Loading…

A frequentist approach to estimating the force of infection for a respiratory disease using repeated measurement data from a birth cohort

This article aims to develop a probability-based model involving the use of direct likelihood formulation and generalised linear modelling (GLM) approaches useful in estimating important disease parameters from longitudinal or repeated measurement data. The current application is based on infection...

Full description

Saved in:
Bibliographic Details
Published in:Statistical methods in medical research 2011-10, Vol.20 (5), p.551-570
Main Authors: Mwambi, H, Ramroop, S, White, LJ, Okiro, EA, Nokes, DJ, Shkedy, Z, Molenberghs, G
Format: Article
Language:English
Subjects:
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
cited_by cdi_FETCH-LOGICAL-c492t-99435f3bdb4650a5de5cae085b16b694696f2f2d4c9a179445b36d0956b237613
cites cdi_FETCH-LOGICAL-c492t-99435f3bdb4650a5de5cae085b16b694696f2f2d4c9a179445b36d0956b237613
container_end_page 570
container_issue 5
container_start_page 551
container_title Statistical methods in medical research
container_volume 20
creator Mwambi, H
Ramroop, S
White, LJ
Okiro, EA
Nokes, DJ
Shkedy, Z
Molenberghs, G
description This article aims to develop a probability-based model involving the use of direct likelihood formulation and generalised linear modelling (GLM) approaches useful in estimating important disease parameters from longitudinal or repeated measurement data. The current application is based on infection with respiratory syncytial virus. The force of infection and the recovery rate or per capita loss of infection are the parameters of interest. However, because of the limitation arising from the study design and subsequently, the data generated only the force of infection is estimable. The problem of dealing with time-varying disease parameters is also addressed in the article by fitting piecewise constant parameters over time via the GLM approach. The current model formulation is based on that published in White LJ, Buttery J, Cooper B, Nokes DJ and Medley GF. Rotavirus within day care centres in Oxfordshire, UK: characterization of partial immunity. Journal of Royal Society Interface 2008; 5: 1481-1490 with an application to rotavirus transmission and immunity.
doi_str_mv 10.1177/0962280210385749
format article
fullrecord <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_3704207</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sage_id>10.1177_0962280210385749</sage_id><sourcerecordid>2496111941</sourcerecordid><originalsourceid>FETCH-LOGICAL-c492t-99435f3bdb4650a5de5cae085b16b694696f2f2d4c9a179445b36d0956b237613</originalsourceid><addsrcrecordid>eNqNkk1rFTEUhoMo9ra6dyXBjavRfE1ysxFK0SoU3Nh1yGRO7qTcmYxJRuhP6L8209tWLQhdBc553vd85CD0hpIPlCr1kWjJ2JYwSvi2VUI_QxsqlGoI5-I52qzpZs0foeOcrwghigj9Eh0xRtiWC7JBN6fYJ_i5wFRCLtjOc4rWDbhEDLmE0ZYw7XAZAPuYHODocZg8uBLitIawxQnyHJItMV3jPmSwGfCSV1mCGWyBHo81uCQYaxXc22JrzThWaRdSGbCLQ0zlFXrh7T7D67v3BF1--fzj7Gtz8f3829npReOEZqXRWvDW867vhGyJbXtonQWybTsqO6mF1NIzz3rhtKVKC9F2XPZEt7JjXEnKT9Cng--8dCP0rvaU7N7MqQ6brk20wfybmcJgdvGX4XV5jKhq8P7OIMW6uFzMGLKD_d5OEJdsNNVaUcGfQNYPUZxIXcl3j8iruKSp7uEWooxrXiFygFyKOSfwD01TYtZ7MI_voUre_j3sg-D-ACrQHIBsd_Cn6H8NfwOm_78T</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>900712393</pqid></control><display><type>article</type><title>A frequentist approach to estimating the force of infection for a respiratory disease using repeated measurement data from a birth cohort</title><source>Applied Social Sciences Index &amp; Abstracts (ASSIA)</source><source>Social Science Premium Collection</source><source>Sociology Collection</source><source>Sage Journals Online</source><creator>Mwambi, H ; Ramroop, S ; White, LJ ; Okiro, EA ; Nokes, DJ ; Shkedy, Z ; Molenberghs, G</creator><creatorcontrib>Mwambi, H ; Ramroop, S ; White, LJ ; Okiro, EA ; Nokes, DJ ; Shkedy, Z ; Molenberghs, G</creatorcontrib><description>This article aims to develop a probability-based model involving the use of direct likelihood formulation and generalised linear modelling (GLM) approaches useful in estimating important disease parameters from longitudinal or repeated measurement data. The current application is based on infection with respiratory syncytial virus. The force of infection and the recovery rate or per capita loss of infection are the parameters of interest. However, because of the limitation arising from the study design and subsequently, the data generated only the force of infection is estimable. The problem of dealing with time-varying disease parameters is also addressed in the article by fitting piecewise constant parameters over time via the GLM approach. The current model formulation is based on that published in White LJ, Buttery J, Cooper B, Nokes DJ and Medley GF. Rotavirus within day care centres in Oxfordshire, UK: characterization of partial immunity. Journal of Royal Society Interface 2008; 5: 1481-1490 with an application to rotavirus transmission and immunity.</description><identifier>ISSN: 0962-2802</identifier><identifier>EISSN: 1477-0334</identifier><identifier>DOI: 10.1177/0962280210385749</identifier><identifier>PMID: 22028340</identifier><language>eng</language><publisher>London, England: SAGE Publications</publisher><subject>Cohort Studies ; Female ; Humans ; Immunity ; Infection ; Male ; Measurement ; Parameters ; Respiratory diseases ; Respiratory Syncytial Viruses - isolation &amp; purification ; Respiratory Tract Infections - complications ; Respiratory Tract Infections - epidemiology ; Respiratory Tract Infections - physiopathology ; Rotavirus</subject><ispartof>Statistical methods in medical research, 2011-10, Vol.20 (5), p.551-570</ispartof><rights>The Author(s), 2011.</rights><rights>SAGE Publications © Oct 2011</rights><rights>The Author(s) 2013 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav 2013 SAGE Publications</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c492t-99435f3bdb4650a5de5cae085b16b694696f2f2d4c9a179445b36d0956b237613</citedby><cites>FETCH-LOGICAL-c492t-99435f3bdb4650a5de5cae085b16b694696f2f2d4c9a179445b36d0956b237613</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.proquest.com/docview/900712393?pq-origsite=primo$$EHTML$$P50$$Gproquest$$H</linktohtml><link.rule.ids>230,314,780,784,885,12846,21394,21395,27924,27925,30999,31000,33611,33612,34530,34531,43733,44115,79364</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/22028340$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Mwambi, H</creatorcontrib><creatorcontrib>Ramroop, S</creatorcontrib><creatorcontrib>White, LJ</creatorcontrib><creatorcontrib>Okiro, EA</creatorcontrib><creatorcontrib>Nokes, DJ</creatorcontrib><creatorcontrib>Shkedy, Z</creatorcontrib><creatorcontrib>Molenberghs, G</creatorcontrib><title>A frequentist approach to estimating the force of infection for a respiratory disease using repeated measurement data from a birth cohort</title><title>Statistical methods in medical research</title><addtitle>Stat Methods Med Res</addtitle><description>This article aims to develop a probability-based model involving the use of direct likelihood formulation and generalised linear modelling (GLM) approaches useful in estimating important disease parameters from longitudinal or repeated measurement data. The current application is based on infection with respiratory syncytial virus. The force of infection and the recovery rate or per capita loss of infection are the parameters of interest. However, because of the limitation arising from the study design and subsequently, the data generated only the force of infection is estimable. The problem of dealing with time-varying disease parameters is also addressed in the article by fitting piecewise constant parameters over time via the GLM approach. The current model formulation is based on that published in White LJ, Buttery J, Cooper B, Nokes DJ and Medley GF. Rotavirus within day care centres in Oxfordshire, UK: characterization of partial immunity. Journal of Royal Society Interface 2008; 5: 1481-1490 with an application to rotavirus transmission and immunity.</description><subject>Cohort Studies</subject><subject>Female</subject><subject>Humans</subject><subject>Immunity</subject><subject>Infection</subject><subject>Male</subject><subject>Measurement</subject><subject>Parameters</subject><subject>Respiratory diseases</subject><subject>Respiratory Syncytial Viruses - isolation &amp; purification</subject><subject>Respiratory Tract Infections - complications</subject><subject>Respiratory Tract Infections - epidemiology</subject><subject>Respiratory Tract Infections - physiopathology</subject><subject>Rotavirus</subject><issn>0962-2802</issn><issn>1477-0334</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>AFRWT</sourceid><sourceid>7QJ</sourceid><sourceid>ALSLI</sourceid><sourceid>HEHIP</sourceid><sourceid>M2S</sourceid><recordid>eNqNkk1rFTEUhoMo9ra6dyXBjavRfE1ysxFK0SoU3Nh1yGRO7qTcmYxJRuhP6L8209tWLQhdBc553vd85CD0hpIPlCr1kWjJ2JYwSvi2VUI_QxsqlGoI5-I52qzpZs0foeOcrwghigj9Eh0xRtiWC7JBN6fYJ_i5wFRCLtjOc4rWDbhEDLmE0ZYw7XAZAPuYHODocZg8uBLitIawxQnyHJItMV3jPmSwGfCSV1mCGWyBHo81uCQYaxXc22JrzThWaRdSGbCLQ0zlFXrh7T7D67v3BF1--fzj7Gtz8f3829npReOEZqXRWvDW867vhGyJbXtonQWybTsqO6mF1NIzz3rhtKVKC9F2XPZEt7JjXEnKT9Cng--8dCP0rvaU7N7MqQ6brk20wfybmcJgdvGX4XV5jKhq8P7OIMW6uFzMGLKD_d5OEJdsNNVaUcGfQNYPUZxIXcl3j8iruKSp7uEWooxrXiFygFyKOSfwD01TYtZ7MI_voUre_j3sg-D-ACrQHIBsd_Cn6H8NfwOm_78T</recordid><startdate>20111001</startdate><enddate>20111001</enddate><creator>Mwambi, H</creator><creator>Ramroop, S</creator><creator>White, LJ</creator><creator>Okiro, EA</creator><creator>Nokes, DJ</creator><creator>Shkedy, Z</creator><creator>Molenberghs, G</creator><general>SAGE Publications</general><general>Sage Publications Ltd</general><scope>AFRWT</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>0-V</scope><scope>3V.</scope><scope>7QJ</scope><scope>7SC</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88I</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ALSLI</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>HEHIP</scope><scope>JQ2</scope><scope>K9.</scope><scope>L6V</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0S</scope><scope>M1P</scope><scope>M2P</scope><scope>M2S</scope><scope>M7S</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PTHSS</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20111001</creationdate><title>A frequentist approach to estimating the force of infection for a respiratory disease using repeated measurement data from a birth cohort</title><author>Mwambi, H ; Ramroop, S ; White, LJ ; Okiro, EA ; Nokes, DJ ; Shkedy, Z ; Molenberghs, G</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c492t-99435f3bdb4650a5de5cae085b16b694696f2f2d4c9a179445b36d0956b237613</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Cohort Studies</topic><topic>Female</topic><topic>Humans</topic><topic>Immunity</topic><topic>Infection</topic><topic>Male</topic><topic>Measurement</topic><topic>Parameters</topic><topic>Respiratory diseases</topic><topic>Respiratory Syncytial Viruses - isolation &amp; purification</topic><topic>Respiratory Tract Infections - complications</topic><topic>Respiratory Tract Infections - epidemiology</topic><topic>Respiratory Tract Infections - physiopathology</topic><topic>Rotavirus</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Mwambi, H</creatorcontrib><creatorcontrib>Ramroop, S</creatorcontrib><creatorcontrib>White, LJ</creatorcontrib><creatorcontrib>Okiro, EA</creatorcontrib><creatorcontrib>Nokes, DJ</creatorcontrib><creatorcontrib>Shkedy, Z</creatorcontrib><creatorcontrib>Molenberghs, G</creatorcontrib><collection>Sage Journals GOLD Open Access 2024</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Social Sciences Premium Collection</collection><collection>ProQuest Central (Corporate)</collection><collection>Applied Social Sciences Index &amp; Abstracts (ASSIA)</collection><collection>Computer and Information Systems Abstracts</collection><collection>ProQuest_Health &amp; Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Science Database (Alumni Edition)</collection><collection>Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science &amp; Engineering Collection</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Social Science Premium Collection</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection (Proquest) (PQ_SDU_P3)</collection><collection>Sociology Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Health &amp; Medical Complete (Alumni)</collection><collection>ProQuest Engineering Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Health &amp; Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>ProQuest Science Journals</collection><collection>Sociology Database</collection><collection>Engineering Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>Engineering Collection</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Statistical methods in medical research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Mwambi, H</au><au>Ramroop, S</au><au>White, LJ</au><au>Okiro, EA</au><au>Nokes, DJ</au><au>Shkedy, Z</au><au>Molenberghs, G</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A frequentist approach to estimating the force of infection for a respiratory disease using repeated measurement data from a birth cohort</atitle><jtitle>Statistical methods in medical research</jtitle><addtitle>Stat Methods Med Res</addtitle><date>2011-10-01</date><risdate>2011</risdate><volume>20</volume><issue>5</issue><spage>551</spage><epage>570</epage><pages>551-570</pages><issn>0962-2802</issn><eissn>1477-0334</eissn><abstract>This article aims to develop a probability-based model involving the use of direct likelihood formulation and generalised linear modelling (GLM) approaches useful in estimating important disease parameters from longitudinal or repeated measurement data. The current application is based on infection with respiratory syncytial virus. The force of infection and the recovery rate or per capita loss of infection are the parameters of interest. However, because of the limitation arising from the study design and subsequently, the data generated only the force of infection is estimable. The problem of dealing with time-varying disease parameters is also addressed in the article by fitting piecewise constant parameters over time via the GLM approach. The current model formulation is based on that published in White LJ, Buttery J, Cooper B, Nokes DJ and Medley GF. Rotavirus within day care centres in Oxfordshire, UK: characterization of partial immunity. Journal of Royal Society Interface 2008; 5: 1481-1490 with an application to rotavirus transmission and immunity.</abstract><cop>London, England</cop><pub>SAGE Publications</pub><pmid>22028340</pmid><doi>10.1177/0962280210385749</doi><tpages>20</tpages><oa>free_for_read</oa></addata></record>
fulltext fulltext
identifier ISSN: 0962-2802
ispartof Statistical methods in medical research, 2011-10, Vol.20 (5), p.551-570
issn 0962-2802
1477-0334
language eng
recordid cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_3704207
source Applied Social Sciences Index & Abstracts (ASSIA); Social Science Premium Collection; Sociology Collection; Sage Journals Online
subjects Cohort Studies
Female
Humans
Immunity
Infection
Male
Measurement
Parameters
Respiratory diseases
Respiratory Syncytial Viruses - isolation & purification
Respiratory Tract Infections - complications
Respiratory Tract Infections - epidemiology
Respiratory Tract Infections - physiopathology
Rotavirus
title A frequentist approach to estimating the force of infection for a respiratory disease using repeated measurement data from a birth cohort
url http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-25T16%3A35%3A51IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_pubme&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=A%20frequentist%20approach%20to%20estimating%20the%20force%20of%20infection%20for%20a%20respiratory%20disease%20using%20repeated%20measurement%20data%20from%20a%20birth%20cohort&rft.jtitle=Statistical%20methods%20in%20medical%20research&rft.au=Mwambi,%20H&rft.date=2011-10-01&rft.volume=20&rft.issue=5&rft.spage=551&rft.epage=570&rft.pages=551-570&rft.issn=0962-2802&rft.eissn=1477-0334&rft_id=info:doi/10.1177/0962280210385749&rft_dat=%3Cproquest_pubme%3E2496111941%3C/proquest_pubme%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c492t-99435f3bdb4650a5de5cae085b16b694696f2f2d4c9a179445b36d0956b237613%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=900712393&rft_id=info:pmid/22028340&rft_sage_id=10.1177_0962280210385749&rfr_iscdi=true