Longitudinal monitoring of SARS-CoV-2 RNA on high-touch surfaces in a community setting.

Autor: Harvey AP; Civil and Environmental Engineering, Tufts University, Medford, MA, 02155., Fuhrmeister ER; Civil and Environmental Engineering, Tufts University, Medford, MA, 02155., Cantrell M; Civil and Environmental Engineering, Tufts University, Medford, MA, 02155., Pitol AK; Department of Civil and Environmental Engineering, Imperial College London, United Kingdom., Swarthout JM; Civil and Environmental Engineering, Tufts University, Medford, MA, 02155., Powers JE; Civil and Environmental Engineering, Tufts University, Medford, MA, 02155., Nadimpalli ML; Civil and Environmental Engineering, Tufts University, Medford, MA, 02155., Julian TR; Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dubendorf CH-8600, Switzerland.; Swiss Tropical and Public Health Institute, Basel, Switzerland.; University of Basel, Basel, Switzerland., Pickering AJ; Civil and Environmental Engineering, Tufts University, Medford, MA, 02155.; Department of Civil and Environmental Engineering, University of California, Berkeley.
Jazyk: angličtina
Zdroj: MedRxiv : the preprint server for health sciences [medRxiv] 2020 Nov 01. Date of Electronic Publication: 2020 Nov 01.
DOI: 10.1101/2020.10.27.20220905
Abstrakt: Environmental surveillance of surface contamination is an unexplored tool for understanding transmission of SARS-CoV-2 in community settings. We conducted longitudinal swab sampling of high-touch non-porous surfaces in a Massachusetts town during a COVID-19 outbreak from April to June 2020. Twenty-nine of 348 (8.3 %) surface samples were positive for SARS-CoV-2, including crosswalk buttons, trash can handles, and door handles of essential business entrances (grocery store, liquor store, bank, and gas station). The estimated risk of infection from touching a contaminated surface was low (less than 5 in 10,000), suggesting fomites play a minimal role in SARS-CoV-2 community transmission. The weekly percentage of positive samples (out of n=33 unique surfaces per week) best predicted variation in city-level COVID-19 cases using a 7-day lead time. Environmental surveillance of SARS-CoV-2 RNA on high-touch surfaces could be a useful tool to provide early warning of COVID-19 case trends.
Databáze: MEDLINE