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Speech-generated aerosol settling times and viral viability can improve COVID-19 transmission prediction

Gu, Alan Y. and Zhu, Yanzhe and Li, Jing and Hoffmann, Michael R. (2022) Speech-generated aerosol settling times and viral viability can improve COVID-19 transmission prediction. Environmental Science: Atmospheres, 2 (1). pp. 34-45. ISSN 2634-3606. doi:10.1039/d1ea00013f. https://resolver.caltech.edu/CaltechAUTHORS:20211209-456403000

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Abstract

Droplets during human speech are found to remain suspended in the air for minutes, while studies suggest that the SARS-CoV-2 virus is infectious in experimentally produced aerosols for more than one hour. However, the absence of a large-scale association between regional outbreaks and weather-influenced virus-laden speech-generated aerosol characteristics such as settling time and viral viability makes it challenging for policy making on appropriate infection control measures. Here we investigate the correlation between the time series of daily infections and of settling times of virus-containing particles produced by speaking. Characteristic droplet settling times determined by the Stokes–Cunningham equation as influenced by daily weather conditions were estimated based on local meteorological data. Daily infection data were calibrated from local reported cases based on established infection timeframes. Linear regression, vector autoregression, simple recurrent neural network, and long short-term memory models predict transmission rates within one-sigma intervals using the settling times and viral viability over 5 days before the day of prediction. Corroborating with previous health science studies, from the perspective of meteorology-modulated transmission, our results strengthen that airborne aerosol transmission is an important pathway for the spread of SARS-CoV-2. Furthermore, historical weather data can improve the prediction accuracy of infection spreading rates.


Item Type:Article
Related URLs:
URLURL TypeDescription
https://doi.org/10.1039/D1EA00013FDOIArticle
https://www.rsc.org/suppdata/d1/ea/d1ea00013f/d1ea00013f1.pdfPublisherSupplementary information
ORCID:
AuthorORCID
Gu, Alan Y.0000-0001-8095-3634
Zhu, Yanzhe0000-0002-2260-1830
Li, Jing0000-0003-0639-9422
Hoffmann, Michael R.0000-0001-6495-1946
Additional Information:© 2021 The Author(s). Published by the Royal Society of Chemistry. This article is licensed under a Creative Commons Attribution 3.0 Unported Licence. Submitted 19 Feb 2021. Accepted 25 Nov 2021. First published 08 Dec 2021. This work is supported by the Bill & Melinda Gates Foundation Investment Grant INV-018569. The authors thank Paul Dabisch at National Biodefense Analysis and Countermeasures Center for sharing his insights on SARS-CoV-2 viability. The authors would like to acknowledge Richard Flagan for helpful discussions.
Group:COVID-19
Funders:
Funding AgencyGrant Number
Bill and Melinda Gates FoundationINV-018569
Issue or Number:1
DOI:10.1039/d1ea00013f
Record Number:CaltechAUTHORS:20211209-456403000
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20211209-456403000
Official Citation:Speech-generated aerosol settling times and viral viability can improve COVID-19 transmission prediction. Environ. Sci.: Atmos., 2022, 2, 34-45; DOI: 10.1039/d1ea00013f
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:112326
Collection:CaltechAUTHORS
Deposited By: George Porter
Deposited On:10 Dec 2021 20:32
Last Modified:01 Feb 2022 17:00

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