Linked Life Data

15273957

Source:http://linkedlifedata.com/resource/pubmed/id/15273957

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
15
pubmed:dateCreated
2004-7-26
pubmed:abstractText
Serological surveys are a useful source of information about epidemiological parameters for infectious diseases. In particular they may be used to estimate contact rates, forces of infection, the reproduction number and the critical vaccination threshold. However, these estimation methods require the assumption that the infection is in endemic equilibrium. Such equilibria seldom exist in practice: for example, many common infections of childhood exhibit regular epidemic cycles. In this paper, we investigate whether ignoring such cycles produces biased estimates. We apply the methods to data on mumps and rubella in the U.K. prior to the introduction of the combined measles, mumps, rubella (MMR) vaccine. We conclude that past epidemics have only a marginal effect on estimates, and that standard methods that do not adjust for regular epidemics are valid.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:status
MEDLINE
pubmed:month
Aug
pubmed:issn
0277-6715
pubmed:author
pubmed:issnType
Print
pubmed:day
15
pubmed:volume
23
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
2429-43
pubmed:dateRevised
2006-11-15
pubmed:meshHeading
pubmed:year
2004
pubmed:articleTitle
Estimation of infectious disease parameters from serological survey data: the impact of regular epidemics.
pubmed:affiliation
Department of Statistics, The Open University, Milton Keynes, UK. h.j.whitaker@open.ac.uk
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't