Author: Agua-Agum, Junerlyn; Ariyarajah, Archchun; Aylward, Bruce; Bawo, Luke; Bilivogui, Pepe; Blake, Isobel M.; Brennan, Richard J.; Cawthorne, Amy; Cleary, Eilish; Clement, Peter; Conteh, Roland; Cori, Anne; Dafae, Foday; Dahl, Benjamin; Dangou, Jean-Marie; Diallo, Boubacar; Donnelly, Christl A.; Dorigatti, Ilaria; Dye, Christopher; Eckmanns, Tim; Fallah, Mosoka; Ferguson, Neil M.; Fiebig, Lena; Fraser, Christophe; Garske, Tini; Gonzalez, Lice; Hamblion, Esther; Hamid, Nuha; Hersey, Sara; Hinsley, Wes; Jambei, Amara; Jombart, Thibaut; Kargbo, David; Keita, Sakoba; Kinzer, Michael; George, Fred Kuti; Godefroy, Beatrice; Gutierrez, Giovanna; Kannangarage, Niluka; Mills, Harriet L.; Moller, Thomas; Meijers, Sascha; Mohamed, Yasmine; Morgan, Oliver; Nedjati-Gilani, Gemma; Newton, Emily; Nouvellet, Pierre; Nyenswah, Tolbert; Perea, William; Perkins, Devin; Riley, Steven; Rodier, Guenael; Rondy, Marc; Sagrado, Maria; Savulescu, Camelia; Schafer, Ilana J.; Schumacher, Dirk; Seyler, Thomas; Shah, Anita; Van Kerkhove, Maria D.; Wesseh, C. Samford; Yoti, Zabulon
Title: Exposure Patterns Driving Ebola Transmission in West Africa: A Retrospective Observational Study Document date: 2016_11_15
ID: 069pelqj_12
Snippet: We assessed whether cases who reported at least one non-funeral or funeral exposure were different from cases who did not report that type of exposure. This allowed us to assess whether cases who report exposures are representative of the line-list. Multivariable logistic regressions were performed using predictors identified as significant (p < 0.05) in univariable logistic regressions (see section 1.11 in S1 Text for a list of predictors includ.....
Document: We assessed whether cases who reported at least one non-funeral or funeral exposure were different from cases who did not report that type of exposure. This allowed us to assess whether cases who report exposures are representative of the line-list. Multivariable logistic regressions were performed using predictors identified as significant (p < 0.05) in univariable logistic regressions (see section 1.11 in S1 Text for a list of predictors included in univariable analyses). The most parsimonious yet adequate multivariable model was then identified (using the Akaike information criterion) through backwards stepwise model selection (see final results in Tables b and c in S1 Text).
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