Detection of SARS-CoV-2 in aerosols in long term care facilities and other indoor spaces with known COVID-19 outbreaks

Abstract

Coronavirus outbreaks are likely to occur in crowded and congregate indoor spaces, and their effects are most severe in vulnerable long term care facilities (LTCFs) residents. Public health officers benefit from tools that allow them to control COVID-19 outbreaks in vulnerable settings such as LTCFs, but which could be translated in the future to control other known and future virus outbreaks. This study aims to develop and test a methodology based on detection of SARS-CoV-2 in aerosol samples collected with personal pumps that could be easily implemented by public health officers. The proposed methodology was used to investigate the levels of SARS-CoV-2 in aerosol in indoor settings, mainly focusing on LTCFs, suffering COVID-19 outbreaks, or in the presence of known COVID-19 cases, and targeting the initial days after diagnosis.Aerosol samples (N = 18) were collected between November 2020 and March 2022 in Castelló (Spain) from LTCFs, merchant ships and a private home with recently infected COVID-19 cases. Sampling was performed for 24-h, onto 47 mm polytetrafluoroethylene (PTFE) and quartz filters, connected to personal pumps at 2 and 4 L/min respectively. RNA from filters was extracted and SARS-CoV-2 was determined by detection of regions N1 and N2 of the nucleocapsid gene alongside the E gene using RT-PCR technique.SARS-CoV-2 genetic material was detected in 87.5% samples. Concentrations ranged ND-19,525 gc/m3 (gene E). No genetic traces were detected in rooms from contacts that were isolated as a preventative measure. Very high levels were also measured at locations with poor ventilation. Aerosol measurement conducted with the proposed methodology provided useful information to public health officers and contributed to manage and control 12 different COVID-19 outbreaks.SARS-CoV-2 was detected in aerosol samples collected during outbreaks in congregate spaces. Indoor aerosol sampling is a useful tool in the early detection and management of COVID-19 outbreaks and supports epidemiological investigations.