Inferring Pathogen Type Interactions Using Cross-sectional Prevalence Data: Opportunities and Pitfalls for Predicting Type Replacement.

2.50
Hdl Handle:
http://hdl.handle.net/10029/622083
Title:
Inferring Pathogen Type Interactions Using Cross-sectional Prevalence Data: Opportunities and Pitfalls for Predicting Type Replacement.
Authors:
Man, Irene; Wallinga, Jacco; Bogaards, Johannes A
Abstract:
Many multivalent vaccines target only a subset of all pathogenic types. If vaccine and nonvaccine types compete, vaccination may lead to type replacement. The plausibility of type replacement has been assessed using the odds ratio (OR) of co-infections in cross-sectional prevalence data, with OR > 1 being interpreted as low risk of type replacement. The usefulness of the OR as a predictor for type replacement is debated, as it lacks a theoretical justification, and there is no framework explaining under which assumptions the OR predicts type replacement.
Citation:
Inferring Pathogen Type Interactions Using Cross-sectional Prevalence Data: Opportunities and Pitfalls for Predicting Type Replacement. 2018, 29 (5):666-674 Epidemiology
Journal:
Epidemiology 2018; advance online publication (ahead of print)
Issue Date:
Sep-2018
URI:
http://hdl.handle.net/10029/622083
DOI:
10.1097/EDE.0000000000000870
PubMed ID:
29923864
Type:
Article
Language:
en
ISSN:
1531-5487
Appears in Collections:
Miscellaneous

Full metadata record

DC FieldValue Language
dc.contributor.authorMan, Ireneen
dc.contributor.authorWallinga, Jaccoen
dc.contributor.authorBogaards, Johannes Aen
dc.date.accessioned2018-08-02T11:14:28Z-
dc.date.available2018-08-02T11:14:28Z-
dc.date.issued2018-09-
dc.identifier.citationInferring Pathogen Type Interactions Using Cross-sectional Prevalence Data: Opportunities and Pitfalls for Predicting Type Replacement. 2018, 29 (5):666-674 Epidemiologyen
dc.identifier.issn1531-5487-
dc.identifier.pmid29923864-
dc.identifier.doi10.1097/EDE.0000000000000870-
dc.identifier.urihttp://hdl.handle.net/10029/622083-
dc.description.abstractMany multivalent vaccines target only a subset of all pathogenic types. If vaccine and nonvaccine types compete, vaccination may lead to type replacement. The plausibility of type replacement has been assessed using the odds ratio (OR) of co-infections in cross-sectional prevalence data, with OR > 1 being interpreted as low risk of type replacement. The usefulness of the OR as a predictor for type replacement is debated, as it lacks a theoretical justification, and there is no framework explaining under which assumptions the OR predicts type replacement.en
dc.language.isoenen
dc.rightsinfo:eu-repo/semantics/closedAccessen
dc.titleInferring Pathogen Type Interactions Using Cross-sectional Prevalence Data: Opportunities and Pitfalls for Predicting Type Replacement.en
dc.typeArticleen
dc.identifier.journalEpidemiology 2018; advance online publication (ahead of print)en
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