Hospital vulnerability to spread of respiratory infections: close contact data collection and mathematical modelling

Abstract

The transmission risk of SARS-CoV-2 within hospitals can exceed that in the general community because of more frequent close proximity interactions (CPIs). Heterogeneity of risk across wards is still poorly described. We measured CPIs in 15 clinical wards across three hospitals using wearable sensors over 36 hours in spring 2020. This data was combined with a transmission model to estimate and compare transmission risks across wards. We found a four-fold range of epidemic risk between wards, with patients frequently presenting high risk to patients and healthcare workers (HCWs). Using a simulation study, we then assessed the potential impact on global risk of targeting individuals for prevention based on their contact patterns. We found that targeting individuals with the highest cumulative contact hours was most impactful. This study reveals patterns of interactions between individuals in hospital during a pandemic and opens new routes for research into airborne nosocomial risk.One Sentence SummaryWe measured contacts between staff, patients and visitors in 15 hospital wards, and used models to predict epidemic risk and evaluate interventions.