
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30845904
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Medium
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E-only publicatie
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Full text (Publisher's DOI)
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Full text (open access)
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