File Download

There are no files associated with this item.

  Links for fulltext
     (May Require Subscription)
Supplementary

Article: Modelling non-linear patterns of time-varying intervention effects on recurrent events in infectious disease prevention studies

TitleModelling non-linear patterns of time-varying intervention effects on recurrent events in infectious disease prevention studies
Authors
KeywordsAndersen–Gill model
infectious disease
non-linear function
protective efficacy
recurrent events
time-varying effect
Issue Date10-Aug-2022
PublisherTaylor and Francis Group
Citation
Journal of Biopharmaceutical Statistics, 2022, v. 33, n. 2, p. 220-233 How to Cite?
Abstract

Protective efficacy of vaccines and pharmaceutical products for prevention of infectious diseases usually vary over time. Information on the trajectory of the level of protection is valuable. We consider a parsimonious, non-linear and non-monotonic function for modelling time-varying intervention effects and compare it with several alternatives. The cumulative effects of multiple doses of intervention over time can be captured by an additive series of the function. We apply it to the Andersen–Gill model for analysis of recurrent time-to-event data. We re-analyze data from a trial of intermittent preventive treatment for malaria to illustrate and evaluate the method by simulation.


Persistent Identifierhttp://hdl.handle.net/10722/331592
ISSN
2023 Impact Factor: 1.2
2023 SCImago Journal Rankings: 0.812
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorCheung, Yin Bun-
dc.contributor.authorMa, Xiangmei-
dc.contributor.authorLam, K F-
dc.contributor.authorYung, Chee Fu-
dc.contributor.authorMilligan, Paul-
dc.date.accessioned2023-09-21T06:57:13Z-
dc.date.available2023-09-21T06:57:13Z-
dc.date.issued2022-08-10-
dc.identifier.citationJournal of Biopharmaceutical Statistics, 2022, v. 33, n. 2, p. 220-233-
dc.identifier.issn1054-3406-
dc.identifier.urihttp://hdl.handle.net/10722/331592-
dc.description.abstract<p>Protective efficacy of vaccines and pharmaceutical products for prevention of infectious diseases usually vary over time. Information on the trajectory of the level of protection is valuable. We consider a parsimonious, non-linear and non-monotonic function for modelling time-varying intervention effects and compare it with several alternatives. The cumulative effects of multiple doses of intervention over time can be captured by an additive series of the function. We apply it to the Andersen–Gill model for analysis of recurrent time-to-event data. We re-analyze data from a trial of intermittent preventive treatment for malaria to illustrate and evaluate the method by simulation.<br></p>-
dc.languageeng-
dc.publisherTaylor and Francis Group-
dc.relation.ispartofJournal of Biopharmaceutical Statistics-
dc.subjectAndersen–Gill model-
dc.subjectinfectious disease-
dc.subjectnon-linear function-
dc.subjectprotective efficacy-
dc.subjectrecurrent events-
dc.subjecttime-varying effect-
dc.titleModelling non-linear patterns of time-varying intervention effects on recurrent events in infectious disease prevention studies-
dc.typeArticle-
dc.identifier.doi10.1080/10543406.2022.2108826-
dc.identifier.scopuseid_2-s2.0-85135773146-
dc.identifier.volume33-
dc.identifier.issue2-
dc.identifier.spage220-
dc.identifier.epage233-
dc.identifier.eissn1520-5711-
dc.identifier.isiWOS:000838647400001-
dc.identifier.issnl1054-3406-

Export via OAI-PMH Interface in XML Formats


OR


Export to Other Non-XML Formats