Optimal Design of Intervention Studies to Prevent Influenza in Healthy Cohorts

Abstract

Influenza cohort studies, in which participants are monitored for infection over an epidemic period, are invaluable in assessing the effectiveness of control measures such as vaccination, antiviral prophylaxis and non-pharmaceutical interventions (NPIs). Influenza infections and illnesses can be identified through a number of approaches with different costs and logistical requirements. In the context of a randomized controlled trial of an NPI with a constrained budget, we used a simulation approach to examine which approaches to measuring outcomes could provide greater statistical power to identify an effective intervention against confirmed influenza. We found that for a short epidemic season, the optimal design was to collect respiratory specimens at biweekly intervals, as well as following report of acute respiratory illness (ARI), for virologic testing by reverse transcription polymerase chain reaction (RT-PCR). Collection of respiratory specimens only from individuals reporting ARI was also an efficient design particularly for studies in settings with longer periods of influenza activity. Collection of specimens only from individuals reporting a febrile ARI was less efficient. Collection and testing of sera before and after influenza activity appeared to be inferior to collection of respiratory specimens for RT-PCR confirmation of acute infections. The performance of RT-PCR was robust to uncertainty in the costs and diagnostic performance of RT-PCR and serological tests. Our results suggest that unless the sensitivity or specificity of serology can be increased RT-PCR will remain as the preferable outcome measure in NPI studies. Routine collection of specimens for RT-PCR testing even when study participants do not report acute respiratory illness appears to be the most cost efficient design under most scenarios.