Quantitative risk assessment of COVID-19 aerosol transmission indoors: a mechanistic stochastic web application

Applications of Quantitative Microbial Risk Assessment to Respiratory Pathogens and Implications for Uptake in Policy: A State-of-the-Science Review

BACKGROUND

Respiratory tract infections are major contributors to the global disease burden. Quantitative microbial risk assessment (QMRA) holds potential as a rapidly deployable framework to understand respiratory pathogen transmission and inform policy on infection control.

OBJECTIVES

The goal of this paper was to evaluate, motivate, and inform further development of the use of QMRA as a rapid tool to understand the transmission of respiratory pathogens and improve the evidence base for infection control policies.

METHODS

We conducted a literature review to identify peer-reviewed studies of complete QMRA frameworks on aerosol inhalation or contact transmission of respiratory pathogens. From each of the identified studies, we extracted and summarized information on the applied exposure model approaches, dose-response models, and parameter values, including risk characterization. Finally, we reviewed linkages between model outcomes and policy.

RESULTS

We identified 93 studies conducted in 16 different countries with complete QMRA frameworks for diverse respiratory pathogens, including SARS-CoV-2, Legionella spp., Staphylococcus aureus, influenza, and Bacillus anthracis. Six distinct exposure models were identified across diverse and complex transmission pathways. In 57 studies, exposure model frameworks were informed by their ability to model the efficacy of potential interventions. Among interventions, masking, ventilation, social distancing, and other environmental source controls were commonly assessed. Pathogen concentration, aerosol concentration, and partitioning coefficient were influential exposure parameters as identified by sensitivity analysis. Most (84%, n = 78 ) studies presented policy-relevant content including a) determining disease burden to call for policy intervention, b) determining risk-based threshold values for regulations, c) informing intervention and control strategies, and d) making recommendations and suggestions for QMRA application in policy.

CONCLUSIONS

We identified needs to further the development of QMRA frameworks for respiratory pathogens that prioritize appropriate aerosol exposure modeling approaches, consider trade-offs between model validity and complexity, and incorporate research that strengthens confidence in QMRA results. https://doi.org/10.1289/EHP12695.

The Wells-Riley model revisited: Randomness, heterogeneity, and transient behaviours

The Wells-Riley model has been widely used to estimate airborne infection risk, typically from a deterministic point of view (i.e., focusing on the average number of infections) or in terms of a per capita probability of infection. Some of its main limitations relate to considering well-mixed air, steady-state concentration of pathogen in the air, a particular amount of time for the indoor interaction, and that all individuals are homogeneous and behave equally. Here, we revisit the Wells-Riley model, providing a mathematical formalism for its stochastic version, where the number of infected individuals follows a Binomial distribution. Then, we extend the Wells-Riley methodology to consider transient behaviours, randomness, and population heterogeneity. In particular, we provide analytical solutions for the number of infections and the per capita probability of infection when: (i) susceptible individuals remain in the room after the infector leaves, (ii) the duration of the indoor interaction is random/unknown, and (iii) infectors have heterogeneous quanta production rates (or the quanta production rate of the infector is random/unknown). We illustrate the applicability of our new formulations through two case studies: infection risk due to an infectious healthcare worker (HCW) visiting a patient, and exposure during lunch for uncertain meal times in different dining settings. Our results highlight that infection risk to a susceptible who remains in the space after the infector leaves can be nonnegligible, and highlight the importance of incorporating uncertainty in the duration of the indoor interaction and the infectivity of the infector when estimating risk.

A critical review of research methodologies for COVID-19 transmission in indoor built environment

The Coronavirus Disease 2019 (COVID-19) has caused massive losses for the global economy. Scholars have used different methods to study the transmission mode and influencing factors of the virus to find effective methods to provide people with a healthy built environment. However, these studies arrived at different or even contradictory conclusions. This review presents the main research methodologies utilized in this field, summarizes the main investigation methods, and critically discusses their related conclusions. Data statistical analysis, sample collection, simulation models, and replication transmission scenarios are the main research methods. The summarized conclusion for prevention from all reviewed papers are: adequate ventilation and proper location of return air vents, proper use of personal protective equipment, as well as the reasonable and strict enforcement of policies are the main methods for reducing the transmission. Recommendations including standardized databases, causation clarification, rigorous experiment design, improved simulation accuracy and verification are provided.

Molecular insights into microbial transformation of bioaerosol-derived dissolved organic matter discharged from wastewater treatment plant

Wastewater treatment plants (WWTP) are important sources of aerosol-derived dissolved organic matter (ADOM) which may threaten human health via the respiratory system. In this study, aerosols were sampled from a typical WWTP to explore the chemical molecular diversity, molecular ecological network, and potential toxicities of the ADOM in the aerosols. The high fluorescence index (>1.9) and biological index (0.66-1.17) indicated the strong autogenous microbial source characteristics of the ADOM in the WWTP. DOM and microbes in the wastewater were aerosolized due to strong agitation and bubbling in the treatment processes, and contributed to 74 % and 75 %, respectively, of the ADOM and microbes in the aerosols. The ADOM was mainly composed of CHO and CHOS accounting for 35 % and 29 % of the total number of molecules, respectively, with lignin-like (69 %) as the major constituent. 49 % of the ADOM transformations were thermodynamically limited, and intragroup transformations were easier than intergroup transformations. Bacteria in the aerosols involved in ADOM transformations exhibited both cooperative and divergent behaviors and tended to transform carbohydrate-like and amino sugar/protein-like into recalcitrant lignin-like. The microbial compositions were affected by atmosphere temperature and humidity indirectly by modulating the properties of ADOM. Tannin-like, lignin-like, and unsaturated hydrocarbon-like molecules in the ADOM were primary toxicity contributors, facilitating the expression of inflammatory factors IL-β (2.2-5.4 folds), TNF-α (3.5-7.0 folds), and IL-6 (3.5-11.2 folds), respectively.

On-site airborne pathogen detection for infection risk mitigation

Human-infecting pathogens that transmit through the air pose a significant threat to public health. As a prominent instance, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that caused the COVID-19 pandemic has affected the world in an unprecedented manner over the past few years. Despite the dissipating pandemic gloom, the lessons we have learned in dealing with pathogen-laden aerosols should be thoroughly reviewed because the airborne transmission risk may have been grossly underestimated. From a bioanalytical chemistry perspective, on-site airborne pathogen detection can be an effective non-pharmaceutic intervention (NPI) strategy, with on-site airborne pathogen detection and early-stage infection risk evaluation reducing the spread of disease and enabling life-saving decisions to be made. In light of this, we summarize the recent advances in highly efficient pathogen-laden aerosol sampling approaches, bioanalytical sensing technologies, and the prospects for airborne pathogen exposure measurement and evidence-based transmission interventions. We also discuss open challenges facing general bioaerosols detection, such as handling complex aerosol samples, improving sensitivity for airborne pathogen quantification, and establishing a risk assessment system with high spatiotemporal resolution for mitigating airborne transmission risks. This review provides a multidisciplinary outlook for future opportunities to improve the on-site airborne pathogen detection techniques, thereby enhancing the preparedness for more on-site bioaerosols measurement scenarios, such as monitoring high-risk pathogens on airplanes, weaponized pathogen aerosols, influenza variants at the workplace, and pollutant correlated with sick building syndromes.

Evaluation of indoor environmental quality, personal cumulative exposure dose, and aerosol transmission risk levels inside urban buses in Dalian, China

The transmission of pollutants in buses has an important impact on personal exposure to airborne particles and spread of the COVID-19 epidemic in enclosed spaces. We conducted the following real-time field measurements inside buses: CO₂, airborne particle concentration, temperature, and relative humidity data during peak and off-peak hours in spring and autumn. Correlation analysis was adopted to evaluate the dominant factors influencing CO₂ and particle mass concentrations in the vehicle. The cumulative personal exposure dose to particulate matter and reproduction number were calculated for passengers on a one-way trip. The results showed the in-cabin CO₂ concentrations, with 22.11% and 21.27% of the total time exceeding 1000 ppm in spring and autumn respectively. In-cabin PM_2.5 mass concentration exceeded 35 μm/m³ by 57.35% and 86.42% in spring and autumn, respectively. CO₂ concentration and the cumulative number of passengers were approximately linearly correlated in both seasons, with R value up to 0.896. The cumulative number of passengers had the most impact on PM_2.5 mass concentration among tested parameters. The cumulative personal exposure dose to PM_2.5 during a one-way trip in autumn was up to 43.13 μg. The average reproductive number throughout the one-way trip was 0.26; it was 0.57 under the assumed extreme environment. The results of this study provide an important basic theoretical guidance for the optimization of ventilation system design and operation strategies aimed at reducing multi-pollutant integrated health exposure and airborne particle infection (such as SARS-CoV-2) risks.