Nabila Parveen, E. Moodie, J. Cox, G. Lambert, J. Otis, M. Roger, B. Brenner
{"title":"New Challenges in HIV Research: Combining Phylogenetic Cluster Size and Epidemiological Data","authors":"Nabila Parveen, E. Moodie, J. Cox, G. Lambert, J. Otis, M. Roger, B. Brenner","doi":"10.1515/EM-2017-0017","DOIUrl":null,"url":null,"abstract":"Abstract An exciting new direction in HIV research is centered on using molecular phylogenetics to understand the social and behavioral drivers of HIV transmission. SPOT was an intervention designed to offer HIV point of care testing to men who have sex with men at a community-based site in Montreal, Canada; at the time of testing, a research questionnaire was also deployed to collect data on socio-demographic and behavioral characteristics of participating men. The men taking part in SPOT could be viewed, from the research perspective, as having been recruited via a convenience sample. Among men who were found to be HIV positive, phylogenetic cluster size was measured using a large cohort of HIV-positive individuals in the province of Quebec. The cluster size is likely subject to under-estimation. In this paper, we use SPOT data to evaluate the association between HIV transmission cluster size and the number of sex partners for MSM, after adjusting for the SPOT sampling scheme and correcting for measurement error in cluster size by leveraging external data sources. The sampling weights for SPOT participants were calculated from another study of men who have sex with men in Montreal by fitting a weight-adjusted model, whereas measurement error was corrected using the simulation-extrapolation conditional on covariates approach.","PeriodicalId":37999,"journal":{"name":"Epidemiologic Methods","volume":"36 9","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Epidemiologic Methods","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1515/EM-2017-0017","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Mathematics","Score":null,"Total":0}
引用次数: 3
Abstract
Abstract An exciting new direction in HIV research is centered on using molecular phylogenetics to understand the social and behavioral drivers of HIV transmission. SPOT was an intervention designed to offer HIV point of care testing to men who have sex with men at a community-based site in Montreal, Canada; at the time of testing, a research questionnaire was also deployed to collect data on socio-demographic and behavioral characteristics of participating men. The men taking part in SPOT could be viewed, from the research perspective, as having been recruited via a convenience sample. Among men who were found to be HIV positive, phylogenetic cluster size was measured using a large cohort of HIV-positive individuals in the province of Quebec. The cluster size is likely subject to under-estimation. In this paper, we use SPOT data to evaluate the association between HIV transmission cluster size and the number of sex partners for MSM, after adjusting for the SPOT sampling scheme and correcting for measurement error in cluster size by leveraging external data sources. The sampling weights for SPOT participants were calculated from another study of men who have sex with men in Montreal by fitting a weight-adjusted model, whereas measurement error was corrected using the simulation-extrapolation conditional on covariates approach.
期刊介绍：
Epidemiologic Methods (EM) seeks contributions comparable to those of the leading epidemiologic journals, but also invites papers that may be more technical or of greater length than what has traditionally been allowed by journals in epidemiology. Applications and examples with real data to illustrate methodology are strongly encouraged but not required. Topics. genetic epidemiology, infectious disease, pharmaco-epidemiology, ecologic studies, environmental exposures, screening, surveillance, social networks, comparative effectiveness, statistical modeling, causal inference, measurement error, study design, meta-analysis
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