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Leveraging Contact Network Information in Clustered Randomized Studies of Contagion Processes.

dc.rights.licenseopenen_US
dc.contributor.authorWANG, Maxwell H
dc.contributor.authorSTAPLES, Patrick
hal.structure.identifierStatistics In System biology and Translational Medicine [SISTM]
hal.structure.identifierBordeaux population health [BPH]
dc.contributor.authorPRAGUE, Melanie
dc.contributor.authorGOYAL, Ravi
dc.contributor.authorDEGRUTTOLA, Victor
dc.contributor.authorONNELA, Jukka-Pekka
dc.date.accessioned2023-10-04T14:25:09Z
dc.date.available2023-10-04T14:25:09Z
dc.date.issued2023
dc.identifier.issn2767-3324en_US
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/184329
dc.description.abstractEnIn a randomized study, leveraging covariates related to the outcome (e.g. disease status) may produce less variable estimates of the effect of exposure. For contagion processes operating on a contact network, transmission can only occur through ties that connect affected and unaffected individuals; the outcome of such a process is known to depend intimately on the structure of the network. In this paper, we investigate the use of contact network features as efficiency covariates in exposure effect estimation. Using augmented generalized estimating equations (GEE), we estimate how gains in efficiency depend on the network structure and spread of the contagious agent or behavior. We apply this approach to simulated randomized trials using a stochastic compartmental contagion model on a collection of model-based contact networks and compare the bias, power, and variance of the estimated exposure effects using an assortment of network covariate adjustment strategies. We also demonstrate the use of network-augmented GEEs on a clustered randomized trial evaluating the effects of wastewater monitoring on COVID-19 cases in residential buildings at the the University of California San Diego.
dc.language.isoENen_US
dc.subject.enNetwork
dc.subject.enContagion
dc.subject.enStatistics
dc.title.enLeveraging Contact Network Information in Clustered Randomized Studies of Contagion Processes.
dc.title.alternativeObs Studen_US
dc.typeArticle de revueen_US
dc.identifier.doi10.1353/obs.2023.0021en_US
dc.subject.halSciences du Vivant [q-bio]/Santé publique et épidémiologieen_US
dc.identifier.pubmed37325081en_US
bordeaux.journalObservational Studiesen_US
bordeaux.page157-175en_US
bordeaux.volume9en_US
bordeaux.hal.laboratoriesBordeaux Population Health Research Center (BPH) - UMR 1219en_US
bordeaux.issue2en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.institutionINSERMen_US
bordeaux.institutionINRIAen_US
bordeaux.teamSISTMen_US
bordeaux.peerReviewedouien_US
bordeaux.inpressnonen_US
bordeaux.identifier.funderIDNational Institutes of Healthen_US
bordeaux.import.sourcepubmed
hal.popularnonen_US
hal.audienceInternationaleen_US
hal.exportfalse
workflow.import.sourcepubmed
dc.rights.ccPas de Licence CCen_US
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Observational%20Studies&rft.date=2023&rft.volume=9&rft.issue=2&rft.spage=157-175&rft.epage=157-175&rft.eissn=2767-3324&rft.issn=2767-3324&rft.au=WANG,%20Maxwell%20H&STAPLES,%20Patrick&PRAGUE,%20Melanie&GOYAL,%20Ravi&DEGRUTTOLA,%20Victor&rft.genre=article


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