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...
Saved in:
Published in: | Statistical methods in medical research 2011-10, Vol.20 (5), p.551-570 |
---|---|
Main Authors: | , , , , , , |
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 & 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 & 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 & 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 & 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 & Abstracts (ASSIA)</collection><collection>Computer and Information Systems Abstracts</collection><collection>ProQuest_Health & 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 & 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 & 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 & 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 |