چکیده (انگلیسی):

Social networks are increasingly recognized as important points of intervention, yet rela-tively few intervention studies of respiratory infection transmission have utilized a network design. Herewe describe the design, methods, and social network structure of a randomized intervention for isolatingrespiratory infection cases in a university setting over a 10-week period.Methodology/principal findings: 590 students in six residence halls enrolled in the eX-FLU study during achain-referral recruitment process from September 2012–January 2013. Of these, 262 joined as “seed”participants, who nominated their social contacts to join the study, of which 328 “nominees” enrolled.Participants were cluster-randomized by 117 residence halls. Participants were asked to respond toweekly surveys on health behaviors, social interactions, and influenza-like illness (ILI) symptoms. Par-ticipants were randomized to either a 3-Day dorm room isolation intervention or a control group (noisolation) upon illness onset. ILI cases reported on their isolation behavior during illness and providedthroat and nasal swab specimens at onset, day-three, and day-six of illness. A subsample of individ-uals (N = 103) participated in a sub-study using a novel smartphone application, iEpi, which collectedsensor and contextually-dependent survey data on social interactions. Within the social network, par-ticipants were significantly positively assortative by intervention group, enrollment type, residence hall,iEpi participation, age, gender, race, and alcohol use (all P < 0.002).Conclusions/significance: We identified a feasible study design for testing the impact of isolation fromsocial networks in a university setting. These data provide an unparalleled opportunity to address ques-tions about isolation and infection transmission, as well as insights into social networks and behaviorsamong college-aged students. Several important lessons were learned over the course of this project,including feasible isolation durations, the need for extensive organizational efforts, as well as the needfor specialized programmers and server space for managing survey and smartphone data.© 2016 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-NDlicense (http://creativecommons.org/licenses/by-nc-nd/4.0/).