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Household characteristics associated with surface contamination of SARS-CoV-2 and frequency of RT-PCR and viral culture positivity-California and Colorado, 2021.

Talya ShragaiCaroline PrattJoaudimir Castro GeorgiMarisa A P DonnellyNoah G SchwartzRaymond SotoMeagan ChueyVictoria T ChuPerrine MarcenacGeun Woo ParkAusaf AhmadBernadette AlbaneseSarah Elizabeth TottenBrett AustinPaige BunkleyBlake CherneyElizabeth A DietrichErica FigueroaJennifer M FolsterClaire GodinoOwen HerzeghKristine LindellBoris ReljaSarah W SheldonSuxiang TongJan VinjéNatalie J ThornburgAlmea M MatanockLaura J HughesGinger StringerMeghan HudziecMark E BeattyJacqueline E TateHannah L KirkingChristopher H Hsunull null
Published in: PloS one (2022)
While risk of fomite transmission of SARS-CoV-2 is considered low, there is limited environmental data within households. This January-April 2021 investigation describes frequency and types of surfaces positive for SARS-CoV-2 by real-time reverse transcription polymerase chain reaction (RT-PCR) among residences with ≥1 SARS-CoV-2 infection, and associations of household characteristics with surface RT-PCR and viable virus positivity. Of 1232 samples from 124 households, 27.8% (n = 342) were RT-PCR positive with nightstands (44.1%) and pillows (40.9%) most frequently positive. SARS-CoV-2 lineage, documented household transmission, greater number of infected persons, shorter interval between illness onset and sampling, total household symptoms, proportion of infected persons ≤12 years old, and persons exhibiting upper respiratory symptoms or diarrhea were associated with more positive surfaces. Viable virus was isolated from 0.2% (n = 3 samples from one household) of all samples. This investigation suggests that while SARS-CoV-2 on surfaces is common, fomite transmission risk in households is low.
Keyphrases
  • sars cov
  • respiratory syndrome coronavirus
  • biofilm formation
  • real time pcr
  • escherichia coli
  • machine learning
  • transcription factor
  • staphylococcus aureus
  • sleep quality
  • data analysis
  • cystic fibrosis