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1.
Indoor Air ; 32(1): e12940, 2022 01.
Article in English | MEDLINE | ID: mdl-35048430

ABSTRACT

This article presents results from an experimental study to ascertain the transmissibility of the SARS-CoV-2 virus between rooms in a building that are connected by a central ventilation system. Respiratory droplet surrogates made of mucus and virus mimics were released in one room in a test building, and measurements of concentration levels were made in other rooms connected via the ventilation system. The paper presents experimental results for different ventilation system configurations, including ventilation rate, filtration level (up to MERV-13), and fractional outdoor air intake. The most important finding is that respiratory droplets can and do transit through central ventilation systems, suggesting a mechanism for viral transmission (and COVID-19 specifically) within the built environment in reasonable agreement with well-mixed models. We also find the deposition of small droplets (0.5-4 µm) on room walls to be negligibly small.


Subject(s)
Air Microbiology , Air Pollution, Indoor , COVID-19 , Respiratory Aerosols and Droplets/virology , Ventilation , COVID-19/transmission , Humans , SARS-CoV-2
2.
Build Environ ; 197: 107633, 2021 Jun 15.
Article in English | MEDLINE | ID: mdl-33531734

ABSTRACT

The COVID-19 pandemic has raised concern of viral spread within buildings. Although near-field transmission and infectious spread within individual rooms are well studied, the impact of aerosolized spread of SARS-CoV-2 via air handling systems within multiroom buildings remains unexplored. This study evaluates the concentrations and probabilities of infection for both building interior and exterior exposure sources using a well-mixed model in a multiroom building served by a central air handling system (without packaged terminal air conditioning). In particular, we compare the influence of filtration, air change rates, and the fraction of outdoor air. When the air supplied to the rooms comprises both outdoor air and recirculated air, we find filtration lowers the concentration and probability of infection the most in connected rooms. We find that increasing the air change rate removes virus from the source room faster but also increases the rate of exposure in connected rooms. Therefore, slower air change rates reduce infectivity in connected rooms at shorter durations. We further find that increasing the fraction of virus-free outdoor air is helpful, unless outdoor air is infective in which case pathogen exposure inside persists for hours after a short-term release. Increasing the outdoor air to 33% or the filter to MERV-13 decreases the infectivity in the connected rooms by 19% or 93% respectively, relative to a MERV-8 filter with 9% outdoor air based on 100 quanta/h of 5 µm droplets, a breathing rate of 0.48 m3/h, and the building dimensions and air handling system considered.

3.
Nucleic Acids Res ; 38(Database issue): D443-7, 2010 Jan.
Article in English | MEDLINE | ID: mdl-19884132

ABSTRACT

FlyTF (http://www.flytf.org) is a database of computationally predicted and/or experimentally verified site-specific transcription factors (TFs) in the fruit fly Drosophila melanogaster. The manual classification of TFs in the initial version of FlyTF that concentrated primarily on the DNA-binding characteristics of the proteins has now been extended to a more fine-grained annotation of both DNA binding and regulatory properties in the new release. Furthermore, experimental evidence from the literature was classified into a defined vocabulary, and in collaboration with FlyBase, translated into Gene Ontology (GO) annotation. While our GO annotations will also be available through FlyBase as they will be incorporated into the genes' official GO annotation in the future, the entire evidence used for classification including computational predictions and quotes from the literature can be accessed through FlyTF. The FlyTF website now builds upon the InterMine framework, which provides experimental and computational biologists with powerful search and filter functionality, list management tools and access to genomic information associated with the TFs.


Subject(s)
Computational Biology/methods , Databases, Genetic , Databases, Nucleic Acid , Drosophila Proteins/chemistry , Drosophila melanogaster/genetics , Drosophila melanogaster/physiology , Animals , Computational Biology/trends , DNA/genetics , Databases, Protein , Information Storage and Retrieval/methods , Internet , Protein Structure, Tertiary , Software , Transcription Factors/genetics , Transcription, Genetic
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