Action Levels for SARS-CoV-2 in Air: Preliminary Approach

Evaluating infection risks and importance of hand hygiene during the household laundry process using a quantitative microbial risk assessment approach

BACKGROUND

Contaminated laundry contributes to infectious disease spread in residential and home health care settings. The objectives were to (1) evaluate pathogen transmission risks for individuals doing laundry, and (2) compare hand hygiene timing to reduce risks.

METHODS

A quantitative microbial risk assessment using experimental data from a laundry washing effectiveness study was applied to estimate infection risks from SARS-CoV-2, rotavirus, norovirus, nontyphoidal Salmonella, and Escherichia coli in 4 laundry scenarios: 1 baseline scenario (no hand hygiene event) and 3 hand hygiene scenarios (scenario 1: after moving dirty clothes to the washing machine, scenario 2: after moving washed clothes to the dryer, and scenario 3: hand hygiene events following scenario 1 and 2).

RESULTS

The average infection risks for the baseline scenario were all greater than 2 common risk thresholds (1.0×10-6and 1.0×10-4). For all organisms, scenario 1 yielded greater risk reductions (39.95%-99.86%) than scenario 2 (1.35%-55.25%). Scenario 3 further reduced risk, achieving 1.0×10-6(SARS-CoV-2) and 1.0×10-4risk thresholds (norovirus and E. coli).

CONCLUSIONS

The modeled results suggest individuals should reduce hand-to-facial orifice (eyes, nose, and mouth) contacts and conduct proper hand hygiene when handling contaminated garments. More empirical data are needed to confirm the estimated risks.

DATA AVAILABILITY STATEMENT

The data and code that support the findings of this study can be retrieved via a Creative Commons Zero v1.0 Universal license in GitHub at https://github.com/yhjung1231/Laundry-QMRAproject-2022.git DOI: http://doi.org/10.5281/zenodo.7122065.

Quantitative Microbial Risk Assessment of Contracting COVID-19 Derived from Measured and Simulated Aerosol Particle Transmission in Aircraft Cabins

BACKGROUND

SARS-CoV-2 can be effectively transmitted between individuals located in close proximity to each other for extended durations. Aircraft provide such conditions. Although high attack rates during flights were reported, little was known about the risk levels of aerosol transmission of SARS-CoV-2 in aircraft cabins.

OBJECTIVES

The major objective was to estimate the risk of contracting COVID-19 from transmission of aerosol particles in aircraft cabins.

METHODS

In two single-aisle and one twin-aisle aircraft, dispersion of generated aerosol particles over a seven-row economy class cabin section was measured under cruise and taxi conditions and simulated with a computational fluid dynamic model under cruise conditions. Using the aerosol particle dispersion data, a quantitative microbial risk assessment was conducted for scenarios with an asymptomatic infectious person expelling aerosol particles by breathing and speaking. Effects of flight conditions were evaluated using generalized additive mixed models.

RESULTS

Aerosol particle concentration decreased with increasing distance from the infectious person, and this decrease varied with direction. On a typical flight with an average shedder, estimated mean risk of contracting COVID-19 ranged from 1.3 × 10 - 3 to 9.0 × 10 - 2 . Risk increased to 7.7 × 10 - 2 with a super shedder (< 3 % of cases) on a long flight. Risks increased with increasing flight duration: 2-23 cruise flights of typical duration and 2-10 flights of longer duration resulted in at least 1 case of COVID-19 due to onboard aerosol transmission by one average shedder, and in the case of one super shedder, at least 1 case in 1-3 flights of typical duration cruise and 1 flight of longer duration.

DISCUSSION

Our findings indicate that the risk of contracting COVID-19 by aerosol transmission in an aircraft cabin is low, but it will not be zero. Testing before boarding may help reduce the chance of a (super)shedder boarding an aircraft and mask use further reduces aerosol transmission in the aircraft cabin. https://doi.org/10.1289/EHP11495.

Risk assessment of banknotes as a fomite of SARS-CoV-2 in cash payment transactions

The COVID 19 pandemic has triggered concerns and assumptions globally about transmission of the SARS-CoV-2 virus via cash transactions. This paper assesses the risk of contracting COVID-19 through exposure to SARS-CoV-2 via cash acting as a fomite in payment transactions. A quantitative microbial risk assessment was conducted for a scenario assuming an infectious person at the onset of symptoms, when virion concentrations in coughed droplets are at their highest. This person then contaminates a banknote by coughing on it and immediately hands it over to another person, who might then be infected by transferring the virions with a finger from the contaminated banknote to a facial mucous membrane. The scenario considered transfer efficiency of virions on the banknote to fingertips when droplets were still wet and after having dried up and subsequently being touched by finger printing or rubbing the object. Accounting for the likelihood of the scenario to occur by considering (1) a local prevalence of 100 COVID-19 cases/100,000 persons, (2) a maximum of about one-fifth of infected persons transmit high virus loads, and (3) the numbers of cash transactions/person/day, the risk of contracting COVID-19 via person-to-person cash transactions was estimated to be much lower than once per 39,000 days (107 years) for a single person. In the general populace, there will be a maximum of 2.6 expected cases/100,000 persons/day. The risk for a cashier at an average point of sale was estimated to be much less than once per 430 working days (21 months). The depicted scenario is a rare event, therefore, for a single person, the risk of contracting COVID-19 via person-to-person cash transactions is very low. At a point of sale, the risk to the cashier proportionally increases but it is still low.

Zonal modeling of air distribution impact on the long-range airborne transmission risk of SARS-CoV-2

A widely used analytical model to quantitatively assess airborne infection risk is the Wells-Riley model which is limited to complete air mixing in a single zone. However, this assumption tends not to be feasible (or reality) for many situations. This study aimed to extend the Wells-Riley model so that the infection risk can be calculated in spaces where complete mixing is not present. Some more advanced ventilation concepts create either two horizontally divided air zones in spaces as displacement ventilation or the space may be divided into two vertical zones by downward plane jet as in protective-zone ventilation systems. This is done by evaluating the time-dependent distribution of infectious quanta in each zone and by solving the coupled system of differential equations based on the zonal quanta concentrations. This model introduces a novel approach by estimating the interzonal mixing factor based on previous experimental data for three types of ventilation systems: incomplete mixing ventilation, displacement ventilation, and protective zone ventilation. The modeling approach is applied to a room with one infected and one susceptible person present. The results show that using the Wells-Riley model based on the assumption of completely air mixing may considerably overestimate or underestimate the long-range airborne infection risk in rooms where air distribution is different than complete mixing, such as displacement ventilation, protected zone ventilation, warm air supplied from the ceiling, etc. Therefore, in spaces with non-uniform air distribution, a zonal modeling approach should be preferred in analytical models compared to the conventional single-zone Wells-Riley models when assessing long-range airborne transmission risk of infectious respiratory diseases.

A Quantitative Risk Estimation Platform for Indoor Aerosol Transmission of COVID-19

Aerosol transmission has played a significant role in the transmission of COVID-19 disease worldwide. We developed a COVID-19 aerosol transmission risk estimation model to better understand how key parameters associated with indoor spaces and infector emissions affect inhaled deposited dose of aerosol particles that convey the SARS-CoV-2 virus. The model calculates the concentration of size-resolved, virus-laden aerosol particles in well-mixed indoor air challenged by emissions from an index case(s). The model uses a mechanistic approach, accounting for particle emission dynamics, particle deposition to indoor surfaces, ventilation rate, and single-zone filtration. The novelty of this model relates to the concept of "inhaled & deposited dose" in the respiratory system of receptors linked to a dose-response curve for human coronavirus HCoV-229E. We estimated the volume of inhaled & deposited dose of particles in the 0.5-4 μm range expressed in picoliters (pL) in a well-documented COVID-19 outbreak in restaurant X in Guangzhou China. We anchored the attack rate with the dose-response curve of HCoV-229E which provides a preliminary estimate of the average SARS-CoV-2 dose per person, expressed in plaque forming units (PFUs). For a reasonable emission scenario, we estimate approximately three PFU per pL deposited, yielding roughly 10 PFUs deposited in the respiratory system of those infected in restaurant X. To explore the model's utility, we tested it with four COVID-19 outbreaks. The risk estimates from the model fit reasonably well with the reported number of confirmed cases given available metadata from the outbreaks and uncertainties associated with model assumptions.

Monitoring SARS-CoV-2 in air and on surfaces and estimating infection risk in buildings and buses on a university campus

BACKGROUND

Evidence is needed on the presence of SARS-CoV-2 in various types of environmental samples and on the estimated transmission risks in non-healthcare settings on campus.

OBJECTIVES

The objective of this research was to collect data on SARS-CoV-2 viral load and to examine potential infection risks of people exposed to the virus in publicly accessible non-healthcare environments on a university campus.

METHODS

Air and surface samples were collected using wetted wall cyclone bioaerosol samplers and swab kits, respectively, in a longitudinal environmental surveillance program from August 2020 until April 2021 on the University of Michigan Ann Arbor campus. Quantitative rRT-PCR with primers and probes targeting gene N1 were used for SARS-CoV-2 RNA quantification. The RNA concentrations were used to estimate the probability of infection by quantitative microbial risk assessment modeling and Monte-Carlo simulation.

RESULTS

In total, 256 air samples and 517 surface samples were collected during the study period, among which positive rates were 1.6% and 1.4%, respectively. Point-biserial correlation showed that the total case number on campus was significantly higher in weeks with positive environmental samples than in non-positive weeks (p = 0.001). The estimated probability of infection was about 1 per 100 exposures to SARS-CoV-2-laden aerosols through inhalation and as high as 1 per 100,000 exposures from contacting contaminated surfaces in simulated scenarios.

SIGNIFICANCE

Viral shedding was demonstrated by the detection of viral RNA in multiple air and surface samples on a university campus. The low overall positivity rate indicated that the risk of exposure to SARS-CoV-2 at monitored locations was low. Risk modeling results suggest that inhalation is the predominant route of exposure compared to surface contact, which emphasizes the importance of protecting individuals from airborne transmission of SARS-CoV-2 and potentially other respiratory infectious diseases.

IMPACT

Given the reoccurring epidemics caused by highly infectious respiratory viruses in recent years, our manuscript reinforces the importance of monitoring environmental transmission by the simultaneous sampling and integration of multiple environmental surveillance matrices for modeling and risk assessment.

Effects of face masks and ventilation on the risk of SARS-CoV-2 respiratory transmission in public toilets: a quantitative microbial risk assessment

Public toilets may increase the risk of COVID-19 infection via airborne transmission; however, related research is limited. We aimed to estimate SARS-CoV-2 infection risk through respiratory transmission using a quantitative microbial risk assessment framework by retrieving SARS-CoV-2 concentrations from the swab tests of 251 Thai patients. Three virus-generating scenarios were investigated: an infector breathing, breathing with a cough, and breathing with a sneeze. The infection risk (95th percentile) was as high as 10^-1 with breathing and increased to 1 with a cough or a sneeze. No significant gender differences for toilet users (receptors) were noted. The highest risk scenario, namely breathing with a sneeze, was further evaluated for risk mitigation measures. Mitigation to a lower risk under 10^-3 succeeded only when the infector and the receptor both wore N95 respirators or surgical masks. Ventilation of up to 20 air changes per hour (ACH) did not decrease the risk. However, an extended waiting time of 10 min between an infector and a receptor resulted in approximately 1.0-log₁₀ further risk reduction when both wore masks with the WHO-recommended 12 ACH. The volume of expelled droplets, virus concentrations, and receptor dwell time were identified as the main contributors to transmission risk.

Estimating the impact of indoor relative humidity on SARS-CoV-2 airborne transmission risk using a new modification of the Wells-Riley model

A novel modified version of the Wells-Riley model was used to estimate the impact of relative humidity (RH) on the removal of respiratory droplets containing the SARS-CoV-2 virus by deposition through gravitational settling and its inactivation by biological decay; the effect of RH on susceptibility to SARS-CoV-2 was not considered. These effects were compared with the removal achieved by increased ventilation rate with outdoor air. Modeling was performed assuming that the infected person talked continuously for 60 and 120 min. The results of modeling showed that the relative impact of RH on the infection risk depended on the ventilation rate and the size range of virus-laden droplets. A ventilation rate of 0.5 ACH, the change of RH between 20% and 53% was predicted to have a small effect on the infection risk, while at a ventilation rate of 6 ACH this change had nearly no effect. On the contrary, increasing the ventilation rate from 0.5 ACH to 6 ACH was predicted to decrease the infection risk by half which is remarkably larger effect compared with that predicted for RH. It is thus concluded that increasing the ventilation rate is more beneficial for reducing the airborne levels of SARS-CoV-2 than changing indoor RH.

PRACTICAL IMPLICATIONS

The present results show that humidification to moderate levels of 40%-60% RH should not be expected to provide a significant reduction in infection risk caused by SARS-CoV-2, hence installing and running humidifiers may not be an efficient solution to reduce the risk of COVID-19 disease in indoor spaces. The results do however confirm that ventilation has a key role in controlling SARS-CoV-2 virus concentration in the air providing considerably higher benefits. The modified model developed in the present work can be used by public health experts, engineers, and epidemiologists when selecting different measures to reduce the infection risk from SARS-CoV-2 indoors allowing informed decisions concerning indoor environmental control.

Modeling the impacts of physical distancing and other exposure determinants on aerosol transmission

Minimization of airborne virus transmission has become increasingly important due to pandemic and endemic infectious respiratory diseases. Physical distancing is a frequently advocated control measure, but the proximity-based transmission it is intended to control is challenging to incorporate into generalized, ventilation-based models. We utilize a size-dependent aerosol release model with turbulent dispersion to assess the impact of direct, near-field transport in conjunction with changes in ventilation, exposure duration, exhalation/inhalation rates, and masks. We demonstrate this model on indoor and outdoor scenarios to estimate the relative impacts on infection risk. The model can be expressed as a product of six multiplicative factors that may be used to identify opportunities for risk reduction. The additive nature of the short-range (proximity) and long-range (background) transmission components of the aerosol transport factor implies that they must be minimized simultaneously. Indoor simulations showed that close physical distances attenuated the impact of most other risk reduction factors. Increasing ventilation resulted in a 17-fold risk decrease at further physical distances but only a 6-fold decrease at shorter distances. Distance, emission rate, and duration also had large impacts on risk (11-65-fold), while air direction and inhalation rate had lower risk impacts (3-4-fold range). Surgical mask and respirator models predicted higher maximum risk impacts (33- and 280-fold, respectively) than cloth masks (4-fold). Most simulations showed decreasing risk at distances > 1-2 m (3-6 ft). The risk benefit of maintaining 2-m distance vs. 1 m depended substantially on the environmental turbulence and ventilation rate. Outdoors, long-range transmission was negligible and short-range transmission was the primary determinant of risk. Temporary passing events increased risk by up to 50 times at very slow walking speeds and close passing distances, but the relative risks outdoors were still much lower than indoors. The current model assumes turbulent dispersion typical of a given room size and ventilation rate. However, calm environments or confined airflows may increase transmission risks beyond levels predicted with this turbulent model.

An opinion on the multiscale nature of Covid-19 type disease spread

Recognizing the multiscale, interdisciplinary nature of the Covid-19 transmission dynamics, we discuss some recent developments concerning an attempt to construct a disease spread model from the flow physics of infectious droplets and aerosols and the frequency of contact between susceptible individuals with the infectious aerosol cloud. Such an approach begins with the exhalation event–specific, respiratory droplet size distribution (both airborne/aerosolized and ballistic droplets), followed by tracking its evolution in the exhaled air to estimate the probability of infection and the rate constants of the disease spread model. The basic formulations and structure of submodels, experiments involved to validate those submodels, are discussed. Finally, in the context of preventive measures, respiratory droplet–face mask interactions are described.

Global Systemic Risk and Resilience for Novel Coronavirus and COVID-19

This Special Issue is dedicated to issues and challenges related to pandemic risk and resilience, with a focus on policy and operations of global systems in the COVID-19 pandemic. The cascading effects of emerging and reemerging infectious diseases to the global economy are a critical interest. Measures to confront the ongoing pandemic are an urgent need. Data analysis at regional and global scales is helping to prioritize response and resilience across locations of high risks. The risk sciences are available for addressing human health and infection risks; the evaluation of risk management strategies and tradeoffs; risk perception as it relates to information processing and receiving risk communication; and tracking system resilience as it relates to various imposed measures.