Modeling Prevention Strategies for Gonorrhea and Chlamydia Using Stochastic Network Simulations

A simulation model was used to study the spread of two sexually transmitted diseases (STDs), namely gonorrhea and genital infection with Chlamydia trachomatis. The model is based on a stochastic pair formation and separation process, which describes the underlying structure of the sexual contact pat...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:American journal of epidemiology 1996-08, Vol.144 (3), p.306-317
Hauptverfasser: Kretzschmar, Mirjam, van Duynhoven, Yvonne T. H. P., Severijnen, Anton J.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
container_end_page 317
container_issue 3
container_start_page 306
container_title American journal of epidemiology
container_volume 144
creator Kretzschmar, Mirjam
van Duynhoven, Yvonne T. H. P.
Severijnen, Anton J.
description A simulation model was used to study the spread of two sexually transmitted diseases (STDs), namely gonorrhea and genital infection with Chlamydia trachomatis. The model is based on a stochastic pair formation and separation process, which describes the underlying structure of the sexual contact pattern. It is implemented as a Monte Carlo simulation model. Spread of the STDs was modeled in an age-structured heterosexual population with a highly sexually active core group. Contact tracing strategies, screening of various subgroups, and the effect of condom use were compared. The authors conclude that contact tracing is very effective as a prevention strategy, that screening should be targeted to the highly active core group, that age is not sufficient as a determinant for high sexual activity to make screening of certain age groups useful, and, finally, that consistent condom use by a fraction of the population can contribute substantially to the prevention of STDs. All strategies proved more effective for gonorrhea than for chlamydia prevention, which may explain the relatively high prevalence of chlamydia found in many heterosexual populations. Am J Epidemiol 1996; 144: 306–17.
doi_str_mv 10.1093/oxfordjournals.aje.a008926
format Article
fullrecord <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_78178931</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>78178931</sourcerecordid><originalsourceid>FETCH-LOGICAL-c412t-a3437ff5182ea816f01b532aaef0f02b6c1da37298037d8930b113675dee2d663</originalsourceid><addsrcrecordid>eNqFkV-L00AUxQdR1rr6EYQg4lvqnZnOn_gmRVuhrkpdEF-G2-RmO90ks84kuvvtTWko-OTThXt-59xhDmOvOMw5FPJtuK9DrA5hiB02aY4HmiOALYR-xGZ8YXSuhdKP2QwARD6uxVP2LKUDAOeFggt2YbXVBmDG3OdQUeO7m-xrpN_U9T502baP2NONp5SNh7JV6EKMe8IMuypb7htsHyqP2XU6-rZ9KPeYel9mV9T_CfE22_p2aPAYlZ6zJ_X4RnoxzUt2_fHD9-U633xZfVq-3-Tlgos-R7mQpq4Vt4LQcl0D3ykpEKmGGsROl7xCaURhQZrKFhJ2nEttVEUkKq3lJXtzyr2L4ddAqXetTyU1DXYUhuSM5Wa08f-CXOmFKNQx8d0JLGNIKVLt7qJvMT44Du5Yg_u3BjfW4KYaRvPL6cqwa6k6W6d_H_XXk46pxKaO2JU-nTHJrZTWjlh-wnzq6f4sY7x12kij3PrHT2ftZqVg_c1dyb-N8abq</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>15642956</pqid></control><display><type>article</type><title>Modeling Prevention Strategies for Gonorrhea and Chlamydia Using Stochastic Network Simulations</title><source>MEDLINE</source><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><source>Oxford University Press Journals All Titles (1996-Current)</source><source>Alma/SFX Local Collection</source><creator>Kretzschmar, Mirjam ; van Duynhoven, Yvonne T. H. P. ; Severijnen, Anton J.</creator><creatorcontrib>Kretzschmar, Mirjam ; van Duynhoven, Yvonne T. H. P. ; Severijnen, Anton J.</creatorcontrib><description>A simulation model was used to study the spread of two sexually transmitted diseases (STDs), namely gonorrhea and genital infection with Chlamydia trachomatis. The model is based on a stochastic pair formation and separation process, which describes the underlying structure of the sexual contact pattern. It is implemented as a Monte Carlo simulation model. Spread of the STDs was modeled in an age-structured heterosexual population with a highly sexually active core group. Contact tracing strategies, screening of various subgroups, and the effect of condom use were compared. The authors conclude that contact tracing is very effective as a prevention strategy, that screening should be targeted to the highly active core group, that age is not sufficient as a determinant for high sexual activity to make screening of certain age groups useful, and, finally, that consistent condom use by a fraction of the population can contribute substantially to the prevention of STDs. All strategies proved more effective for gonorrhea than for chlamydia prevention, which may explain the relatively high prevalence of chlamydia found in many heterosexual populations. Am J Epidemiol 1996; 144: 306–17.</description><identifier>ISSN: 0002-9262</identifier><identifier>EISSN: 1476-6256</identifier><identifier>DOI: 10.1093/oxfordjournals.aje.a008926</identifier><identifier>PMID: 8686700</identifier><identifier>CODEN: AJEPAS</identifier><language>eng</language><publisher>Cary, NC: Oxford University Press</publisher><subject>Adolescent ; Adult ; Biological and medical sciences ; chlamydia infections ; Chlamydia Infections - epidemiology ; Chlamydia Infections - prevention &amp; control ; Chlamydia Infections - transmission ; Chlamydia trachomatis ; Condoms - statistics &amp; numerical data ; Female ; General aspects ; gonorrhea ; Gonorrhea - epidemiology ; Gonorrhea - prevention &amp; control ; Gonorrhea - transmission ; Human infectious diseases. Experimental studies and models ; Humans ; Incidence ; Infectious diseases ; Male ; Markov Chains ; Medical sciences ; Middle Aged ; Models, Statistical ; Monte Carlo Method ; Neisseria gonorrhoeae ; Netherlands - epidemiology ; Prevalence ; Random Allocation ; Sexual Behavior - statistics &amp; numerical data ; Sexual Partners ; sexually transmitted diseases ; stochastic</subject><ispartof>American journal of epidemiology, 1996-08, Vol.144 (3), p.306-317</ispartof><rights>1996 INIST-CNRS</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c412t-a3437ff5182ea816f01b532aaef0f02b6c1da37298037d8930b113675dee2d663</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,777,781,27905,27906</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&amp;idt=3183388$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/8686700$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Kretzschmar, Mirjam</creatorcontrib><creatorcontrib>van Duynhoven, Yvonne T. H. P.</creatorcontrib><creatorcontrib>Severijnen, Anton J.</creatorcontrib><title>Modeling Prevention Strategies for Gonorrhea and Chlamydia Using Stochastic Network Simulations</title><title>American journal of epidemiology</title><addtitle>Am J Epidemiol</addtitle><description>A simulation model was used to study the spread of two sexually transmitted diseases (STDs), namely gonorrhea and genital infection with Chlamydia trachomatis. The model is based on a stochastic pair formation and separation process, which describes the underlying structure of the sexual contact pattern. It is implemented as a Monte Carlo simulation model. Spread of the STDs was modeled in an age-structured heterosexual population with a highly sexually active core group. Contact tracing strategies, screening of various subgroups, and the effect of condom use were compared. The authors conclude that contact tracing is very effective as a prevention strategy, that screening should be targeted to the highly active core group, that age is not sufficient as a determinant for high sexual activity to make screening of certain age groups useful, and, finally, that consistent condom use by a fraction of the population can contribute substantially to the prevention of STDs. All strategies proved more effective for gonorrhea than for chlamydia prevention, which may explain the relatively high prevalence of chlamydia found in many heterosexual populations. Am J Epidemiol 1996; 144: 306–17.</description><subject>Adolescent</subject><subject>Adult</subject><subject>Biological and medical sciences</subject><subject>chlamydia infections</subject><subject>Chlamydia Infections - epidemiology</subject><subject>Chlamydia Infections - prevention &amp; control</subject><subject>Chlamydia Infections - transmission</subject><subject>Chlamydia trachomatis</subject><subject>Condoms - statistics &amp; numerical data</subject><subject>Female</subject><subject>General aspects</subject><subject>gonorrhea</subject><subject>Gonorrhea - epidemiology</subject><subject>Gonorrhea - prevention &amp; control</subject><subject>Gonorrhea - transmission</subject><subject>Human infectious diseases. Experimental studies and models</subject><subject>Humans</subject><subject>Incidence</subject><subject>Infectious diseases</subject><subject>Male</subject><subject>Markov Chains</subject><subject>Medical sciences</subject><subject>Middle Aged</subject><subject>Models, Statistical</subject><subject>Monte Carlo Method</subject><subject>Neisseria gonorrhoeae</subject><subject>Netherlands - epidemiology</subject><subject>Prevalence</subject><subject>Random Allocation</subject><subject>Sexual Behavior - statistics &amp; numerical data</subject><subject>Sexual Partners</subject><subject>sexually transmitted diseases</subject><subject>stochastic</subject><issn>0002-9262</issn><issn>1476-6256</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1996</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkV-L00AUxQdR1rr6EYQg4lvqnZnOn_gmRVuhrkpdEF-G2-RmO90ks84kuvvtTWko-OTThXt-59xhDmOvOMw5FPJtuK9DrA5hiB02aY4HmiOALYR-xGZ8YXSuhdKP2QwARD6uxVP2LKUDAOeFggt2YbXVBmDG3OdQUeO7m-xrpN_U9T502baP2NONp5SNh7JV6EKMe8IMuypb7htsHyqP2XU6-rZ9KPeYel9mV9T_CfE22_p2aPAYlZ6zJ_X4RnoxzUt2_fHD9-U633xZfVq-3-Tlgos-R7mQpq4Vt4LQcl0D3ykpEKmGGsROl7xCaURhQZrKFhJ2nEttVEUkKq3lJXtzyr2L4ddAqXetTyU1DXYUhuSM5Wa08f-CXOmFKNQx8d0JLGNIKVLt7qJvMT44Du5Yg_u3BjfW4KYaRvPL6cqwa6k6W6d_H_XXk46pxKaO2JU-nTHJrZTWjlh-wnzq6f4sY7x12kij3PrHT2ftZqVg_c1dyb-N8abq</recordid><startdate>19960801</startdate><enddate>19960801</enddate><creator>Kretzschmar, Mirjam</creator><creator>van Duynhoven, Yvonne T. H. P.</creator><creator>Severijnen, Anton J.</creator><general>Oxford University Press</general><scope>BSCLL</scope><scope>IQODW</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>7QL</scope><scope>C1K</scope><scope>7X8</scope></search><sort><creationdate>19960801</creationdate><title>Modeling Prevention Strategies for Gonorrhea and Chlamydia Using Stochastic Network Simulations</title><author>Kretzschmar, Mirjam ; van Duynhoven, Yvonne T. H. P. ; Severijnen, Anton J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c412t-a3437ff5182ea816f01b532aaef0f02b6c1da37298037d8930b113675dee2d663</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1996</creationdate><topic>Adolescent</topic><topic>Adult</topic><topic>Biological and medical sciences</topic><topic>chlamydia infections</topic><topic>Chlamydia Infections - epidemiology</topic><topic>Chlamydia Infections - prevention &amp; control</topic><topic>Chlamydia Infections - transmission</topic><topic>Chlamydia trachomatis</topic><topic>Condoms - statistics &amp; numerical data</topic><topic>Female</topic><topic>General aspects</topic><topic>gonorrhea</topic><topic>Gonorrhea - epidemiology</topic><topic>Gonorrhea - prevention &amp; control</topic><topic>Gonorrhea - transmission</topic><topic>Human infectious diseases. Experimental studies and models</topic><topic>Humans</topic><topic>Incidence</topic><topic>Infectious diseases</topic><topic>Male</topic><topic>Markov Chains</topic><topic>Medical sciences</topic><topic>Middle Aged</topic><topic>Models, Statistical</topic><topic>Monte Carlo Method</topic><topic>Neisseria gonorrhoeae</topic><topic>Netherlands - epidemiology</topic><topic>Prevalence</topic><topic>Random Allocation</topic><topic>Sexual Behavior - statistics &amp; numerical data</topic><topic>Sexual Partners</topic><topic>sexually transmitted diseases</topic><topic>stochastic</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kretzschmar, Mirjam</creatorcontrib><creatorcontrib>van Duynhoven, Yvonne T. H. P.</creatorcontrib><creatorcontrib>Severijnen, Anton J.</creatorcontrib><collection>Istex</collection><collection>Pascal-Francis</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Environmental Sciences and Pollution Management</collection><collection>MEDLINE - Academic</collection><jtitle>American journal of epidemiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kretzschmar, Mirjam</au><au>van Duynhoven, Yvonne T. H. P.</au><au>Severijnen, Anton J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Modeling Prevention Strategies for Gonorrhea and Chlamydia Using Stochastic Network Simulations</atitle><jtitle>American journal of epidemiology</jtitle><addtitle>Am J Epidemiol</addtitle><date>1996-08-01</date><risdate>1996</risdate><volume>144</volume><issue>3</issue><spage>306</spage><epage>317</epage><pages>306-317</pages><issn>0002-9262</issn><eissn>1476-6256</eissn><coden>AJEPAS</coden><abstract>A simulation model was used to study the spread of two sexually transmitted diseases (STDs), namely gonorrhea and genital infection with Chlamydia trachomatis. The model is based on a stochastic pair formation and separation process, which describes the underlying structure of the sexual contact pattern. It is implemented as a Monte Carlo simulation model. Spread of the STDs was modeled in an age-structured heterosexual population with a highly sexually active core group. Contact tracing strategies, screening of various subgroups, and the effect of condom use were compared. The authors conclude that contact tracing is very effective as a prevention strategy, that screening should be targeted to the highly active core group, that age is not sufficient as a determinant for high sexual activity to make screening of certain age groups useful, and, finally, that consistent condom use by a fraction of the population can contribute substantially to the prevention of STDs. All strategies proved more effective for gonorrhea than for chlamydia prevention, which may explain the relatively high prevalence of chlamydia found in many heterosexual populations. Am J Epidemiol 1996; 144: 306–17.</abstract><cop>Cary, NC</cop><pub>Oxford University Press</pub><pmid>8686700</pmid><doi>10.1093/oxfordjournals.aje.a008926</doi><tpages>12</tpages></addata></record>
fulltext fulltext
identifier ISSN: 0002-9262
ispartof American journal of epidemiology, 1996-08, Vol.144 (3), p.306-317
issn 0002-9262
1476-6256
language eng
recordid cdi_proquest_miscellaneous_78178931
source MEDLINE; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals; Oxford University Press Journals All Titles (1996-Current); Alma/SFX Local Collection
subjects Adolescent
Adult
Biological and medical sciences
chlamydia infections
Chlamydia Infections - epidemiology
Chlamydia Infections - prevention & control
Chlamydia Infections - transmission
Chlamydia trachomatis
Condoms - statistics & numerical data
Female
General aspects
gonorrhea
Gonorrhea - epidemiology
Gonorrhea - prevention & control
Gonorrhea - transmission
Human infectious diseases. Experimental studies and models
Humans
Incidence
Infectious diseases
Male
Markov Chains
Medical sciences
Middle Aged
Models, Statistical
Monte Carlo Method
Neisseria gonorrhoeae
Netherlands - epidemiology
Prevalence
Random Allocation
Sexual Behavior - statistics & numerical data
Sexual Partners
sexually transmitted diseases
stochastic
title Modeling Prevention Strategies for Gonorrhea and Chlamydia Using Stochastic Network Simulations
url https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-19T11%3A23%3A10IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Modeling%20Prevention%20Strategies%20for%20Gonorrhea%20and%20Chlamydia%20Using%20Stochastic%20Network%20Simulations&rft.jtitle=American%20journal%20of%20epidemiology&rft.au=Kretzschmar,%20Mirjam&rft.date=1996-08-01&rft.volume=144&rft.issue=3&rft.spage=306&rft.epage=317&rft.pages=306-317&rft.issn=0002-9262&rft.eissn=1476-6256&rft.coden=AJEPAS&rft_id=info:doi/10.1093/oxfordjournals.aje.a008926&rft_dat=%3Cproquest_cross%3E78178931%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=15642956&rft_id=info:pmid/8686700&rfr_iscdi=true