We introduce an inverse probability censoring weighted (IPCW) estimator, extending the IPW estimator for network-based observational studies to handle possible outcome censoring. We prove the consistency and asymptotic normality of the proposed estimator and derive a closed-form estimator for its asymptotic variance. Applying the IPCW estimator, we assess spillover effects in a network-based study of a nonrandomized intervention with outcome censoring. A simulation study evaluates the finite-sample performance of the IPCW estimator, demonstrating its effectiveness with sufficiently large sample sizes and number of connected subnetworks. We then employ the method to assess spillover effects of community alerts on self-reported HIV risk behavior among people who inject drugs and their contacts in the Transmission Reduction Intervention Project (TRIP), 2013 to 2015, Athens, Greece. Results suggest that community alerts may help reduce HIV risk behavior for both the individuals who receive them and others in their network, possibly through shared information. In this study, we found that the risk of HIV behavior was reduced by increasing the proportion of a participant’s immediate contacts exposed to community alerts.

Final publication available soon.