scholarly journals A spatiotemporally resolved infection risk model for airborne transmission of COVID-19 variants in indoor spaces

2021 ◽  
pp. 152592
Author(s):  
Xiangdong Li ◽  
Daniel Lester ◽  
Gary Rosengarten ◽  
Craig Aboltins ◽  
Milan Patel ◽  
...  
Keyword(s):  
Risk Model ◽  
Infection Risk ◽  
Airborne Transmission ◽  
Indoor Spaces

scholarly journals Simulation-Based Study on the COVID-19 Airborne Transmission in a Restaurant

2020 ◽  
Author(s):  
Han Liu ◽  
Sida He ◽  
Lian Shen ◽  
Jiarong Hong
Keyword(s):  
Preventive Measures ◽  
Strong Support ◽  
Infection Risk ◽  
Exposure Index ◽  
Reverse Time ◽  
Aerosol Transport ◽  
Airborne Transmission ◽  
Local Flow ◽  
Airborne Infection ◽  
Aerosol Exposure

COVID-19 has shown a high potential of transmission via virus-carrying aerosols as supported by growing evidence. However, detailed investigations that draw direct links between aerosol transport and virus infection are still lacking. To fill in the gap, we conducted a systematic computational fluid dynamics (CFD)-based investigation of indoor air flow and the associated aerosol transport in a restaurant setting, where likely cases of airborne infection of COVID-19 caused by asymptomatic individuals were widely reported by the media. We employed an advanced in-house large eddy simulation (LES) solver and other cutting-edge numerical methods to resolve complex indoor processes simultaneously, including turbulence, flow–aerosol interplay, thermal effect, and the filtration effect by air conditioners. Using the aerosol exposure index derived from the simulation, we are able to provide a spatial map of the airborne infection risk under different settings. Our results have shown a remarkable direct linkage between regions of high aerosol exposure index and the reported infection patterns in the restaurant, providing strong support to the airborne transmission occurring in this widely-reported incidence. Using flow structure analysis and reverse-time tracing of aerosol trajectories, we are able to further pinpoint the influence of environmental parameters on the infection risks and highlight the needs for more effective preventive measures, e.g., placement of shielding according to the local flow patterns. Our research, thus, has demonstrated the capability and value of high-fidelity CFD tools for airborne infection risk assessment and the development of effective preventive measures.

Assessing coughing-induced influenza droplet transmission and implications for infection risk control

2015 ◽  
Vol 144 (2) ◽  
pp. 333-345 ◽  
Author(s):  
Y.-H. CHENG ◽  
C.-H. WANG ◽  
S.-H. YOU ◽  
N.-H. HSIEH ◽  
W.-Y. CHEN ◽  
...  
Keyword(s):  
Respiratory Tract ◽  
Risk Model ◽  
Control Measure ◽  
Influenza Infection ◽  
Infection Risk ◽  
Transmission Dynamics ◽  
Human Respiratory Tract ◽  
Host Interactions ◽  
And Control ◽  
Respiratory Droplets

SUMMARYIndoor transmission of respiratory droplets bearing influenza within humans poses high risks to respiratory function deterioration and death. Therefore, we aimed to develop a framework for quantifying the influenza infection risk based on the relationships between inhaled/exhaled respiratory droplets and airborne transmission dynamics in a ventilated airspace. An experiment was conducted to measure the size distribution of influenza-containing droplets produced by coughing for a better understanding of potential influenza spread. Here we integrated influenza population transmission dynamics, a human respiratory tract model, and a control measure approach to examine the indoor environment–virus–host interactions. A probabilistic risk model was implemented to assess size-specific infection risk for potentially transmissible influenza droplets indoors. Our results found that there was a 50% probability of the basic reproduction number (R0) exceeding 1 for small-size influenza droplets of 0·3–0·4 µm, implicating a potentially high indoor infection risk to humans. However, a combination of public health interventions with enhanced ventilation could substantially contain indoor influenza infection. Moreover, the present dynamic simulation and control measure assessment provide insights into why indoor transmissible influenza droplet-induced infection is occurring not only in upper lung regions but also in the lower respiratory tract, not normally considered at infection risk.

scholarly journals Development and Validation of an Infection Risk Model for Bacterial Canker of Kiwifruit, Using a Multiplication and Dispersal Concept for Forecasting Bacterial Diseases

2017 ◽  
Vol 107 (2) ◽  
pp. 184-191 ◽  
Author(s):  
R. M. Beresford ◽  
J. L. Tyson ◽  
W. R. Henshall
Keyword(s):  
Pseudomonas Syringae ◽  
Risk Model ◽  
Risk Index ◽  
Infection Risk ◽  
Bacterial Disease ◽  
Disease Prediction ◽  
Risk Indicator ◽  
Bacterial Canker ◽  
Temperature Function ◽  
Bacterial Diseases

A weather-based disease prediction model for bacterial canker of kiwifruit (known worldwide as Psa; Pseudomonas syringae pv. actinidiae biovar 3) was developed using a new mechanistic scheme for bacterial disease forecasters, the multiplication and dispersal concept. Bacterial multiplication is estimated from a temperature function, the M index, accumulated from hourly air temperature over 3 days for hours when the leaf canopy is wet. Rainfall provides free water to move inoculum to infection sites, and the daily risk indicator, the R index, is the 3-day accumulation of the M index output on days with total rainfall >1 mm; otherwise, R is zero. The model was field-tested using potted kiwifruit trap plants exposed for discrete periods in infected kiwifruit orchards to identify when leaf infection occurred. In a 9-week study during spring, the R index predicted leaf-spot intensity with high accuracy (R2 = 93%) and, in an 82-week seasonal accuracy study, prediction of infection incidence was most accurate from spring to late summer and lower during other times. To implement the risk model for the New Zealand kiwifruit industry, a modified risk index, R’, used relative humidity (RH) >81% instead of wetness, so that 2- and 6-day weather forecasts of RH could be used. Risk index values were affected by the shape of the temperature function and an alternative ‘low temperature’ function for the M index was identified that could be used in climates in which high temperatures are known to limit Psa development during some parts of the year. This study has shown how infection risk for bacterial diseases can be conceptualized as separate processes for temperature-dependent bacterial multiplication and rain-dependent dispersal and infection. This concept has potentially wide application for bacterial disease prediction in the same way that the infection monocycle concept has had for fungal disease prediction.

scholarly journals The role of classroom volume, natural ventilation and voice reduction in transmission risk of SARS-CoV2 in schools

2021 ◽  
Author(s):  
Alessandro Zivelonghi ◽  
Massimo Lai
Keyword(s):  
Natural Ventilation ◽  
Risk Model ◽  
Emission Rate ◽  
Winter Season ◽  
Transmission Risk ◽  
Outdoor Temperature ◽  
Airborne Transmission ◽  
Air Exchange Rate ◽  
Theoretical Risk

School classrooms are enclosed settings where students and teachers spend prolonged periods of time and therefore risky environments for airborne transmission of SARS-CoV2. While countries worldwide have been pursuing different school reopening strategies, most countries are planning to keep schools open during the whole winter season 2020/21. This poses a controversial issue: ventilation of classrooms (an essential mitigation factor for airborne transmission) is expected to sensibly decrease due to outdoor temperatures getting colder and regulators going to allow less restrictive policies on windows closure. Moreover, most schools are not provided with mechanical ventilation/filtartion systems to date. Fundamental and urgent questions to be addressed are therefore: to which extent can we contain the airborne transmission risk in schools through natural ventilation only? can we reduce the airborne risk with easy to implement countermeasures like lowering the speaking volume? To answer these questions a theoretical risk model based on the emission rate of viral charge from an infective subject has been developed extending previous models for tubercolosis and influenza. The case of an infective student or an infective teacher in a classroom, as well as an infective teacher with microphone have been investigated and compared with infection thresholds for different group sizes. The model also considers the influence of indoor-outdoor temperature difference on the air exchange rate, which seems to be particularly strong during winter.

scholarly journals Beyond well-mixed: a simple probabilistic model of airborne disease transmission in indoor spaces

2021 ◽  
Author(s):  
Sijian Tan ◽  
Zhihang Zhang ◽  
Kevin Maki ◽  
Krzysztof J. Fidkowski ◽  
Jesse Capecelatro
Keyword(s):  
Disease Transmission ◽  
Risk Model ◽  
Ventilation Rate ◽  
Turbulent Dispersion ◽  
Balance Model ◽  
Wide Range ◽  
Ventilation Rates ◽  
Airborne Disease ◽  
Droplet Nuclei ◽  
Indoor Spaces

AbstractWe develop a simple model for assessing risk of airborne disease transmission that accounts for non-uniform mixing in indoor spaces and is compatible with existing epidemiological models. A database containing 174 high-resolution simulations of airflow in classrooms, lecture halls, and buses is generated and used to quantify the spatial distribution of expiratory droplet nuclei for a wide range of ventilation rates, exposure times, and room configurations. Imperfect mixing due to obstructions, buoyancy, and turbulent dispersion results in concentration fields with significant variance. The spatial non-uniformity is found to be accurately described by a shifted lognormal distribution. A well-mixed mass balance model is used to predict the mean, and the standard deviation is parameterized based on ventilation rate and room geometry. When employed in a dose-response function risk model, infection probability can be estimated considering spatial heterogeneity that contributes to both short- and long-range transmission.

scholarly journals Analytic modeling and risk assessment of aerial transmission of SARS-CoV-2 virus through vaping expirations in shared micro-environments

2021 ◽  
Author(s):  
Roberto Sussman ◽  
Eliana Golberstein ◽  
Riccardo Polosa
Keyword(s):  
Mechanical Ventilation ◽  
Risk Model ◽  
Case Scenario ◽  
Direct Exposure ◽  
Containment Measures ◽  
Nicotine Consumption ◽  
Contagion Risk ◽  
Droplet Nuclei ◽  
Respiratory Droplets ◽  
Indoor Spaces

Abstract Background. E-cigarettes are an important harm reduction tool that provides smokers an alternative for nicotine consumption that is much safer than smoking. It is important to asses its safety under preventive and containment measures undertaken during the COVID-19 pandemic. Methods. We develop a theoretical risk model to assess the contagion risk by aerial transmission of the SARS-CoV-2 virus carried by e–cigarette aerosol (ECA) in shared indoor spaces, a home and restaurant scenarios, with natural and mechanical ventilation, with and without face masks. We also provide the theoretical elements to explain the visibility of exhaled ECA, which has important safety implications. Results. In a home or restaurant scenarios bystanders exposed to ECA expirations by an infectious vaper (and not wearing face masks) face a 1% increase of risk of contagion with respect to a “control case” scenario defined by exclusively rest breathing without vaping. This relative added risk becomes 5 - 17% for high intensity vaping, 44 - 176% and over 260% for speaking for various periods or coughing (all without vaping). Mechanical ventilation significantly decrease infective emissions but keep the same proportionality in risk percentages. Face masks of common usage effectively protect wearers from respiratory droplets and droplet nuclei possibly emitted by mask-less vapers as long as they avoid direct exposure to the visible exhaled vaping jet. Conclusions. Vaping emissions in shared indoor spaces involve only a minuscule added risk of COVID-19 contagion with respect to the already existing (unavoidable) risk from continuous breathing, significantly less than speaking or coughing. Protection of bystanders from this contagion does not require extra preventive measures besides those already recommended (1.5 meters separation and wearing face masks).

scholarly journals A new apple scab risk model that integrates ascospore release infection risk and susceptible leaf area

2004 ◽  
Vol 57 ◽  
pp. 20-24 ◽  
Author(s):  
R.M Beresford ◽  
W.R. Henshall ◽  
J.W. Palmer
Keyword(s):  
Leaf Area ◽  
Risk Model ◽  
Venturia Inaequalis ◽  
Apple Scab ◽  
Black Spot ◽  
Infection Risk ◽  
Weather Data ◽  
Scab Control ◽  
Ascospore Release ◽  
Maturation Rate

A new model has been developed for assessing daytoday variation in risk of infection of apples by Venturia inaequalis the scab or black spot pathogen The model comprises three components ascospore availability wetnessbased infection risk based on Mills periods and susceptible leaf area The ascospore and wetnessbased infection risk components were adapted from previous models whereas the susceptible leaf area component is new When the model used weather data from Hawkes Bay and Nelson in spring 2003 the predicted risk incidence was determined mostly by wetnessbased infection risk but the magnitude of risk periods was greatly influenced by predicted ascospore release The susceptible leaf area component predicted a hitherto unidentified increase in infection risk after the peak in ascospore maturation rate had occurred The model is intended to assist in fungicide selection and timing for scab control in New Zealand apples but needs to be field tested before implementation

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