A Computational Approach for the Characterization of Airborne Pathogen Transmission in Turbulent Molecular Communication Channels

Airborne pathogen transmission mechanisms play a key role in the spread of infectious diseases such as COVID-19. In this work, we propose a computational fluid dynamics (CFD) approach to model and statistically characterize airborne pathogen transmission via pathogen-laden particles in turbulent channels from a molecular communication viewpoint. To this end, turbulent flows induced by coughing and the turbulent dispersion of droplets and aerosols are modeled by using the Reynolds-averaged Navier-Stokes equations coupled with the realizable k-model and the discrete random walk model, respectively. Via simulations realized by a CFD simulator, statistical data for the number of received particles are obtained. These data are post-processed to obtain the statistical characterization of the turbulent effect in the reception and to derive the probability of infection. Our results reveal that the turbulence has an irregular effect on the probability of infection, which shows itself by the multi-modal distribution as a weighted sum of normal and Weibull distributions. Furthermore, it is shown that the turbulent MC channel is characterized via multi-modal, i.e., sum of weighted normal distributions, or stable distributions, depending on the air velocity. Crown

The effectiveness of disinfection protocols in medical school osteopathic manipulative medicine labs.

CONTEXT: In light of the COVID-19 pandemic, healthcare-associated infections have taken center stage. Healthcare has adjusted workflows to accommodate for more robust disinfecting regiments to help protect the community. This has resulted in the need for medical institutions to reevaluate the current disinfection protocols down to the student level. The osteopathic manipulative medicine (OMM) laboratory provides an optimal avenue for assessing the effectiveness of medical students' ability to clean examination tables. With OMM laboratories having a high level of interaction, adequate disinfection is important for the health and safety of students and teaching faculties. OBJECTIVES: This study will evaluate the effectiveness of the current disinfection protocols in the medical school OMM labs. METHODS: A cross-sectional, nonrandomized study was performed on 20 OMM examination tables utilized for osteopathic training. Tables were chosen based on their close proximity to the podium. Close proximity was utilized as a criteria to increase the probability of utilization by students. The sampled tables were observed to ensure their use by students during class. Initial samples were collected in the morning after disinfection by Environmental Services. Terminal samples were collected after Osteopathic medical students utilized and disinfected the OMM examination tables. Samples were collected from the face-cradle and midtorso regions and analyzed utilizing adenosine triphosphate (ATP) bioluminescence assays with an AccuPoint Advanced HC Reader. This reader provides a digital readout of the quantity of light measured in relative light units (RLUs), which is directly correlated to the amount of ATP present in the sample, providing an estimated pathogen count. For statistical analysis, a Wilcoxon signed-rank test was utilized to find statistical differences in RLUs in samples after initial and terminal disinfection. RESULTS: The face cradle showed a 40 % increase in failure rate in samples after terminal disinfection when samples were compared after initial disinfection. A Wilcoxon signed-rank test revealed an estimated pathogen level for face cradle that was significantly higher after terminal disinfection (median, 4,295 RLUs; range, 2,269-12919 RLUs; n=20) compared to initial disinfection (median, 769 RLUs; range, 29-2,422 RLUs; n=20), z=-3.8, p=0.00008, with a large effect size, d=2.2. The midtorso region showed a 75 % increase in samples after terminal disinfection when samples were compared after initial disinfection. A Wilcoxon signed-rank test revealed that the estimated pathogen levels for midtorso were significantly higher after terminal disinfecting (median, 656 RLUs; range, 112-1,922 RLUs; n=20) compared to initial disinfecting (median, 128 RLUs; range, 1-335 RLUs; n=20), z=-3.9, p=0.00012, with a large effect size, d=1.8. CONCLUSIONS: This study suggests that medical students frequently failed to disinfect high-touch regions on examination tables, such as the midtorso and the face cradle. It is recommended that the current OMM lab disinfection protocol be modified to include the disinfection of high-touch regions in order to reduce the possibility of pathogen transmission. Further research should explore the effectiveness of disinfection protocols in clinical settings such as outpatient offices.

Lung aerosol particle emission increases with age at rest and during exercise.

Airborne respiratory aerosol particle transmission of pathogens such as severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2), influenza, or rhinoviruses plays a major role in the spread of infectious diseases. The infection risk is increased during indoor exercise, as aerosol particle emission can increase by more than 100-fold from rest to maximal exercise. Earlier studies have investigated the effect of factors such as age, sex, and body mass index (BMI), but only at rest and without taking ventilation into account. Here, we report that during both rest and exercise, subjects aged 60 to 76 y emit on average more than twice as many aerosol particles per minute than subjects aged 20 to 39 y. In terms of volume, older subjects emit on average five times as much dry volume (i.e., the residue of dried aerosol particles) than younger subjects. There was no statistically significant effect of sex or BMI within the test group. Together, this suggests that aging of the lung and respiratory tract is associated with an increased generation of aerosol particles irrespective of ventilation. Our findings demonstrate that age and exercise increase aerosol particle emission. In contrast, sex or BMI only have minor effects.

Gut microbiome and COVID-19

Coronavirus disease 2019 (COVID-19) caused by the enveloped double-stranded positive sense RNA virus, SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is responsible for one of the most significant and widespread global pandemic in recent times. It started in China in December 2019 and rapidly spread to each and every country of the world and caused more 521 million infections and more than 6.28 million deaths (as of May 17, 2022) and counting. It primarily infects the respiratory tract, but direct infection thorough other routes (ocular and gastrointestinal) is also reported. The virus can spread easily to different body systems causing multisystemic diseases leading to significant morbidity and mortality. Human gut microbiome is the most complex ecological niche in nature and harbors trillions of microorganisms, predominantly bacteria and viruses. Gut microbiome exists in homeostatic, mutually beneficial, equilibrium with the host in healthy humans. However, any shift in balance towards dysbiosis (unhealthy gut microbiome) due to different factors (such as unhealthy diet, antibiotic use, disease) that modulate microbiome may lead to a variety of diseases and health conditions. Recent studies are demonstrating that SARS-CoV-2 infection modulate gut microbiome and gut microbiome can also influence severity of COVID-19. In this review, we summarize our knowledge with focus on the emerging theme of bidirectional cross-talk between gut microbiome and SARS-CoV-2, an important component in formulating strategies to control this formidable virus. © 2023 Elsevier Inc. All rights reserved.

Respiratory aerosol particle emission and simulated infection risk is greater during indoor endurance than resistance exercise.

Pathogens such as severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), influenza, and rhinoviruses are transmitted by airborne aerosol respiratory particles that are exhaled by infectious subjects. We have previously reported that the emission of aerosol particles increases on average 132-fold from rest to maximal endurance exercise. The aims of this study are to first measure aerosol particle emission during an isokinetic resistance exercise at 80% of the maximal voluntary contraction until exhaustion, second to compare aerosol particle emission during a typical spinning class session versus a three-set resistance training session. Finally, we then used this data to calculate the risk of infection during endurance and resistance exercise sessions with different mitigation strategies. During a set of isokinetic resistance exercise, aerosol particle emission increased 10-fold from 5,400 ± 1,200 particles/min at rest to 59,000 ± 69,900 particles/min during a set of resistance exercise. We found that aerosol particle emission per minute is on average 4.9-times lower during a resistance training session than during a spinning class. Using this data, we determined that the simulated infection risk increase during an endurance exercise session was sixfold higher than during a resistance exercise session when assuming one infected participant in the class. Collectively, this data helps to select mitigation measures for indoor resistance and endurance exercise classes at times where the risk of aerosol-transmitted infectious disease with severe outcomes is high.

Effect of ceiling fan in mitigating exposure to airborne pathogens and COVID-19

Ceiling fans are the ubiquitously used electrical appliance in indoor spaces that affect the local airflow pattern and, consequently, transmission of airborne pathogens and respiratory droplets. This study numerically investigated the effect of airflow induced by the ceiling fan and ventilation rate on aerosol distribution to mitigate exposure to airborne pathogens and COVID-19. A full-scale room with a ceiling fan, natural ventilation and an occupant was modelled through transient computational fluid-particle dynamics (CFPD). To analyze the relationship between the ceiling fan rotation speed and the aerosol distribution, a ceiling fan was operated with 160, 265 and 365 revolutions per minute (RPM). The effect of the ceiling fan on particles was analyzed for particles of different sizes. The increasing ceiling fan rotation speed, the percentage deposition of the aerosol particles with diameters >40 μm was increased. The effect of different ventilation rates on aerosol distribution was evaluated. The increased ventilation rate, the percentage of the total aerosol particles flushed out was increased. The effectiveness of the mask in mitigating the exposure risk of airborne pathogens was also investigated. In combination with the natural ventilation and mask, the ceiling fan was demonstrated to have the potential to reduce airborne pathogen transmission in indoor spaces.

Safety and immunogenicity of the Nipah virus vaccine.

In 1999, a new RNA virus was identified in Malaysia, later named Nipah. Although the global pandemic of the SARS--CoV-2 virus has not yet ended, it is the Nipah virus that is often referred to as another potentially highly dangerous viral infection for humankind. It is again a zoonosis. The virus is transmitted mainly by water lilies. These flying mammals are closely related to bats. In 2001, the virus spread to Bangladesh, causing several rapidly spreading epidemics. In 2020, Nipah appeared in India and killed 17 people in the Kerala region where more than two billion people live. In October 2021, the Phase 1 study of the Nipah virus vaccine HeV-sG-V developed by Auro Vaccines LLC should be completed and evaluated. Copyright © 2021, Medakta s.r.o.. All rights reserved.

Application of an Ultrasonic Nebulizer Closet in the Disinfection of Textiles and Footwear.

The emergence of the coronavirus disease 2019 (COVID-19) pandemic highlighted the importance of disinfection processes in health safety. Textiles and footwear have been identified as vectors for spreading infections. Therefore, their disinfection can be crucial to controlling pathogens' dissemination. The present work aimed to evaluate the effectiveness of a commercial disinfectant aerosolized by an ultrasonic nebulizer closet as an effective method for disinfecting textiles and footwear. The disinfection was evaluated in three steps: suspension tests; nebulization in a 0.08 m3 closet; nebulization in the upscaled 0.58 m3 closet. The disinfection process of textiles and footwear was followed by the use of bacteriophages, bacterial spores, and bacterial cells. The disinfection in the 0.58 m3 closet was efficient for textiles (4 log reduction) when bacteriophage Lambda, Pseudomonas aeruginosa, and Bacillus subtilis were used. The footwear disinfection was achieved (4 log reduction) in the 0.08 m3 closet for Escherichia coli and Staphylococcus aureus. Disinfection in an ultrasonic nebulization closet has advantages such as being quick, not wetting, being efficient on porous surfaces, and is performed at room temperature. Ultrasonic nebulization disinfection in a closet proves to be useful in clothing and footwear stores to prevent pathogen transmission by the items' widespread handling.

Mobile human ad hoc networks: A communication engineering viewpoint on interhuman airborne pathogen transmission.

A number of transmission models for airborne pathogens transmission, as required to understand airborne infectious diseases such as COVID-19, have been proposed independently from each other, at different scales, and by researchers from various disciplines. We propose a communication engineering approach that blends different disciplines such as epidemiology, biology, medicine, and fluid dynamics. The aim is to present a unified framework using communication engineering, and to highlight future research directions for modeling the spread of infectious diseases through airborne transmission. We introduce the concept of mobile human ad hoc networks (MoHANETs), which exploits the similarity of airborne transmission-driven human groups with mobile ad hoc networks and uses molecular communication as the enabling paradigm. In the MoHANET architecture, a layered structure is employed where the infectious human emitting pathogen-laden droplets and the exposed human to these droplets are considered as the transmitter and receiver, respectively. Our proof-of-concept results, which we validated using empirical COVID-19 data, clearly demonstrate the ability of our MoHANET architecture to predict the dynamics of infectious diseases by considering the propagation of pathogen-laden droplets, their reception and mobility of humans.

Ultraviolet-C Light-emitting Device Against Microorganisms in Beauty Salons.

Background: Ultraviolet light in the UV-C band is also known as germicidal radiation, and it is widely used for decontamination and disinfection of environments, water, and food. The ultraviolet source transfers electromagnetic energy from a mercury arc lamp to an organism's genetic material. When UV radiation penetrates the cell wall of an organism, it destroys the cell's ability to reproduce, through a physical and not chemical process. Thus, the objective of this study was to evaluate the antimicrobial potential of a new UV-C generating device (Asepsis) against clinically important microorganisms that may be present in beauty centers. Methods: We present here a set of tests performed on tools easy to find in beauty salons (hair-brushes, nail pliers, makeup brushes, and, due to the recent COVID-19 pandemic, face mask samples). They were individually contaminated with bacteria (Pseudomonas aeruginosa, Staphylococcus aureus), fungi (Microsporum canis, Trichophyton rubrum, Candida albicans, Malassezia furfur), and the Chikungunya virus. Different times of exposure were evaluated (1, 3, and 5 minutes). Results: There was notable reduction in the microbial load in every test, in comparison with control groups. Best results were observed on face mask samples, while the makeup brush showed less reduction, even with longer periods of exposure. Conclusions: Beauty salons present a risk of infections due to microbial exposure. The device tested can efficiently inactivate, in a short time, microorganisms contaminating most tools found in this setting. The device also showed promising results against enveloped virus.

Impact of COVID-19 Social Distancing Mandates on Gastrointestinal Pathogen Positivity: Secondary Data Analysis.

BACKGROUND: Acute gastrointestinal (GI) illnesses are of the most common problems evaluated by physicians and some of the most preventable. There is evidence of GI pathogen transmission when people are in close contact. The COVID-19 pandemic led to the sudden implementation of widespread social distancing measures in the United States. There is strong evidence that social distancing measures impact the spread of SARS-CoV-2, and a growing body of research indicates that these measures also decrease the transmission of other respiratory pathogens. OBJECTIVE: This study aims to investigate the impact of COVID-19 social distancing mandates on the GI pathogen positivity rates. METHODS: Deidentified GI Panel polymerase chain reaction test results from a routinely collected diagnostic database from January 1, 2019, through August 31, 2020, were analyzed for the GI pathogen positivity percentage. An interrupted time series analysis was performed, using social distancing mandate issue dates as the intervention date. The following 3 target organisms were chosen for the final analysis to represent different primary transmission routes: adenovirus F40 and 41, norovirus GI and GII, and Escherichia coli O157. RESULTS: In total, 84,223 test results from 9 states were included in the final data set. With the exception of E coli O157 in Kansas, Michigan, and Nebraska, we observed an immediate decrease in positivity percentage during the week of social distancing mandates for all other targets and states. Norovirus GI and GII showed the most notable drop in positivity, whereas E coli O157 appeared to be least impacted by social distancing mandates. Although we acknowledge the analysis has a multiple testing problem, the majority of our significant results showed significance even below the .01 level. CONCLUSIONS: This study aimed to investigate the impact of social distancing mandates for COVID-19 on GI pathogen positivity, and we discovered that social distancing measures in fact decreased GI pathogen positivity initially. The use of similar measures may prove useful in GI pathogen outbreaks. The use of a unique diagnostic database in this study exhibits the potential for its use as a public health surveillance tool.

Direct Numerical Simulation of a Moist Cough Flow using Eulerian Approximation for Liquid Droplets

The COVID-19 pandemic has inspired several studies on the fluid dynamics of respiratory events. Here, we propose a computational approach in which respiratory droplets are coarse-grained into an Eulerian liquid field advected by the fluid streamlines. A direct numerical simulation is carried out for a moist cough using a closure model for space-time dependence of the evaporation time scale. Stokes-number estimates are provided, for the initial droplet size of 10 mu m, which are found to be MUCH LESS-THAN1, thereby justifying the neglect of droplet inertia, over the duration of the simulation. Several important features of the moist-cough flow reported in the literature using Lagrangian tracking methods have been accurately captured using our scheme. Some new results are presented, including the evaporation time for a 'mild' cough, a saturation-temperature diagram and a favourable correlation between the vorticity and liquid fields. The present approach can be extended for studying the long-range transmission of virus-laden droplets.

Live animal markets: Identifying the origins of emerging infectious diseases.

Emerging infectious diseases (EIDs) of zoonotic origin appear, affect a population and can spread rapidly. At the beginning of 2020, the World Health Organization pronounced an emergency public health advisory because of the SARS-CoV-2 coronavirus outbreak, and declared that COVID-19 had reached the level of a pandemic, rapidly spreading around the world. In order to identify one of the origins of EIDs, and propose some control alternatives, an extensive review was conducted of the available literature. The problem can originate in live animal markets, where animal species of all kinds, from different origins, ecosystems, and taxonomic groups are caged and crowded together, sharing the same unsanitary and unnatural space, food, water, and also the ecto- and endoparasitic vectors of disease. They defecate on each other, leading to the exchange of pathogenic and parasitic microorganisms, forcing interactions among species that should never happen. This is the ideal scenario for causing zoonoses and outbreaks of EIDs. We must start by stopping the illegal collection and sale of wild animals in markets. The destruction of ecosystems and forests also promote zoonoses and outbreaks of EIDs. Science and knowledge should be the basis of the decisions and policies for the development of management strategies. Wildlife belongs in its natural habitat, which must be defended, conserved, and restored at all costs.

CFD modeling of airborne pathogen transmission of COVID-19 in confined spaces under different ventilation strategies.

Airborne transmission is an important route of spread of viral diseases (e.g., COVID-19) inside the confined spaces. In this respect, computational fluid dynamics (CFD) emerged as a reliable and fast tool to understand the complex flow patterns in such spaces. Most of the recent studies, nonetheless, focused on the spatial distribution of airborne pathogens to identify the infection probability without considering the exposure time. This research proposes a framework to evaluate the infection probability related to both spatial and temporal parameters. A validated Eulerian-Lagrangian CFD model of exhaled droplets is first developed and then evaluated with an office case study impacted by different ventilation strategies (i.e., cross- (CV), single- (SV), mechanical- (MV) and no-ventilation (NV)). CFD results were analyzed in a bespoke code to calculate the tempo-spatial distribution of accumulated airborne pathogens. Furthermore, two indices of local and general infection risks were used to evaluate the infection probability of the ventilation scenarios. The results suggest that SV has the highest infection probability while SV and NO result in higher dispersions of airborne pathogens inside the room. Eventually, the time history of indices reveals that the efficiency of CV and MV can be poor in certain regions of the room.

Social contact patterns and implications for infectious disease transmission - a systematic review and meta-analysis of contact surveys.

Background: Transmission of respiratory pathogens such as SARS-CoV-2 depends on patterns of contact and mixing across populations. Understanding this is crucial to predict pathogen spread and the effectiveness of control efforts. Most analyses of contact patterns to date have focused on high-income settings. Methods: Here, we conduct a systematic review and individual-participant meta-analysis of surveys carried out in low- and middle-income countries and compare patterns of contact in these settings to surveys previously carried out in high-income countries. Using individual-level data from 28,503 participants and 413,069 contacts across 27 surveys, we explored how contact characteristics (number, location, duration, and whether physical) vary across income settings. Results: Contact rates declined with age in high- and upper-middle-income settings, but not in low-income settings, where adults aged 65+ made similar numbers of contacts as younger individuals and mixed with all age groups. Across all settings, increasing household size was a key determinant of contact frequency and characteristics, with low-income settings characterised by the largest, most intergenerational households. A higher proportion of contacts were made at home in low-income settings, and work/school contacts were more frequent in high-income strata. We also observed contrasting effects of gender across income strata on the frequency, duration, and type of contacts individuals made. Conclusions: These differences in contact patterns between settings have material consequences for both spread of respiratory pathogens and the effectiveness of different non-pharmaceutical interventions. Funding: This work is primarily being funded by joint Centre funding from the UK Medical Research Council and DFID (MR/R015600/1).

Infectious diseases, particularly those caused by airborne pathogens like SARS-CoV-2, spread by social contact, and understanding how people mix is critical in controlling outbreaks. To explore these patterns, researchers typically carry out large contact surveys. Participants are asked for personal information (such as gender, age and occupation), as well as details of recent social contacts, usually those that happened in the last 24 hours. This information includes, the age and gender of the contact, where the interaction happened, how long it lasted, and whether it involved physical touch. These kinds of surveys help scientists to predict how infectious diseases might spread. But there is a problem: most of the data come from high-income countries, and there is evidence to suggest that social contact patterns differ between places. Therefore, data from these countries might not be useful for predicting how infections spread in lower-income regions. Here, Mousa et al. have collected and combined data from 27 contact surveys carried out before the COVID-19 pandemic to see how baseline social interactions vary between high- and lower-income settings. The comparison revealed that, in higher-income countries, the number of daily contacts people made decreased with age. But, in lower-income countries, younger and older individuals made similar numbers of contacts and mixed with all age groups. In higher-income countries, more contacts happened at work or school, while in low-income settings, more interactions happened at home and people were also more likely to live in larger, intergenerational households. Mousa et al. also found that gender affected how long contacts lasted and whether they involved physical contact, both of which are key risk factors for transmitting airborne pathogens. These findings can help researchers to predict how infectious diseases might spread in different settings. They can also be used to assess how effective non-medical restrictions, like shielding of the elderly and workplace closures, will be at reducing transmissions in different parts of the world.

A simplified tempo-spatial model to predict airborne pathogen release risk in enclosed spaces: An Eulerian-Lagrangian CFD approach.

COVID19 pathogens are primarily transmitted via airborne respiratory droplets expelled from infected bio-sources. However, there is a lack of simplified accurate source models that can represent the airborne release to be utilized in the safe-social distancing measures and ventilation design of buildings. Although computational fluid dynamics (CFD) can provide accurate models of airborne disease transmissions, they are computationally expensive. Thus, this study proposes an innovative framework that benefits from a series of relatively accurate CFD simulations to first generate a dataset of respiratory events and then to develop a simplified source model. The dataset has been generated based on key clinical parameters (i.e., the velocity of droplet release) and environmental factors (i.e., room temperature and relative humidity) in the droplet release modes. An Eulerian CFD model is first validated against experimental data and then interlinked with a Lagrangian CFD model to simulate trajectory and evaporation of numerous droplets in various sizes (0.1 µm-700 µm). A risk assessment model previously developed by the authors is then applied to the simulation cases to identify the horizontal and vertical spread lengths (risk cloud) of viruses in each case within an exposure time. Eventually, an artificial neural network-based model is fitted to the spread lengths to develop the simplified predictive source model. The results identify three main regimes of risk clouds, which can be fairly predicted by the ANN model.

Unveiling social distancing mechanisms via a fish-robot hybrid interaction.

Pathogen transmission is a major limit of social species. Social distancing, a behavioural-based response to diseases, has been regularly reported in nature. However, the identification of distinctive stimuli associated with an infectious disease represents a challenging task for host species, whose cognitive mechanisms are still poorly understood. Herein, the social fish Paracheirodon innesi, was selected as model organism to investigate animal abilities in exploiting visual information to identify and promote social distancing towards potentially infected conspecifics. To address this, a robotic fish replica mimicking a healthy P. innesi subject, and another mimicking P. innesi with morphological and/or locomotion anomalies were developed. P. innesi individuals were attracted by the healthy fish replica, while they avoided the fish replica with morphological abnormalities, as well as the fish replica with an intact appearance, but performing locomotion anomalies (both symptoms associated with a microsporidian parasite infesting P. innesi and other fish). Furthermore, the fish replica presenting both morphology and locomotion anomalies in conjunction, triggered a significantly stronger social distancing response. This confirms the hypothesis that group living animals overgeneralize cues that can be related with a disease to minimize transmission, and highlights the important role of visual cues in infection risk contexts. This study prompts more attention on the role of behavioural-based strategies to avoid pathogen/parasite diffusion, and can be used to optimize computational approaches to model disease dynamics.

Spatial dynamics of pathogen transmission in communally roosting species: Impacts of changing habitats on bat-virus dynamics.

The spatial organization of populations determines their pathogen dynamics. This is particularly important for communally roosting species, whose aggregations are often driven by the spatial structure of their environment. We develop a spatially explicit model for virus transmission within roosts of Australian tree-dwelling bats (Pteropus spp.), parameterized to reflect Hendra virus. The spatial structure of roosts mirrors three study sites, and viral transmission between groups of bats in trees was modelled as a function of distance between roost trees. Using three levels of tree density to reflect anthropogenic changes in bat habitats, we investigate the potential effects of recent ecological shifts in Australia on the dynamics of zoonotic viruses in reservoir hosts. We show that simulated infection dynamics in spatially structured roosts differ from that of mean-field models for equivalently sized populations, highlighting the importance of spatial structure in disease models of gregarious taxa. Under contrasting scenarios of flying-fox roosting structures, sparse stand structures (with fewer trees but more bats per tree) generate higher probabilities of successful outbreaks, larger and faster epidemics, and shorter virus extinction times, compared to intermediate and dense stand structures with more trees but fewer bats per tree. These observations are consistent with the greater force of infection generated by structured populations with less numerous but larger infected groups, and may flag an increased risk of pathogen spillover from these increasingly abundant roost types. Outputs from our models contribute insights into the spread of viruses in structured animal populations, like communally roosting species, as well as specific insights into Hendra virus infection dynamics and spillover risk in a situation of changing host ecology. These insights will be relevant for modelling other zoonotic viruses in wildlife reservoir hosts in response to habitat modification and changing populations, including coronaviruses like SARS-CoV-2.

Time-Variant Positive Air Pressure in Drainage Stacks as a Pathogen Transmission Pathway of COVID-19.

Time-variant positive air pressure in a drainage stack poses a risk of pathogenic virus transmission into a habitable space, however, the excessive risk and its significance have not yet been sufficiently addressed for drainage system designs. This study proposes a novel measure for the probable pathogenic virus transmission risk of a high-rise drainage stack with the occurrence of positive air pressure. The proposed approach is based on time-variant positive air pressures measured in a 38 m high drainage stack of a full-scale experimental tower under steady flow conditions of flow rate 1-4 Ls-1 discharging at a height between 15 m to 33 m above the stack base. The maximum pressure and probabilistic positive air pressures in the discharging stack ventilation section with no water (Zone A of the discharging drainage stack) were determined. It was demonstrated that the positive air pressures were lower in frequency as compared with those in other stack zones and could propagate along the upper 1/3 portion of the ventilation pipe (H' ≥ 0.63) towards the ventilation opening at the rooftop. As the probabilistic positive pressures at a stack height were found to be related to the water discharging height and flow rate, a risk model of positive air pressure is proposed. Taking the 119th, 124th, 140th and 11,547th COVID-19 cases of an epidemiological investigation in Hong Kong as a baseline of concern, excessive risk of system overuse was evaluated. The results showed that for a 20-80% increase in the frequency of discharge flow rate, the number of floors identified at risk increased from 1 to 9 and 1 to 6 in the 34- and 25-storey residential buildings, respectively. The outcome can apply to facilities planning for self-quarantine arrangements in high-rise buildings where pathogenic virus transmission associated with drainage system overuse is a concern.

COVID-19 transmission: a rapid systematic review of current knowledge.

OBJECTIVE: The objective of this study was to identify the potential and definite sources of transmission of coronavirus disease 2019 (COVID-19). METHODS: Due to time constraints and the acute nature of the pandemic, we searched only PubMed/Medline from inception until January 28, 2021. We analyzed the level of evidence and risk of bias in each category and made suggestions accordingly. RESULTS: The virus was traced from its potential origin via possible ways of transmission to the last host. Symptomatic human-to-human transmission remains the driver of the epidemic, but asymptomatic transmission can potentially contribute in a substantial manner. Feces and fomites have both been found to contain viable virus; even though transmission through these routes has not been documented, their contribution cannot be ruled out. Finally, transmission from pregnant women to their children has been found to be low (up to 3%). CONCLUSION: Even though robust outcomes cannot be easily assessed, medical personnel must maintain awareness of the main routes of transmission (via droplets and aerosols from even asymptomatic patients). This is the first attempt to systematically review the existing knowledge to produce a paper with a potentially significant clinical impact.