Estimating infectious disease parameters from data on social contacts and serological status
AbstractIn dynamic models of infectious disease transmission, typically various mixing patterns are imposed on the so-called 'who acquires infection from whom' matrix. These imposed mixing patterns are based on prior knowledge of age-related social mixing behaviour rather than observations. Alternatively, we can assume that transmission rates for infections transmitted predominantly through non-sexual social contacts are proportional to rates of conversational contact which can be estimated from a contact survey. In general, however, contacts reported in social contact surveys are proxies of those events by which transmission may occur and there may be age-specific characteristics that are related to susceptibility and infectiousness which are not captured by the contact rates. Therefore, we model transmission as the product of two age-specific variables: the age-specific contact rate and an age-specific proportionality factor, which entails an improvement of fit for the seroprevalence of the varicella zoster virus in Belgium. Furthermore, we address the effect on the estimation of the basic reproduction number, using non-parametric bootstrapping to account for different sources of variability and using multimodel inference to deal with model selection uncertainty. The method proposed makes it possible to obtain important information on transmission dynamics that cannot be inferred from approaches that have been traditionally applied hitherto. Copyright (c) 2010 Royal Statistical Society.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
Bibliographic InfoArticle provided by Royal Statistical Society in its journal Journal of the Royal Statistical Society: Series C (Applied Statistics).
Volume (Year): 59 (2010)
Issue (Month): 2 ()
Contact details of provider:
Postal: 12 Errol Street, London EC1Y 8LX, United Kingdom
Web page: http://wileyonlinelibrary.com/journal/rssc
More information through EDIRC
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley-Blackwell Digital Licensing) or (Christopher F. Baum).
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If references are entirely missing, you can add them using this form.
If the full references list an item that is present in RePEc, but the system did not link to it, you can help with this form.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.