Interior Design Aspects Affecting Infection Rate: A Systematic Review of Possible Interventions

In light of the COVID-19 pandemic, getting infected through the built environment is being studied. The measures that should be taken to reduce infection through the built environment are essential;not only for COVID-19, but this idea is present at all times of widespread diseases.The purpose of this research is to systematically review the relationship between the built environment and the spread of infection to create a potential guideline to reduce the transmission rate. Articles and studies on the relationship between infectious disease and the built environment were reviewed.Articles matching the selection criteria were identified. Most articles described peer reviews, consensus statements, and reports. The articles have provided data that can be used as guidance for reducing the transmission of infection within the built environment. It was found that evidence has been created such as ventilation, buffer spaces, flooring, and surfaces that can reduce the infection of COVID-19.

Modeling undetected live type 1 wild poliovirus circulation after apparent interruption of transmission: Pakistan and Afghanistan.

Since 2013, wild poliovirus (WPV) transmission occurred only for type 1 (WPV1). Following several years of increasing reported incidence (2017-2019) and programmatic disruptions caused by COVID-19 (early 2020), Pakistan and Afghanistan performed a large number of supplementary immunization activities (late 2020-2021). This increased intensity of immunization, following widespread transmission, substantially decreased WPV1 cases and positive environmental samples during 2021. Modeling the potential for undetected circulation of WPV1 after apparent interruption can support regional and global decisions about certification of the eradication of indigenous WPV1 transmission. We apply a stochastic model to estimate the confidence about no circulation (CNC) of WPV1 in Pakistan and Afghanistan as a function of time since the last reported case and/or positive environmental sample. Exploration of different assumptions about surveillance quality suggests a range for CNC for WPV1 as a function of time since the last positive surveillance signal, and supports the potential use of a time with no evidence of transmission of less than 3 years as sufficient to assume die out in the context of good acute flaccid paralysis (AFP) surveillance. We show high expected CNC based on AFP surveillance data alone, even with imperfect surveillance and some use of inactivated poliovirus vaccine masking the ability of AFP surveillance to detect transmission. Ensuring high quality AFP and environmental surveillance may substantially shorten the time required to reach high CNC. The time required for high CNC depends on whether immunization activities maintain high population immunity and the quality of surveillance data.

IoT-Based E-Parking System for Multiplexes and Shopping Malls

This paper helps in automating process of car parking in shopping malls. It helps in making parking more efficient by burning of less fuel. This system is useful for places with large number of people considering less people-to-people contact considering Covid Pandemic and making a safe system for minimal infection transmission from people to people. This paper aims at developing a IoT-based E-parking system. This project uses Micro-controller (ATtiny85) for controlling of sensors. Set of multiple ultrasonic sensors are put on ceilings per floor with multiple slots for detection of vehicles in parked spaces with threshold set for cars. Multiple Wi-Fi modules are used for wirelessly uploading the values of vehicles parked in different floors to cloud from where the Wi-Fi module at entrance extracts data and displays on central display at entrance for assigning empty parking slots to new vehicles on arrival. Entrance display displays number of empty slots on every floor to new customer entering mall parking system. This project achieved objective of making a system which can be used in times of Covid-19 for better safety of people. This paper has been able to achieve its main objectives of making a safe, affordable, scalable parking system which can be used in shopping malls and multiplexes. It can be scaled to large usable parking systems using better sensors and better computing devices. It can provide means of work or business to youth of city for building and selling smart vehicle parking systems and deploy them to multiple malls and multiplexes using help from staff and sell at affordable rates. It can also help make more customizable and modular smart parking systems tailored to use of system in any buildings. Arduino IDE has been used for uploading code to cloud modules in project. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Building Occupancy Simulation and Analysis under Virus Scenarios

During the COVID-19 pandemic, regulations on building usage and occupancy density were brought to the forefront, as research indicated that transmission was most likely to occur in indoor environments. Public health officials and building managers had to decide how to best use their buildings while curtailing the infection risk for their occupants.In this article, we present a systematic simulation-based methodology for estimating the infection risk for a building's occupants under different scenarios of building usage. We have evaluated our simulations against some real-world building usage data from a university campus building;our experiments demonstrate the realism of our simulations. Based on this finding, we have developed a virus transmission model that estimates the potential infection transmission risk given the behaviors of a building's occupants. Our methodology enables building managers to simulate alternative building usage scenarios and estimate their relative infection transmission risk. We argue that such risk estimate comparisons can be useful in making decision about alternative building usage options. © 2022 Association for Computing Machinery.

Interior Design Aspects Affecting Infection Rate: A Systematic Review of Possible Interventions

In light of the COVID-19 pandemic, getting infected through the built environment is being studied. The measures that should be taken to reduce infection through the built environment are essential;not only for COVID-19, but this idea is present at all times of widespread diseases. The purpose of this research is to systematically review the relationship between the built environment and the spread of infection to create a potential guideline to reduce the transmission rate. Articles and studies on the relationship between infectious disease and the built environment were reviewed. Articles matching the selection criteria were identified. Most articles described peer reviews, consensus statements, and reports. The articles have provided data that can be used as guidance for reducing the transmission of infection within the built environment. It was found that evidence has been created such as ventilation, buffer spaces, flooring, and surfaces that can reduce the infection of COVID-19.Copyright © 2022 Mohan R, et al.

Modeling and interactive simulation of measures against infection transmission

In this paper we develop an approach to modeling and simulating the process of infection transmission among individuals and the effectiveness of protective counter-measures. We base our approach on pedestrian dynamics and we implement it as an extension of the Vadere simulation framework. In order to enable a convenient simulation process for a variety of scenarios, we allow the user to interact with the simulated virtual environment (VE) during run time, for example, by dynamically opening/closing doors for room ventilation and moving/stopping agents for re-positioning their locations. We calibrate and evaluate our approach on a real-life case study—simulating COVID-19 infection transmission in two kinds of scenarios: large-scale (such as the city of Münster, Germany) and small-scale (such as the most common indoor environments—classrooms, restaurants, etc.). By using the tunable parameters of our modeling approach, we can simulate and predict the effectiveness of specific anti-COVID protective measures, such as social distancing, wearing masks, self-isolation, schools closing, etc. [ FROM AUTHOR] Copyright of Simulation is the property of Sage Publications, Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Longitudinal Study on the Antimicrobial Performance of a Polyhexamethylene Biguanide (PHMB)-Treated Textile Fabric in a Hospital Environment.

Healthcare workers in the hospital environment are at risk of infection and body fluids such as saliva, bacterial contamination, oral bacteria, etc. directly or indirectly exacerbate this issue. These bio-contaminants, when adhered to hospital linens and clothing, grow substantially, as conventional textile products provide a favorable medium for bacterial and viral growth, adding to the risk of transmitting infectious diseases in the hospital environment. Textiles with durable antimicrobial properties prevent microbial colonization on their surfaces and help contain the spread of pathogens. This longitudinal study aimed to investigate the antimicrobial performance of PHMB-treated healthcare uniforms during prolonged usage and repetitive laundry cycles in a hospital environment. The PHMB-treated healthcare uniforms displayed non-specific antimicrobial properties and remained efficient (>99% against S. aureus and K. pneumoniae) after use for 5 months. With the fact that no antimicrobial resistance was reported towards PHMB, the presented PHMB-treated uniform may reduce infection in hospital settings by minimizing the acquisition, retention, and transmission of infectious diseases on textile products.

Control measure implications of COVID-19 infection in healthcare facilities reconsidered from human physiological and engineering aspects.

The Wells-Riley model invokes human physiological and engineering parameters to successfully treat airborne transmission of infectious diseases. Applications of this model would have high potentiality on evaluating policy actions and interventions intended to improve public safety efforts on preventing the spread of COVID-19 in an enclosed space. Here, we constructed the interaction relationships among basic reproduction number (R0) - exposure time - indoor population number by using the Wells-Riley model to provide a robust means to assist in planning containment efforts. We quantified SARS-CoV-2 changes in a case study of two Wuhan (Fangcang and Renmin) hospitals. We conducted similar approach to develop control measures in various hospital functional units by taking all accountable factors. We showed that inhalation rates of individuals proved crucial for influencing the transmissibility of SARS-CoV-2, followed by air supply rate and exposure time. We suggest a minimum air change per hour (ACH) of 7 h-1 would be at least appropriate with current room volume requirements in healthcare buildings when indoor population number is < 10 and exposure time is < 1 h with one infector and low activity levels being considered. However, higher ACH (> 16 h-1) with optimal arranged-exposure time/people and high-efficiency air filters would be suggested if more infectors or higher activity levels are presented. Our models lay out a practical metric for evaluating the efficacy of control measures on COVID-19 infection in built environments. Our case studies further indicate that the Wells-Riley model provides a predictive and mechanistic basis for empirical COVID-19 impact reduction planning and gives a framework to treat highly transmissible but mechanically heterogeneous airborne SARS-CoV-2.

Pregnancy and COVID-19: past, present and future.

Current evidence suggests that severe acute respiratory syndrome coronavirus 2 infection is associated with an increased incidence of adverse severe maternal and perinatal outcomes. However, vertical transmission is rare. The management of pregnant women with coronavirus disease 2019 (COVID-19) is similar to that of non-pregnant women, and effective treatments, including antiviral therapy, dexamethasone, and prophylactic anticoagulation should not be withheld during pregnancy. During the early COVID-19 pandemic period, the management of pregnant women was often delayed until the polymerase chain reaction (PCR) results came out or due to close contact, even among those without symptoms. Out of concern for the spread of infection, cesarean sections were performed instead of vaginal birth, since infection could have led to an increase in maternal and neonatal morbidities. Additionally, if the maternal PCR test was positive, the neonate was quarantined, and despite infectivity decreasing 10 days after symptom onset. It is necessary to ease the strict measures of infection control in the field of obstetrics. The presence or absence of maternal COVID-19 symptoms should be identified to stratify the risk, and vaginal delivery can be attempted in asymptomatic women with low infectivity. With more women being vaccinated safety data about vaccination is rapidly accumulating and no concerns have been detected. Globally, COVID-19 vaccines are recommended even during pregnancy. In order to prepare for future pandemics, it is necessary to apply lessons learned from this pandemic. Policymakers and healthcare leaders must determine efficient and effective strategies for preserving safe maternal care, even during an ongoing global emergency.

COVID-19 Contact Tracing as an Indicator for Evaluating a Pandemic Situation: Simulation Study.

BACKGROUND: Contact tracing is a fundamental intervention in public health. When systematically applied, it enables the breaking of chains of transmission, which is important for controlling COVID-19 transmission. In theoretically perfect contact tracing, all new cases should occur among quarantined individuals, and an epidemic should vanish. However, the availability of resources influences the capacity to perform contact tracing. Therefore, it is necessary to estimate its effectiveness threshold. We propose that this effectiveness threshold may be indirectly estimated using the ratio of COVID-19 cases arising from quarantined high-risk contacts, where higher ratios indicate better control and, under a threshold, contact tracing may fail and other restrictions become necessary. OBJECTIVE: This study assessed the ratio of COVID-19 cases in high-risk contacts quarantined through contact tracing and its potential use as an ancillary pandemic control indicator. METHODS: We built a 6-compartment epidemiological model to emulate COVID-19 infection flow according to publicly available data from Portuguese authorities. Our model extended the usual susceptible-exposed-infected-recovered model by adding a compartment Q with individuals in mandated quarantine who could develop infection or return to the susceptible pool and a compartment P with individuals protected from infection because of vaccination. To model infection dynamics, data on SARS-CoV-2 infection risk (IR), time until infection, and vaccine efficacy were collected. Estimation was needed for vaccine data to reflect the timing of inoculation and booster efficacy. In total, 2 simulations were built: one adjusting for the presence and absence of variants or vaccination and another maximizing IR in quarantined individuals. Both simulations were based on a set of 100 unique parameterizations. The daily ratio of infected cases arising from high-risk contacts (q estimate) was calculated. A theoretical effectiveness threshold of contact tracing was defined for 14-day average q estimates based on the classification of COVID-19 daily cases according to the pandemic phases and was compared with the timing of population lockdowns in Portugal. A sensitivity analysis was performed to understand the relationship between different parameter values and the threshold obtained. RESULTS: An inverse relationship was found between the q estimate and daily cases in both simulations (correlations >0.70). The theoretical effectiveness thresholds for both simulations attained an alert phase positive predictive value of >70% and could have anticipated the need for additional measures in at least 4 days for the second and fourth lockdowns. Sensitivity analysis showed that only the IR and booster dose efficacy at inoculation significantly affected the q estimates. CONCLUSIONS: We demonstrated the impact of applying an effectiveness threshold for contact tracing on decision-making. Although only theoretical thresholds could be provided, their relationship with the number of confirmed cases and the prediction of pandemic phases shows the role as an indirect indicator of the efficacy of contact tracing.

Experimental measurement of respiratory particles dispersed by wind instruments and analysis of the associated risk of infection transmission

Activities such as singing or playing a wind instrument release respiratory particles into the air that may contain pathogens and thus pose a risk for infection transmission. Here we report measurements of the size distribution, number, and volume concentration of exhaled particles from 31 healthy musicians playing 20 types of wind instruments using aerosol size spectrometry complemented with in-line holography in a strictly controlled cleanroom environment. We find that playing wind instruments carries a lower risk of airborne disease transmission than speaking or singing. We attribute this to the fact that the resonators of wind instruments act as filters for particles >10 µm in diameter, which were found in high abundance right after a brass mouthpiece but very rarely at the instrument bell end. We have also measured the size-dependent filtering properties of different types of filters that can be used as instrument masks. Based on these measurements, we calculated the risk of airborne transmission of SARS-CoV-2 in different near- and far-field scenarios with and without masking and/or distancing. We conclude that in all cases where there is a possibility that the musician is infectious, the only safe measure to prevent airborne transmission of the disease is the use of well-fitting and well-filtering masks for the instrument and the susceptible person. © 2022 The Author(s)

Socio-demographic Heterogeneity in Prevalence of SARS-COV-2 Infection and Death Rate: Relevance to Black College Student Knowledge of COVID-19 and SARS-COV-2.

Black and Brown communities are affected disproportionately by COVID-19. In an attempt to learn if young Black college students unknowingly contribute to the spread of the COVID-19 in their communities, using surveys, this pilot study gauges the general safety knowledge and basic scientific knowledge of Black college students about SARS-COV-2 virus and COVID-19 at an HBCU. We also investigated whether students enrolled in chemistry courses designed for STEM (Science, Technology, and Engineering Majors) majors displayed increased knowledge of SARS-COV-2 and COVID-19 in comparison to their non-STEM major peers. Two sets of surveys with multiple choice questions, one with 25 and the other with 34 questions, were designed to assess general safety knowledge and basic scientific knowledge of the students about COVID-19 and the SARS-COV-2 virus. Survey questions were administered through Blackboard learning management system to one hundred eighty-seven (187) students in the summer of 2020 to two freshman non-science majors and in the fall of 2020 to one freshman non-science-major class, two freshmen STEM-major classes, and one senior STEM-major class. All students self-registered in the 6 chemistry classes at North Carolina A&T State University at random with no predetermined criteria. Results of the study show that regardless of their year of study, majority (> 90%) of the students possess basic scientific knowledge and are aware of the safety precautions concerning SARS-COV-2 virus and COVID-19. Majority of non-science major freshmen answered the basic safety questions correctly but were not able to choose the correct answers for the more specific scientific questions concerning SARS-COV-2 and COVID-19. Surprisingly, there was no significant difference in basic scientific knowledge regarding SARS-COV-2 and COVID-19 between STEM and non-STEM student populations, and first year STEM students were just as knowledgeable as senior STEM students. Based on these data, we speculate that students surveyed here have an acceptable basic understanding of how SARS-CoV-2 is transmitted, and therefore, they may not be a source of COVID-19 transmission to Black and Brown communities as this study confirms they are receiving accurate information about SARS-COV-2 and COVID-19. Possession of crucial timely and accurate knowledge about the health and safety is important in fighting racism and to gain equity within the society at large. By sharing the acquired knowledge, students can serve as positive role models for others in the community thus encouraging them to pursue science. Education brings equity, sharing the acquired knowledge encourages others to continue their education and succeed in obtaining higher degrees and better jobs as remedies for social inequality. Spread of accurate knowledge on various aspects of COVID-19 will also help remove fears of vaccination and hesitation towards visits to health clinics to resolve health issues. Relying on the results of this pilot study, we plan to explore these important factors further in our next study.

Research on the Spread and Influencing Factors of the COVID-19 Variant in the UK

This paper first establishes a clustering algorithm to cluster the data in the attachment, dividing the data into three categories, and determines the infection rate and transmission time of each virus. On this basis, the cities in four regions are selected for analysis, and a multiple regression fitting model is established to determine their corresponding transmission in different stages and regions. In order to better analyze, this paper takes Aberdeen City as an example. According to the data corresponding to the original three viruses, a grey correlation model is established to analyze the data. Finally, according to the number of confirmed cases of Omicron virus transmission, this paper estimates the duration of Omicron virus transmission by establishing a neural network prediction model. © 2022 IEEE.

A novel approach to preventing SARS-CoV-2 transmission in classrooms: A numerical study

The education sector has suffered a catastrophic setback due to the ongoing COVID pandemic, with classrooms being closed indefinitely. The current study aims to solve the existing dilemma by examining COVID transmission inside a classroom and providing long-term sustainable solutions. In this work, a standard 5 × 3 × 5 m3 classroom is considered where 24 students are seated, accompanied by a teacher. A computational fluid dynamics simulation based on OpenFOAM is performed using a Eulerian-Lagrangian framework. Based on the stochastic dose-response framework, we have evaluated the infection risk in the classroom for two distinct cases: (i) certain students are infected and (ii) the teacher is infected. If the teacher is infected, the probability of infection could reach 100% for certain students. When certain students are infected, the maximum infection risk for a susceptible person reaches 30%. The commonly used cloth mask proves to be ineffective in providing protection against infection transmission, reducing the maximum infection probability by approximately 26% only. Another commonly used solution in the form of shields installed on desks has also failed to provide adequate protection against infection, reducing the infection risk only by 50%. Furthermore, the shields serve as a source of fomite mode of infection. Screens suspended from the ceiling, which entrap droplets, have been proposed as a novel solution that reduces the infection risk by 90% and 95% compared to the no screen scenario besides being completely devoid of fomite infection mode. The manifestation of infection risk in the domain was investigated, and it was found out that in the case of screens the maximum infection risk reached the value of only 0.2 (20% infection probability) in 1325 s. © 2023 Author(s).

Infection and Prevention Control Among Nurses in Dedicated Covid-19 Ward at Private Hospital in Indonesia

Introduction: The COVID-19 pandemic demands stricter implementation of infection control and prevention, especially in breaking the chain of the spread of this disease. This study aims to determine the relationship between knowledge and infection prevention control (IPC) implementation by nurses in the COVID-19 ward at a private hospital. Methods: The study is a survey of 36 private hospitals in Indonesia. Knowledge was measured by a questionnaire related to nurses' knowledge about IPC application with 20 questions. Meanwhile, the implementation of IPC is carried out using a checklist from IPC surveillance conducted by infection prevention control nurse (IPCN). Three hundred thirty-six nurses observations were obtained from this study. Data analysis used descriptive and inferential regression to investigate the characteristics, knowledge, and implementation of IPC. Results: The results showed that almost all nurses in private hospitals had received training related to the application of IPC. Most nurses' knowledge is good, although all components have not reached maximum values. There are still several IPC components, such as patient placement, environmental, and PPE usage, that still need to be improved. No significant relationship was found between knowledge and the application of IPC in the COVID-19 ward. Conclusion: It is necessary to conduct intensive training that involves observation of essential domains of IPC for both nurses and IPCN. This study had some implications on clinical practice that components of IPC training need to more emphasize on observation skills. Further study is needed to investigate the availability of facilities in the treatment room, organizational support, and internal factors to fully capture the IPC implementation. © 2022 UPM Press. All rights reserved.

Adsorption Capacity of Plastic Foils Suitable for Barrier Resuscitation

Chest compressions and ventilation attempts can generate aerosols during resuscitation. It is important to determine whether different materials suitable for the blanketing of cardiac arrest patients can diminish exposure to aerosols. In this study, three volatile organic compounds, ethanol, acetone, and isoprene, commonly found in human breath in moistened air, acted as substitutes for aerosols. Here, we present information on the adsorption of these volatiles to three blanketing materials: polyvinyl chloride, polyethylene, and aluminum coated polyethylene terephthalate. After exposure to the surfaces of these materials the test volatiles were quantified by the proton transfer reaction-time of flight-mass spectrometry. There was a trend towards a potentially higher reduction for acetone (p = 0.071) and isoprene (p = 0.050) on polyethylene, compared to polyvinyl chloride and aluminum coated polyethylene terephthalate during the rise interval. Adsorption capacity did not differ between the foils and was between 67% and 70%. From our studies, we propose that the aluminum-coated polyethylene terephthalate surface of space blankets prove adequate to diminish exposure to volatiles in moistened air, and hence to aerosols.

A 30-day Survival and Safety of Percutaneous Tracheostomy in Moderate-to-severe COVID-19 Pneumonia Patients: A Single-center Experience.

Aims and objectives: In coronavirus disease-2019 (COVID-19) pneumonia, guidelines on timing and method of tracheostomy are evolving. The aim of the study was to analyze the outcomes of moderate-to-severe COVID-19 pneumonia patients who required tracheostomy and the safety with regard to the risk of transmission to the healthcare workers. Materials and methods: We retrospectively analyzed 30-day survival outcome of a total of 70 moderate-to-severe COVID-19 pneumonia patients on a ventilator, wherein tracheostomy was performed only in 28 (tracheostomy group), and the remaining were with endotracheal intubation beyond 7 days (non-tracheostomy group). Besides demographics, comorbidities and clinical data including 30-day survival and complications of tracheostomy were analyzed in both groups with respect to the timing of tracheostomy from the day of intubation. Healthcare workers were monitored for COVID-19 symptoms by carrying out periodical COVID tests. Results: The 30-day survival of the tracheostomy group was 75% as compared to 26.2% of the non-tracheostomy group. The majority of the patients (71.4%) had severe disease with PaO2/FiO2 (P/F ratio) <100. The first wave showed an 80% (4/5) while the second wave 100% (8/8) thirty days survival in the tracheostomy group performed before 13 days. All patients during the second wave underwent tracheostomy before 13 days with a median of 12th day from the day of intubation. These tracheostomies were performed percutaneously at the bedside, without any major complications and no transmission of disease to healthcare workers. Conclusion: Early percutaneous tracheostomy within 13 days of intubation demonstrated a good 30-day survival rate in severe COVID-19 pneumonia patients. How to cite this article: Shah M, Bhatuka N, Shalia K, Patel M. A 30-day Survival and Safety of Percutaneous Tracheostomy in Moderate-to-severe COVID-19 Pneumonia Patients: A Single-center Experience. Indian J Crit Care Med 2022;26(10):1120-1125.

Real-Time Learning and Monitoring System in Fighting against SARS-CoV-2 in a Private Indoor Environment.

The SARS-CoV-2 virus has posed formidable challenges that must be tackled through scientific and technological investigations on each environmental scale. This research aims to learn and report about the current state of user activities, in real-time, in a specially designed private indoor environment with sensors in infection transmission control of SARS-CoV-2. Thus, a real-time learning system that evolves and updates with each incoming piece of data from the environment is developed to predict user activities categorized for remote monitoring. Accordingly, various experiments are conducted in the private indoor space. Multiple sensors, with their inputs, are analyzed through the experiments. The experiment environment, installed with microgrids and Internet of Things (IoT) devices, has provided correlating data of various sensors from that special care context during the pandemic. The data is applied to classify user activities and develop a real-time learning and monitoring system to predict the IoT data. The microgrids were operated with the real-time learning system developed by comprehensive experiments on classification learning, regression learning, Error-Correcting Output Codes (ECOC), and deep learning models. With the help of machine learning experiments, data optimization, and the multilayered-tandem organization of the developed neural networks, the efficiency of this real-time monitoring system increases in learning the activity of users and predicting their actions, which are reported as feedback on the monitoring interfaces. The developed learning system predicts the real-time IoT data, accurately, in less than 5 milliseconds and generates big data that can be deployed for different usages in larger-scale facilities, networks, and e-health services.

Investigating dilution ventilation control strategies in a modern U.S. school bus in the context of the COVID-19 pandemic.

Fresh air ventilation has been identified as a widely accepted engineering control effective at diluting air contaminants in enclosed environments. The goal of this study was to evaluate the effects of selected ventilation measures on air change rates in school buses. Air changes per hour (ACH) of outside air were measured using a well-established carbon dioxide (CO2) tracer gas decay method. Ventilation was assessed while stationary and while traversing standardized route during late autumn/winter months in Colorado. Seven CO2 sensors located at the driver's seat and at passenger seats in the front, middle, and rear of the bus yielded similar and consistent measurements. Buses exhibited little air exchange in the absence of ventilation (ACH = 0.13 when stationary; ACH = 1.85 when mobile). Operating the windshield defroster to introduce fresh outside air increased ACH by approximately 0.5-1 ACH during mobile and stationary phases. During the mobile phase (average speed of 23 miles per hour (mph)), the combination of the defroster and two open ceiling hatches (with a powered fan on the rear hatch) yielded an ACH of approximately 9.3 ACH. A mobile phase ACH of 12.4 was achieved by the combination of the defroster, ceiling hatches, and six passenger windows open 2 inches in the middle area of the bus. A maximum mobile phase ACH of 22.1 was observed by using the defroster, open ceiling hatches, driver window open 4 inches, and every other passenger window open 2 inches. For reference, ACHs recommended in patient care settings where patients are being treated for airborne infectious diseases range from 6 to ≥12 ACHs. The results indicate that practical ventilation protocols on school buses can achieve air change rates thought to be capable of reducing airborne viral transmission to the bus driver and student passengers during the COVID-19 pandemic.

Contact tracing as a measure to combat COVID-19 and other infectious diseases.

BACKGROUND: Most of the mathematical modeling studies on COVID-19 transmission are based on continuous deterministic models that do not consider the characteristics of social networks. METHODS: The effect of contact tracing on mitigating COVID-19, and other infectious diseases in general, is studied in a small-world network. This network has its advantages over the commonly used continuous deterministic mathematical models in that the characteristics of social networks can be properly incorporated. RESULTS: Simulation results show that for the original strain of SARS-CoV-2, contact tracing can play an important role in reducing and delaying the peak daily new cases. New cases can be reduced by using symptom onset to isolate tracked individuals, but the benefit can be greatly enhanced by testing asymptomatic and presymptomatic individuals on the sixth to eighth day of infection. For the delta variant, or other variants of much higher infectivity, contact tracing alone cannot significantly lower the number of daily new cases but is able to delay the peaks greatly, thus affording more time to explore and implement pharmaceutical interventions. CONCLUSIONS: Contact tracing can be a very powerful tool to combat COVID-19 caused by the original strain or any variant of SARS-CoV-2. In order to make contact tracing effective, every effort is needed to expand the pool of contact tracing and provide all necessary support to the self-quarantined.