Extended short-range airborne transmission of respiratory infections

The Mediating Role of Human Mobility in Temporal-Lagged Relationships Between Risk Perception and COVID-19 Dynamics in Taiwan: Statistical Modeling for Comparing the Pre-Omicron and Omicron Eras

Background

The COVID-19 pandemic has profoundly impacted all aspects of human life for over 3 years. Understanding the evolution of public risk perception during these periods is crucial. Few studies explore the mechanisms for reducing disease transmission due to risk perception. Thus, we hypothesize that changes in human mobility play a mediating role between risk perception and the progression of the pandemic.

Objective

The study aims to explore how various forms of human mobility, including essential, nonessential, and job-related behaviors, mediate the temporal relationships between risk perception and pandemic dynamics.

Methods

We used distributed-lag linear structural equation models to compare the mediating impact of human mobility across different virus variant periods. These models examined the temporal dynamics and time-lagged effects among risk perception, changes in mobility, and virus transmission in Taiwan, focusing on two distinct periods: (1) April-August 2021 (pre-Omicron era) and (2) February-September 2022 (Omicron era).

Results

In the pre-Omicron era, our findings showed that an increase in public risk perception correlated with significant reductions in COVID-19 cases across various types of mobility within specific time frames. Specifically, we observed a decrease of 5.59 (95% CI -4.35 to -6.83) COVID-19 cases per million individuals after 7 weeks in nonessential mobility, while essential mobility demonstrated a reduction of 10.73 (95% CI -9.6030 to -11.8615) cases after 8 weeks. Additionally, job-related mobility resulted in a decrease of 3.96 (95% CI -3.5039 to -4.4254) cases after 11 weeks. However, during the Omicron era, these effects notably diminished. A reduction of 0.85 (95% CI -1.0046 to -0.6953) cases through nonessential mobility after 10 weeks and a decrease of 0.69 (95% CI -0.7827 to -0.6054) cases through essential mobility after 12 weeks were observed.

Conclusions

This study confirms that changes in mobility serve as a mediating factor between heightened risk perception and pandemic mitigation in both pre-Omicron and Omicron periods. This suggests that elevating risk perception is notably effective in impeding virus progression, especially when vaccines are unavailable or their coverage remains limited. Our findings provide significant value for health authorities in devising policies to address the global threats posed by emerging infectious diseases.

Natural and socio-environmental factors in the transmission of COVID-19: a comprehensive analysis of epidemiology and mechanisms

PURPOSE OF REVIEW

There are significant differences in the transmission rate and mortality rate of COVID-19 under environmental conditions such as seasons and climates. However, the impact of environmental factors on the role of the COVID-19 pandemic and the transmission mechanism of the SARS-CoV-2 is unclear. Therefore, a comprehensive understanding of the impact of environmental factors on COVID-19 can provide innovative insights for global epidemic prevention and control policies and COVID-19 related research. This review summarizes the evidence of the impact of different natural and social environmental factors on the transmission of COVID-19 through a comprehensive analysis of epidemiology and mechanism research. This will provide innovative inspiration for global epidemic prevention and control policies and provide reference for similar infectious diseases that may emerge in the future.

RECENT FINDINGS

Evidence reveals mechanisms by which natural environmental factors influence the transmission of COVID-19, including (i) virus survival and transport, (ii) immune system damage, (iii) inflammation, oxidative stress, and cell death, and (iiii) increasing risk of complications. All of these measures appear to be effective in controlling the spread or mortality of COVID-19: (1) reducing air pollution levels, (2) rational use of ozone disinfection and medical ozone therapy, (3) rational exposure to sunlight, (4) scientific ventilation and maintenance of indoor temperature and humidity, (5) control of population density, and (6) control of population movement. Our review indicates that with the continuous mutation of SARS-CoV-2, high temperature, high humidity, low air pollution levels, and low population density more likely to slow down the spread of the virus.

COVID-19 transmission and control in land public transport: A literature review

Land public transport is an important link within and between cities, and how to control the transmission of COVID-19 in land public transport is a critical issue in our daily lives. However, there are still many inconsistent opinions and views about the spread of SARS-CoV-2 in land public transport, which limits our ability to implement effective interventions. The purpose of this review is to overview the literature on transmission characteristics and routes of the epidemic in land public transport, as well as to investigate factors affecting its spread and provide feasible measures to mitigate the infection risk of passengers. We obtained 898 papers by searching the Web of Science, Pubmed, and WHO global COVID database by keywords, and finally selected 45 papers that can address the purpose of this review. Land public transport is a high outbreak area for COVID-19 due to characteristics like crowding, inadequate ventilation, long exposure time, and environmental closure. Different from surface touch transmission and drop spray transmission, aerosol inhalation transmission can occur not only in short distances but also in long distances. Insufficient ventilation is the most important factor influencing long-distance aerosol transmission. Other transmission factors (e.g., interpersonal distance, relative orientation, and ambient conditions) should be noticed as well, which have been summarized in this paper. To address various influencing factors, it is essential to suggest practical and efficient preventive measures. Among these, increased ventilation, particularly the fresh air (i.e., natural ventilation), has proven to effectively reduce indoor infection risk. Many preventive measures are also effective, such as enlarging social distance, avoiding face-to-face orientation, setting up physical partitions, disinfection, avoiding talking, and so on. As research on the epidemic has intensified, people have broken down many perceived barriers, but more comprehensive studies on monitoring systems and prevention measures in land public transport are still needed.

Understanding lifetime and dispersion of cough-emitted droplets in air

To understand the exact transmission routes of SARS-CoV-2 and to explore effects of time, space and indoor environment on the dynamics of droplets and aerosols, rigorous testing and observation must be conducted. In the current work, the spatial and temporal dispersions of aerosol droplets from a simulated cough were comprehensively examined over a long duration (70 min). An artificial cough generator was constructed to generate reliably repeatable respiratory ejecta. The measurements were performed at different locations in front (along the axial direction and off-axis) and behind the source in a sealed experimental enclosure. Aerosols of 0.3-10 µm (around 20% of the maximum nuclei count) were shown to persist for a very long time in a still environment, and this has a substantial implication for airborne disease transmission. The experiments demonstrated that a ventilation system could reduce the total aerosol volume and the droplet lifetime significantly. To explain the experimental observations in more detail and to understand the droplet in-air behaviour at various ambient temperatures and relative humidity, numerical simulations were performed using the Eulerian-Lagrangian approach. The simulations show that many of the small droplets remain suspended in the air over time instead of falling to the ground.

At the crossroads of epidemiology and biology: Bridging the gap between SARS-CoV-2 viral strain properties and epidemic wave characteristics

The COVID-19 pandemic has given rise to numerous articles from different scientific fields (epidemiology, virology, immunology, airflow physics …) without any effort to link these different insights. In this review, we aim to establish relationships between epidemiological data and the characteristics of the virus strain responsible for the epidemic wave concerned. We have carried out this study on the Wuhan, Alpha, Delta and Omicron strains allowing us to illustrate the evolution of the relationships we have highlighted according to these different viral strains. We addressed the following questions. 1) How can the mean infectious dose (one quantum, by definition in epidemiology) be measured and expressed as an amount of viral RNA molecules (in genome units, GU) or as a number of replicative viral particles (in plaque-forming units, PFU)? 2) How many infectious quanta are exhaled by an infected person per unit of time? 3) How many infectious quanta are exhaled, on average, integrated over the whole contagious period? 4) How do these quantities relate to the epidemic reproduction rate R as measured in epidemiology, and to the viral load, as measured by molecular biological methods? 5) How has the infectious dose evolved with the different strains of SARS-CoV-2? We make use of state-of-the-art modelling, reviewed and explained in the appendix of the article (Supplemental Information, SI), to answer these questions using data from the literature in both epidemiology and virology. We have considered the modification of these relationships according to the vaccination status of the population.

An overview of SARS-CoV-2 transmission and engineering strategies to mitigate risk

The spread of the COVID-19 pandemic has profoundly affected every aspect of our lives. To date, experts have acknowledged that airborne transmission is a key piece of the SARS-CoV-2 puzzle. Nevertheless, the exact mechanism of airborne transmission of SARS-CoV-2 remains unclear. Recent works have shown the spreading of SARS-CoV-2 through numerical modeling and experimental works, but the successful applications of engineering approaches in reducing the spread of SARS-CoV-2 are lacking. In this review, the environmental factors that influence the transmission risk of SARS-CoV-2, such as ventilation flow rates, humidity, and temperature, are discussed. Besides, additional macro and micro weather factors, regional and global transmission, and the variants of the spread of SARS-CoV-2 are also reviewed. Engineering approaches that practically reduce the risks of SARS-CoV-2 transmissions are reported. Given the complex human behavior, environmental properties, and dynamic nature of the SARS-CoV-2 virus, it is reasonable to summarize that SARS-CoV-2 may not be eradicated even with the timely implementation of interventions. Therefore, more research exploring the potential cost-effective ways to control the transmission rate of SARS-CoV-2 may be a worthwhile pursuit to moderate the current crisis.

Student close contact behavior and COVID-19 transmission in China's classrooms

Classrooms are high-risk indoor environments, so analysis of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission in classrooms is important for determining optimal interventions. Due to the absence of human behavior data, it is challenging to accurately determine virus exposure in classrooms. A wearable device for close contact behavior detection was developed, and we recorded >250,000 data points of close contact behaviors of students from grades 1 to 12. Combined with a survey on students' behaviors, we analyzed virus transmission in classrooms. Close contact rates for students were 37 ± 11% during classes and 48 ± 13% during breaks. Students in lower grades had higher close contact rates and virus transmission potential. The long-range airborne transmission route is dominant, accounting for 90 ± 3.6% and 75 ± 7.7% with and without mask wearing, respectively. During breaks, the short-range airborne route became more important, contributing 48 ± 3.1% in grades 1 to 9 (without wearing masks). Ventilation alone cannot always meet the demands of COVID-19 control; 30 m3/h/person is suggested as the threshold outdoor air ventilation rate in a classroom. This study provides scientific support for COVID-19 prevention and control in classrooms, and our proposed human behavior detection and analysis methods offer a powerful tool to understand virus transmission characteristics and can be employed in various indoor environments.

Safe CO2 threshold limits for indoor long-range airborne transmission control of COVID-19

CO2-based infection risk monitoring is highly recommended during the current COVID-19 pandemic. However, the CO2 monitoring thresholds proposed in the literature are mainly for spaces with fixed occupants. Determining CO2 threshold is challenging in spaces with changing occupancy due to the co-existence of quanta and CO2 remaining from previous occupants. Here, we propose a new calculation framework for deriving safe excess CO2 thresholds (above outdoor level), C t, for various spaces with fixed/changing occupancy and analyze the uncertainty involved. We categorized common indoor spaces into three scenarios based on their occupancy conditions, e.g., fixed or varying infection ratios (infectors/occupants). We proved that the rebreathed fraction-based model can be applied directly for deriving C t in the case of a fixed infection ratio (Scenario 1 and Scenario 2). In the case of varying infection ratios (Scenario 3), C t derivation must follow the general calculation framework due to the existence of initial quanta/excess CO2. Otherwise, C t can be significantly biased (e.g., 260 ppm) when the infection ratio varies greatly. C t can vary significantly based on specific space factors such as occupant number, physical activity, and community prevalence, e.g., 7 ppm for gym and 890 ppm for lecture hall, indicating C t must be determined on a case-by-case basis. An uncertainty of up to 6 orders of magnitude for C t was found for all cases due to uncertainty in emissions of quanta and CO2, thus emphasizing the role of accurate emissions data in determining C t.

Local travel behaviour under continuing COVID-19 waves- A proxy for pandemic fatigue?

COVID-19 continues to threaten the world. Relaxing local travel behaviours on preventing the spread of COVID-19, may increase the infection risk in subsequent waves of SARS-CoV-2 transmission. In this study, we analysed changes in the travel behaviour of different population groups (adult, child, student, elderly) during four pandemic waves in Hong Kong before January 2021, by 4-billion second-by-second smartcard records of subway. A significant continuous relaxation in human travel behaviour was observed during the four waves of SARS-CoV-2 transmission. Residents sharply reduced their local travel by 51.9%, 50.1%, 27.6%, and 20.5% from the first to fourth pandemic waves, respectively. The population flow in residential areas, workplaces, schools, shopping areas, amusement areas and border areas, decreased on average by 30.3%, 33.5%, 41.9%, 58.1%, 85.4% and 99.6%, respectively, during the pandemic weeks. We also found that many other cities around the world experienced a similar relaxation trend in local travel behaviour, by comparing traffic congestion data during the pandemic with data from the same period in 2019. The quantitative pandemic fatigue in local travel behaviour could help governments partially predicting personal protective behaviours, and thus to suggest more accurate interventions during subsequent waves, especially for highly infectious virus variants such as Omicron.

Addressing Complexity in the Pandemic Context: How Systems Thinking Can Facilitate Understanding of Design Aspects for Preventive Technologies

The COVID-19 pandemic constitutes a wicked problem that is defined by rapidly evolving and dynamic conditions, where the physical world changes (e.g., pathogens mutate) and, in parallel, our understanding and knowledge rapidly progress. Various preventive measures have been developed or proposed to manage the situation, including digital preventive technologies to support contact tracing or physical distancing. The complexity of the pandemic and the rapidly evolving nature of the situation pose challenges for the design of effective preventive technologies. The aim of this conceptual paper is to apply a systems thinking model, DSRP (distinctions, systems, relations, perspectives) to explain the underlying assumptions, patterns, and connections of the pandemic domain, as well as to identify potential leverage points for design of preventive technologies. Two different design approaches, contact tracing and nudging for distance, are compared, focusing on how their design and preventive logic are related to system complexity. The analysis explains why a contact tracing technology involves more complexity, which can challenge both implementation and user understanding. A system utilizing nudges can operate using a more distinct system boundary, which can benefit understanding and implementation. However, frequent nudges might pose challenges for user experience. This further implies that these technologies have different contextual requirements and are useful at different levels in society. The main contribution of this work is to show how systems thinking can organize our understanding and guide the design of preventive technologies in the context of epidemics and pandemics.

A Numerical Investigation into the Spread Characteristics of a Human Virus-Carrying Droplet in a Classroom Environment

In public health, the transmission characteristics and laws of highly infectious virus-carrying particles in the air environment have become a hot topic. The study on the spread characteristics of human virus-carrying droplets in a typical densely populated space is necessary. As such, a classroom space lattice Boltzmann method (LBM) model with a dense population is established to simulate and analyze the spreading and diffusing behavior of pathogenic droplets. The results show that the dispersion density is mainly affected by the mainstream wind direction in the area of concern, and particle aggregation is more likely to form in the area close to the wind disturbance. Due to the dense thermal plumes, the droplet movement is a clear convergence towards the upper space of the classroom. This could explain the fact that people living above confirmed cases are now more likely to be infected.

Predominance of inhalation route in short-range transmission of respiratory viruses: Investigation based on computational fluid dynamics

During the Coronavirus disease 2019 pandemic, short-range virus transmission has been observed to have a higher risk of causing infection than long-range virus transmission. However, the roles played by the inhalation and large droplet routes cannot be distinguished in practice. A recent analytical study revealed the predominance of short-range inhalation over the large droplet spray route as causes of respiratory infections. In the current study, short-range exposure was analyzed via computational fluid dynamics (CFD) simulations using a discrete phase model. Detailed facial membranes, including eyes, nostrils, and a mouth, were considered. In CFD simulations, there is no need for a spherical approximation of the human head for estimating deposition nor the "anisokinetic aerosol sampling" approximation for estimating inhalation in the analytical model. We considered two scenarios (with two spheres [Scenario 1] and two human manikins [Scenario 2]), source-target distances of 0.2 to 2 m, and droplet diameters of 3 to 1,500 µm. The overall CFD exposure results agree well with data previously obtained from a simple analytical model. The CFD results confirm the predominance of the short-range inhalation route beyond 0.2 m for expiratory droplets smaller than 50 µm during talking and coughing. A critical droplet size of 87.5 µm was found to differentiate droplet behaviors. The number of droplets deposited on the target head exceeded those exposed to facial membranes, which implies a risk of exposure through the immediate surface route over a short range.

Electronic Supplementary Material ESM

the Supplementary Materials are available in the online version of this article at 10.1007/s12273-022-0968-y.

Bioaerosol distribution characteristics and potential SARS-CoV-2 infection risk in a multi-compartment dental clinic

Dental clinics have a potential risk of infection, particularly during the COVID-19 pandemic. Multi-compartment dental clinics are widely used in general hospitals and independent clinics. This study utilised computational fluid dynamics to investigate the bioaerosol distribution characteristics in a multi-compartment dental clinic through spatiotemporal distribution, working area time-varying concentrations, and key surface deposition. The infection probability of SARS-CoV-2 for the dental staff and patients was calculated using the Wells-Riley model. In addition, the accuracy of the numerical model was verified by field measurements of aerosol concentrations performed during a clinical ultrasonic scaling procedure. The results showed that bioaerosols were mainly distributed in the compartments where the patients were treated. The average infection probability was 3.8% for dental staff. The average deposition number per unit area of the treatment chair and table are 28729 pcs/m² and 7945 pcs/m², respectively, which creates a possible contact transmission risk. Moreover, there was a certain cross-infection risk in adjacent compartments, and the average infection probability for patients was 0.84%. The bioaerosol concentrations of the working area in each compartment 30 min post-treatment were reduced to 0.07% of those during treatment, and the infection probability was <0.05%. The results will contribute to an in-depth understanding of the infection risk in multi-compartment dental clinics, forming feasible suggestions for management to efficiently support epidemic prevention and control in dental clinics.

Close contact behavior-based COVID-19 transmission and interventions in a subway system

During COVID-19 pandemic, analysis on virus exposure and intervention efficiency in public transports based on real passenger's close contact behaviors is critical to curb infectious disease transmission. A monitoring device was developed to gather a total of 145,821 close contact data in subways based on semi-supervision learning. A virus transmission model considering both short- and long-range inhalation and deposition was established to calculate the virus exposure. During rush-hour, short-range inhalation exposure is 3.2 times higher than deposition exposure and 7.5 times higher than long-range inhalation exposure of all passengers in the subway. The close contact rate was 56.1 % and the average interpersonal distance was 0.8 m. Face-to-back was the main pattern during close contact. Comparing with random distribution, if all passengers stand facing in the same direction, personal virus exposure through inhalation (deposition) can be reduced by 74.1 % (98.5 %). If the talk rate was decreased from 20 % to 5 %, the inhalation (deposition) exposure can be reduced by 69.3 % (73.8 %). In addition, we found that virus exposure could be reduced by 82.0 % if all passengers wear surgical masks. This study provides scientific support for COVID-19 prevention and control in subways based on real human close contact behaviors.

Role of pathogen-laden expiratory droplet dispersion and natural ventilation explaining a COVID-19 outbreak in a coach bus

The influencing mechanism of droplet transmissions inside crowded and poorly ventilated buses on infection risks of respiratory diseases is still unclear. Based on experiments of one-infecting-seven COVID-19 outbreak with an index patient at bus rear, we conducted CFD simulations to investigate integrated effects of initial droplet diameters(tracer gas, 5 μm, 50 μm and 100 μm), natural air change rates per hour(ACH = 0.62, 2.27 and 5.66 h-1 related to bus speeds) and relative humidity(RH = 35% and 95%) on pathogen-laden droplet dispersion and infection risks. Outdoor pressure difference around bus surfaces introduces natural ventilation airflow entering from bus-rear skylight and leaving from the front one. When ACH = 0.62 h-1(idling state), the 30-min-exposure infection risk(TIR) of tracer gas is 15.3%(bus rear) - 11.1%(bus front), and decreases to 3.1%(bus rear)-1.3%(bus front) under ACH = 5.66 h-1(high bus speed).The TIR of large droplets(i.e., 100 μm/50 μm) is almost independent of ACH, with a peak value(∼3.1%) near the index patient, because over 99.5%/97.0% of droplets deposit locally due to gravity. Moreover, 5 μm droplets can disperse further with the increasing ventilation. However, TIR for 5 μm droplets at ACH = 5.66 h-1 stays relatively small for rear passengers(maximum 0.4%), and is even smaller in the bus middle and front(<0.1%). This study verifies that differing from general rooms, most 5 μm droplets deposit on the route through the long-and-narrow bus space with large-area surfaces(L∼11.4 m). Therefore, tracer gas can only simulate fine droplet with little deposition but cannot replace 5-100 μm droplet dispersion in coach buses.

Uncertainty analysis of facemasks in mitigating SARS-CoV-2 transmission

In the context of global spread of coronavirus disease 2019 (COVID-19) caused by a novel coronavirus (SARS-CoV-2), there is a controversial issue on whether the use of facemasks is promising to control or mitigate the COVID-19 transmission. This study modeled the SARS-CoV-2 transmission process and analyzed the ability of surgical mask and N95 in reducing the infection risk with Sobol's analysis. Two documented outbreaks of COVID-19 with no involvers wearing face masks were reviewed in a restaurant in Guangzhou (China) and a choir rehearsal in Mount Vernon (USA), suggesting that the proposed model can be well validated when airborne transmission is assumed to dominate the virus transmission indoors. Subsequently, the uncertainty analysis of the protection efficiency of N95 and surgical mask were conducted with Monte Carlo simulations, with three main findings: (1) the uncertainty in infection risk is primarily apportioned by respiratory activities, virus dynamics, environment factors and individual exposures; (2) wearing masks can effectively reduce the SARS-CoV-2 infection risk to an acceptable level (< 10^-3) by at least two orders of magnitude; (3) faceseal leakage can reduce protection efficiency by approximately 4% when the infector is speaking or coughing, and by approximately 28% when the infector is sneezing. This work indicates the effectiveness of non-pharmaceutical interventions during the pandemic, and implies the importance of the synergistic studies of medicine, environment, social policies and strategies, etc., on reducing hazards and risks of the pandemic.

Evidence of the Relationship between Social Vulnerability and the Spread of COVID-19 in Urban Spaces

Modeling the social-spatial structure of urban spaces can facilitate the development of guidelines aimed at curbing the spread of the COVID-19 pandemic while also acting as an instrument that helps decision-making concerning mitigation policies. The modeling process starts with categorization of urban spaces based on the concept of social vulnerability. A model is created based on this concept and the theory of analysis of social areas. Statistical techniques of factor analysis and geostatistics are applied. This generates a map of social differentiation that, when related to data on the evolution of the contagion, generates a multidimensional model of social vulnerability. The application of this model towards people (social structure) and the environment where they live (spatial structure) is specified. Our model assumes the uniqueness of cities, and it is intended to be a broadly applicable model that can be extrapolated to other urban areas if pertinent revisions are made. Our work demonstrates that aspects of the social and urban structures may be validly used to analyze and explain the spatial spread of COVID-19.

Aerosol Transmission of SARS-CoV-2 in Two Dormitories - Hubei and Shandong Provinces, China, 2020

What is already known about this topic?

Aerosol transmission is one route for the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, uncertainty remains on the threshold of ventilation rate in its occurrence.

What is added by this report?

Based on two cases in Shandong Province and Hubei Province, the effect of wearing masks and the minimum ventilation required to reduce coronavirus disease 2019 (COVID-19) aerosol transmission was determined.

What are the implications for public health practice?

No masking and low ventilation rates lead to a relatively high contribution of aerosols to COVID-19 transmission. Thus, public awareness of wearing masks should increase and the ventilation rate should be sufficiently higher than the minimum required ventilation.

Prediction and control of aerosol transmission of SARS-CoV-2 in ventilated context: from source to receptor

Global spread of COVID-19 has seriously threatened human life and health. The aerosol transmission route of SARS-CoV-2 is observed often associated with infection clusters under poorly ventilated environment. In the context of COVID-19 pandemic, significant transformation and optimization of traditional ventilation systems are needed. This paper is aimed to offer better understanding and insights into effective ventilation design to maximize its ability in airborne risk control, for particularly the COVID-19. Comprehensive reviews of each phase of aerosol transmission of SARS-CoV-2 from source to receptor are conducted, so as to provide a theoretical basis for risk prediction and control. Infection risk models and their key parameters for risk assessment of SARS-CoV-2 are analyzed. Special focus is given on the efficacy of different ventilation strategies in mitigating airborne transmission. Ventilation interventions are found mainly impacting on the dispersion and inhalation phases of aerosol transmission. The airflow patterns become a key factor in controlling the aerosol diffusion and distribution. Novel and personalized ventilation design, effective integration with other environmental control techniques and resilient HVAC system design to adapt both common and epidemic conditions are still remaining challenging, which need to be solved with the aid of multidisciplinary research and intelligent technologies.