Spread Of Respiratory Diseases Research Articles

Effect of personalized air curtain combined with mixing ventilation on dispersion of aerosols released at different velocities from respiratory activities during close contact

Release velocities of aerosols vary among people and respiratory activities. To better promote the application of personalized air curtain (PAC) in practice, this work investigated the performance of PAC combined with mixing ventilation in terms of dispersion of aerosols released at different velocities using a simulation approach of computational fluid dynamics (CFD). The healthy person (HP) and infected person (IP) were in face-to-face and face-to-back scenarios during close contact. Results showed that the aerosol dispersion was highly affected by aerosol release velocities. When aerosols were released from 2.0 m/s to 8.0 m/s, the deposition rate was increased by more than 3 times and 10 times in the face-to-face and face-to-back scenarios, respectively. The intake fraction was increased by over 3 times in the face-to-face scenario. PAC could significantly reduce the intake fraction and deposition rate. When aerosols were released at 8.0 m/s, PAC could reduce the intake fraction and deposition rate by 76% and 66% in the face-to-face scenario, respectively. A higher PAC velocity did not necessarily lead to a better performance. The appropriate PAC velocity of 3.0–5.0 m/s was suggested in this work. The significantly reduced intake fraction and deposition rate suggest that PAC as an advanced ventilation system can be a promising control measure to prevent the spread of respiratory diseases in indoor environments. Additionally, different performances of PAC indicate the importance of investigating the appropriate PAC velocities in relation to aerosol release velocities. Otherwise, more energy is consumed by PAC, but the best performance is not achieved.

The impacts of earthquakes on air pollution and strategies for mitigation: a case study of Turkey

This study delves into the repercussions of the 2023 earthquake in Turkey, particularity its impact on air pollution. A year post-event, it is evident that scientific literature has paid limited attention to monitoring the situation. However, the release of hazardous substances, such as asbestos, lead, and other toxins, from damaged structures poses a significant threat by contaminating nearby air, soil, and water sources, thereby jeopardizing ecosystems and public well-being. The improper disposal of waste post-earthquake and the presence of mining and oil refinery sites in the region contribute to potential air pollutants. These circumstances create challenging environments conducive to the spread of respiratory diseases, with potential long-term health and social consequences. Unfortunately, existing data gaps hinder a comprehensive understanding of the situation. This paper pioneers the reporting and analysis of data regarding potential sources of air pollution resulting from the earthquake in Turkey. It also pinpoints gaps in knowledge, outlining areas that demand further investigation. To effectively prevent and mitigate air pollution risks and associated health concerns linked to earthquakes, strategic recommendations are proposed. A key suggestion is the establishment of post-disaster air pollution monitoring systems capable of swiftly identifying emerging health issues, facilitating efficient responses, and curtailing potential long-term effects of the disaster. The paper underscores the necessity for continuous health monitoring of the affected population to mitigate possible adverse impacts on human health. These strategies play a pivotal role in reducing the likelihood of air pollution, supporting emergency response and recovery initiatives, and fostering new dedicated scientific studies.

A study of stochastic epidemic model driven by liouville fractional brownian motion coupled with seasonal air pollution

Air pollution can cause and provoke respiratory diseases. It is an important topic to the public, particularly in developing countries. Since there are many uncertain factors in the environment, stochastic differential equation model is a powerful tool to study the changes of air pollution and the transmission of infectious diseases. The removal of air pollutants as well as the transmission of diseases can be influenced by random perturbations with memories. In this research, we develop a mathematical model in the form of a system of stochastic differential equations driven by fractional Brownian motion of Liouville-type, coupled with seasonal air pollution, to study the dynamics of infectious respiratory disease spread. As a result , by using stochastic calculus techniques, we derive the equation for the level of air pollution.

Optimization of cabin seating arrangement strategies based on the Wells-Riley risk theory.

Civil aviation transport is an important source of global respiratory disease spread due to the closely-spaced environment. In order to reduce the probability of infection of passengers, an improved Wells-Riley model for cabin passenger risk assessment have been given in this work, the cabin ventilation and passenger nose and mouth orientation were considered. The model's effectiveness has been verified with published data. Finally, how the load factor and use of an empty seat scheme are associated with the number of infected people was assessed. The results demonstrated that the number of infected people positively correlates with the passenger load factor, and the most suitable load factor can be determined by controlling the final number of infected people with the condition of the epidemic situation in the departure city. Additionally, infection risk was found to be lower among passengers in window seats than in those in aisle seats and middle seats, and keeping empty seats in the middle or aisle could reduce the cabin average probability of infection by up to 37.47%. Using the model developed here, airlines can determine the optimal load factor threshold and seating arrangement strategy to improve economic benefits and reduce the probability of passenger infection.

Exploring the mechanisms of respiratory droplet generation during coughing

Model simulates the oral cavity and respiratory tract, revealing where and when droplets are produced when coughing and providing information to help prevent the spread of respiratory diseases.

Evaluation of the Spread of Respiratory Diseases in the City of Batna Cover a Period of Five Years (2018-2023)

Evaluation of the Spread of Respiratory Diseases in the City of Batna Cover a Period of Five Years (2018-2023)

Preparation and Application of High-Efficiency, Antibacterial, and Antiviral PET-PTHP Fibers.

Transmission through the respiratory tract is one of the most important ways for bacteria and viruses to infect the human body; the use of high-performance antibacterial and antiviral protective equipment is the most effective way to prevent the spread of respiratory diseases. However, at present, most personal protective equipment lacks the ability to kill pathogens. In this paper, a kind of polytetrahydropyrimidine-polyethylene terephthalate functional fiber (PET-PTHP fibers) with highly sustained antibacterial and antiviral properties was prepared. The inactivation rate of the fibers against Staphylococcus aureus and Escherichia coli was as high as 99.99%, and the antibacterial time was more than 72 h. The fibers have an obvious destructive effect on lentiviruses and can reduce the infection rate of lentiviruses in BxPC-3 cells from 25.4 to 9.7%. The cytotoxicity test, cell live/dead staining test, and cell proliferation test all confirmed that PET-PTHP fibers have no obvious cytotoxicity and good cytocompatibility. By applying the functional fibers to the inner layer of the masks, a new type of mask with adsorption, filtration, and killing properties against pathogens was prepared. The filtration efficiency of the new masks was 99.3%, and the pressure drop was 104 Pa. The new masks have excellent air permeability and filtration effect, meet the practical application conditions, and are of grade A; therefore, these masks provide medical protection as well as kill pathogens at the same time, further reducing the risk of human infection.

Differential contagiousness of respiratory disease across the United States

The initial contagiousness of a communicable disease within a given population is quantified by the basic reproduction number, R0. This number depends on both pathogen and population properties. On the basis of compartmental models that reproduce Coronavirus Disease 2019 (COVID-19) surveillance data, we used Bayesian inference and the next-generation matrix approach to estimate region-specific R0 values for 280 of 384 metropolitan statistical areas (MSAs) in the United States (US), which account for 95% of the US population living in urban areas and 82% of the total population. We focused on MSA populations after finding that these populations were more uniformly impacted by COVID-19 than state populations. Our maximum a posteriori (MAP) estimates for R0 range from 1.9 to 7.7 and quantify the relative susceptibilities of regional populations to spread of respiratory diseases. One-Sentence SummaryInitial contagiousness of Coronavirus Disease 2019 varied over a 4-fold range across urban areas of the United States.

Investigating factors in indoor transmission of respiratory disease through agent‐based modeling

AbstractThe transmission of respiratory diseases such as COVID‐19 is exacerbated in densely populated urban areas and crowded indoor settings. Despite the majority of transmissions occurring in such settings, controlling viral spread through individual‐level contacts indoors remains challenging. Experimental studies have investigated the transmission patterns of respiratory behaviors such as coughing or sneezing in controlled spatial environments. However, the effects of dynamic movement and spatial structures have been ignored, making it difficult to apply findings to urban policy and planning. To address this gap, we developed agent‐based simulations to investigate individual virus inhalation patterns across multiple scenarios in a symmetrical and formulaic indoor space. We conducted sensitivity analysis using regression emulator models to identify significant factors for viral transmission. Our results indicate positive associations with viral transmission in descending order of: (1) stay time; (2) encounter frequency; and (3) initial infected population; while negative associations are: (4) mask wearing; (5) distance to infected people; (6) nearest infected people's mask wearing; and (7) distance to entrance. We also found that narrow passages between obstacles increase virus transmission from breathing. Furthermore, we conducted a case study to investigate the potential of reducing the amount of individually inhaled virus by controlling behaviors and spatial environments. Our findings suggest that mask wearing and reduced stay time can substantially reduce transmission risk, while a large number of contacts and high grouping time result in the growth of the infected population at a certain threshold. These results provide guidance for decision makers to formulate guidelines for curbing the spread of respiratory diseases in indoor spaces.

Effects of the nozzle-to-nozzle distance on the performance of the water condensation growth-based virus aerosol concentrator

Efficient collection of airborne viruses is crucial for monitoring and preventing the spread of respiratory diseases. The laminar flow water condensation-based growth tube collector (GTC) is a microbial sampler extensively used to collect virus aerosol particles owing to its high recovery of viable viruses. The GTC involves multiple nozzles and eight tubes for sampling flow rates of 6–8 L per minute (LPM). To allow the GTC to operate at a higher flow rate, optimizing GTC performance through investigation of the effects of nozzle-to-nozzle distance is essential. Herein, we examined these effects on the collection efficiency and viability of airborne MS2 viruses collected by the growth-based virus aerosol concentrator (GVC), which is a lab-made single-tubed GTC, at flow rates of up to 6 LPM per tube. The flow interactions between adjacent jets were analyzed by observing the particle deposition patterns. The collection efficiencies of MS2 virus aerosol particles and the enrichment ratio of the GVC increased with increasing nozzle-to-nozzle distance. The infectious virus concentration relative to that in the virus suspension (RIVC) ranged from 0.0093 to 0.095 for 5 min of sampling. At flow rates of 1 and 6 LPM, the RIVC decreased as the nozzle-to-nozzle distance decreased, which may be ascribed to the higher shear stress at shorter nozzle-to-nozzle distances applied to the viruses collected through the cross-flows driven by adjacent jets. These measured RIVC values are much larger than those collected by the BioSampler. These findings can provide important insights into optimizing multiple nozzles in high-flow-rate GTCs.

Sensitive and highly rapid electrochemical measurement of airborne coronaviruses through condensation-based direct impaction onto carbon nanotube-coated porous paper working electrodes

Rapid detection of indoor airborne viruses is critical to prevent the spread of respiratory diseases. Herein, we present sensitive, highly rapid electrochemical measurement of airborne coronaviruses through condensation-based direct impaction onto antibody-immobilized, carbon nanotube-coated porous paper working electrodes (PWEs). Carboxylated carbon nanotubes are drop-cast on paper fibers to make three-dimensional (3D) porous PWEs. These PWEs have higher active surface area-to-volume ratios and electron transfer characteristics than conventional screen-printed electrodes. The limit of detection and detection time of the PWEs for liquid-borne coronaviruses OC43 are 65.7 plaque-forming units (PFU)/mL and 2 min, respectively. The PWEs showed sensitive and rapid detection of whole coronaviruses, which can be ascribed to the 3D porous electrode structure of the PWEs. Moreover, water molecules condense on airborne virus particles during air sampling, and these water-encapsulated virus particles (<4 µm) are impacted on the PWE for direct measurement without virus lysis and elution. The whole detection takes ∼10 min, including air sampling, at virus concentrations of 1.8 and 11.5 PFU/L of air, which can be due to the highly enriching and minimally damaging virus capture on a soft and porous PWE, demonstrating the potential for the rapid and low-cost airborne virus monitoring system.

Titanium dioxide nanostructures that reduce the infectivity of respiratory syncytial virus

The spread of respiratory diseases has gained significant attention since the detection and rapid global spread of COVID-19. Respiratory viruses are commonly transmitted when an infected person coughs or sneezes onto a surface, infecting persons who subsequently contact this surface. For this reason, developing surfaces with inherent antipathogenic properties is crucially needed for controlling the spread of deadly pathogens. Recent studies have established the antipathogenic potential of hydrothermally synthesised titanium dioxide (TiO2) nanostructured surfaces against bacteria strains (Gram-positive and negative) and several respiratory viruses, including SARS-CoV-2, HRV-16 and HCoV-NL63. This study investigates the antiviral behaviour of TiO2 nanostructured surfaces against Respiratory Syncytial Virus (RSV), a respiratory virus commonly contracted by children, to reduce viral transmission in high-traffic environments such as hospitals and childcare centers. Mimicking droplets produced when a person coughs or sneezes, RSV droplets were exposed to nanostructured surfaces to investigate their antiviral potential. Results show that nanostructured TiO2 reduced the RSV infectious viral load at all timepoints compared to control surfaces, showing 1.7, 2.6 and 3.2 log reductions after 2-, 5- and 7-hours exposure, respectively. Interestingly, virus exposed to nanostructured surfaces showed little to no infectivity after 5 h exposure while viable virus was still detected on control surfaces after 7 h exposure. These encouraging results establish TiO2 nanostructured surfaces as a potential method for reducing transmission and spread of respiratory viruses and bacterial strains.

Medico-Geographical Assessment of the Prevalence of Respiratory Diseases in Northern and Southern Areas of the Russian Far East: Comparison of Kamchatka and Primorsky Regions

Introduction: Diseases of the respiratory system make a significant contribution to the incidence of the Russian population. Consideration of regional differences in the distribution of respiratory diseases contributes to a better understanding of the true extent of this problem. The Primorsky and Kamchatka Regions require stabilization of the demographic situation, which is affected, inter alia, by respiratory diseases. Objective: To study spatial differences and risk factors for diseases of the respiratory system in the Primorsky and Kamchatka Regions. Materials and methods: The assessment was conducted for 2010–2020 based on official statistics on respiratory disease rates in adults and children. To study spatial differences, the epidemiological risk value was estimated for intraregional territories at the first stage of work. The second stage included identification of risk factors for the spread of respiratory diseases using methods of correlation and information entropy analysis. Results: The territories of the regions differing in the level of epidemiological risk (high, increased, moderate and low) were determined. In the Primorsky Region, a high risk of respiratory diseases for adults and children was identified on 9 and 15 territories, respectively, while in the Kamchatka Region, the numbers were found to be much lower (5 and 8). At the regional level, environmental and territorial factors had the greatest impact on respiratory disease rates in the Primorsky Region while in Kamchatka healthcare, weather and climate factors were found to be of major importance. Conclusion: The results of the assessment of long-term respiratory disease rates in the Kamchatka and Primorsky Regions show that the local situation remains difficult and tense. It is of concern since the main part of the population resides within the territories of high and elevated risk. As a rule, these are northern, distant districts both in Kamchatka and Primorye. The risk factors analyzed have regional differences.

Interleukins in serum and bronchoalveolar lavage in patients with chronic obstructive pulmonary disease or bronchial asthma after pulmonary tuberculosis or pneumonia

The spread of respiratory diseases has become a topical issue of modern medicine. The prevalence of the diseases caused the rising rates of disability and mortality among people affected by respiratory diseases. The clinical course of respiratory diseases includes the disorders of general and local adaptive and protective mechanisms and cell-mediated connections. Objective — to determine the interleukin profile of serum and bronchoalveolar lavage for the verification of chronic obstructive pulmonary disease (COPD) or bronchial asthma in patients with pulmonary tuberculosis or pneumonia with bronchial obstruction syndrome. Materials and methods. 67 patients affected by chronic obstructive pulmonary disease and 33 patients diagnosed with bronchial asthma who were hospitalized in the Pulmonology Lviv Regional Diagnostic Center during 2015—2020, were examined. The patients were verified with a non-complicated tuberculosis without any destructive changes evident in the lungs (the first or third clinical category of patients), the community-acquired pneumonia with the bronchial obstruction syndrome. Pro-inflammatory interleukins IL-1β, IL-2, IL-6, TNF-α and anti-inflammatory IL-4 in serum and bronchoalveolar lavage were revealed during the lobar and tertiary bronchi fiber-optic bronchoscopy. Results and discussion. The interleukins misbalance was evident: the decrease in IL-1β and IL-2 and the increase in IL-6 and TNF-α by 4.5 times as compared to the unaffected donors was revealed in the patients with chronic obstructive pulmonary disease. The significant decrease in IL-4 was revealed pointing at the high probability of the severe and prolonged COPD and leading to frequent exacerbation and compilations of the disease. By contrast, the patients diagnosed with bronchial asthma showed higher IL-1β and IL-2 as compared to the unaffected patients; the level of IL-6 was higher as compared to the COPD patients, while TNF-α was lower. The patients with bronchial asthma showed higher IL-4 than the unaffected donors and the patients with COPD. Conclusions. The intensity of interleukins expression (especially pro-inflammatory) revealed the level of inflammation based on the acute-phase proteins in the proteolytic-antiproteolytic balance, which may be also used as the additional criteria for the differential diagnostics and justification for the treatment optimization.

Face Masks as Sources of Cross-Contamination during Food Preparation

Amid the COVID-19 pandemic, mask-wearing has become a common practice in the foodservice industry to prevent the spread of respiratory diseases. Like kitchen utensils, a mask may serve as a vehicle for cross-contamination of pathogens during food handling. The objective of this study was to quantify cross-contamination between tasks of handling contaminated chicken and chopping lettuce. Chicken breasts were inoculated with a high or a low level of nonpathogenic Escherichia coli surrogates (ca. 6 or 4 log CFU/ml) and sliced for 1, 5, or 10 min. During slicing, duplicate, single-use medical masks were touched each minute. One mask was immediately sampled, but the second mask was used to contaminate lettuce by touching the mask each minute while chopping the lettuce for 5 min. E. coli were enumerated from the second mask and lettuce. Masks touched while slicing both high- and low-inoculated chicken showed significant contamination (0.8–4.9 log CFU/cm2) after each slicing scenario of 1, 5, or 10 min (P &gt; 0.05). Lettuce was significantly contaminated regardless of inoculation level (1.0–3.2 log CFU/g). Slicing time was a significant factor in some cases (P &lt; 0.05), whereas inoculation level was not (P &gt; 0.05). Data indicate masks can be a source of cross-contamination if not replaced appropriately.

Numerical modeling of a sneeze, a cough and a continuum speech inside a hospital lift

The global COVID-19 and its variants put us on notice of the importance of studying the spread of respiratory diseases. The most common means of propagation was the emission of droplets due to different respiration activities. This study modeled by computational fluid dynamics (CFD) techniques a high risk scenario like a hospital elevator. The cabin was provided with an extraction fan and a rack for air renewal. Inside, a sneeze, a cough and a continuum speech were simulated. Inside the lift, two occupants were introduced to observe the risk of propagation of emitted droplets and the impact in diseases spreading risk. The fan effectivity over the droplets ejection was analyzed, as well as environmental condition of a clinical setting. For this purpose the amount of droplets inside were counted during whole time of simulations. The effect of the fan was concluded as able to eject the 60% of small droplets, but also a high performance in spreading particles inside. Among the three cases, the riskiest scenario was the continuum speech due to the saturation of droplets in airborne.

CAD System Based on Face Mask Recognition for Respiratory Infections Diseases Hospital

The infection of respiratory diseases can be eliminating and controlling by wearing face mask in contaminated areas. However, to control people about wearing face mask it has been challenging unless the automatic recognitions are applied. Therefore, in this paper, a Face Mask Recognition System by Computer Aided Design (CAD) is introduced. The proposed design system is based on face, mouth and nose detections in captured image. The CAD system considers to be implemented for specialized respiratory diseases hospital with different departments, each department controlled by separated door. The main goal of this paper is to design system based on software programs that helps reduce the spread of respiratory diseases and controlling wearing face mask inside respiratory infection diseases hospital based on mask detection and mask color detection. The proposed system designed for hospital with three respiratory diseases departments and three mask color applied each mask color for each department. The mask recognition system has been used cascaded object detector that is Local Binary Pattern Histogram LBPH algorithm, then color detection as artificial intelligence-based method, Red, Green, and Blue (RGB) color of the face mask images. Finally, by using of Convolutional Neural Network (CNN), the classification accuracy of color recognition achieved 100%, and also the whole system functionality tested successfully obtained all results by testing accuracy 95%. The hardware designing circuit simulation in Proteus software were obtained to control the systems of hospital department doors based on the results obtained from MATLAB software.

The Physiological and Subjective Effects of Exercising with a Face Mask at Different Intensities

ABSTRACT Introduction Face masks are used to reduce the spread of respiratory diseases. Physical exertion increases distance traveled by expelled particles, so masking while exercising is recommended to help prevent disease transmission. However, there is limited literature assessing masking during higher-intensity exercise. Purpose This study aimed to compare the impact of surgical masks on physiological and subjective measures during 45 min of a progressive exercise protocol as compared with unmasked exercise. Methods Each subject completed two random 45-min exercise trials (15 min each at 40%, 60%, and 80% of their oxygen uptake reserve) with and without a surgical mask in random order. Heart rate, oxygen saturation, respiratory rate (RR), ratings of perceived exertion, and dyspnea (Dys) were measured at each intensity. Repeated-measures ANOVA was utilized, and significance was set at P &lt; 0.05. Results Thirty subjects (age, 20.4 ± 1.2 yr; peak oxygen uptake, 40.12 ± 11.05 mL·kg−1·min−1; 57% female) completed the study. When comparing masked and unmasked trials at each exercise intensity, differences were found only in RR (40%: 17.6 ± 4.9 vs 15.8 ± 4.9, P &lt; 0.02, d = 0.4; 60%: 23.7 ± 5.5 vs 21.3 ± 6.2, P &lt; 0.01, d = 0.4; 80%: 35.8 ± 9.0 vs 30.1 ± 8.8, P &lt; 0.01, d = 0.6). When comparing masked with unmasked trials across all intensities, a difference was found in Dys (3.5 ± 2.4 vs 2.9 ± 2.2, respectively; P &lt; 0.001, d = 0.3). Conclusions The use of surgical masks seems to impact RR and one’s perception of Dys, but has minimal influences on heart rate, oxygen saturation, and rating of perceived exertion. Other than increasing one’s RR and perceptions of Dys, it seems that exercising with a mask at moderate and vigorous intensities is acceptable in healthy individuals.

Comparative assessment of the spread of respiratory diseases of occupational etiology in regions with a highly developed mining industry

According to scientific statistical information that occupational pathology includes a number of diseases that are undesirable consequences of the working area and the nature of work. One of these diseases is pneumoconiosis. Despite improvements in mining technology, the majority of miners work in adverse conditions. The problem of pneumoconiosis continues to be relevant, both in the interests of the vast majority of the key economies of the world and for the Republic of Uzbekistan. In Europe, the preferred proportion of respiratory diseases belongs to pneumoconiosis of various etiologies - 46.8%. Respiratory diseases have been the leader among the occupational diseases which is pneumoconiosis (mainly silicosis) occupies a leading position - more than 50% of the total number of initially diagnosed diseases in Uzbekistan.

Novel estimates reveal subnational heterogeneities in disease-relevant contact patterns in the United States.

Population contact patterns fundamentally determine the spread of directly transmitted airborne pathogens such as SARS-CoV-2 and influenza. Reliable quantitative estimates of contact patterns are therefore critical to modeling and reducing the spread of directly transmitted infectious diseases and to assessing the effectiveness of interventions intended to limit risky contacts. While many countries have used surveys and contact diaries to collect national-level contact data, local-level estimates of age-specific contact patterns remain rare. Yet, these local-level data are critical since disease dynamics and public health policy typically vary by geography. To overcome this challenge, we introduce a flexible model that can estimate age-specific contact patterns at the subnational level by combining national-level interpersonal contact data with other locality-specific data sources using multilevel regression with poststratification (MRP). We estimate daily contact matrices for all 50 US states and Washington DC from April 2020 to May 2021 using national contact data from the US. Our results reveal important state-level heterogeneities in levels and trends of contacts across the US over the course of the COVID-19 pandemic, with implications for the spread of respiratory diseases.