Modeling shield immunity to reduce COVID-19 transmission in long-term care facilities

Purpose: Nursing homes and long-term care facilities have experienced severe outbreaks and elevated mortality rates of COVID-19. When available, vaccination at-scale has helped drive a rapid reduction in severe cases. However, vaccination coverage remains incomplete among residents and staff, such that additional mitigation and prevention strategies are needed to reduce the ongoing risk of transmission. One such strategy is that of "shield immunity", in which immune individuals modulate their contact rates and shield uninfected individuals from potentially risky interactions. Methods: Here, we adapt shield immunity principles to a network context, by using computational mod-els to evaluate how restructured interactions between staff and residents affect SARS-CoV-2 epidemic dynamics. Results: First, we identify a mitigation rewiring strategy that reassigns immune healthcare workers to infected residents, significantly reducing outbreak sizes given weekly testing and rewiring (48% reduction in the outbreak size). Second, we identify a preventative prewiring strategy in which susceptible health-care workers are assigned to immunized residents. This preventative strategy reduces the risk and size of an outbreak via the inadvertent introduction of an infectious healthcare worker in a partially immunized population (44% reduction in the epidemic size). These mitigation levels derived from network-based in-terventions are similar to those derived from isolating infectious healthcare workers. Conclusions: This modeling-based assessment of shield immunity provides further support for leveraging infection and immune status in network-based interventions to control and prevent the spread of COVID-19.