Survey on knowledge and behaviors related to covid–19 and plague prevention and control in qinghai

Objective To understand the knowledge of COVID-19 and plague prevention and control in Qinghai Province, so as to carry out targeted health education and improve people's ability to prevent and control COVID–19, plague and other publichealth emergencies. Methods Six counties were randomly selected from three cities (states) by two-stage sampling. A self- designed questionnaire was randomly distributed to the public to investigate the awareness and behavior of COVID-19 and plague prevention and control. The Chinese version of Epidate was used for database construction and data entry. After checking and verifying, the data was exported as an Excel file and analyzed by SPSS 21.0 software. Results Accordign to the recovered questionnaires, the passing rate of knowledge of COVID-19 prevention and control was 78.46%, and the average score was (75. 82±16.43). The passing rate of plague prevention and control knowledge was 91.89%, and the average score was (86.46±15.94). The survey area, occupation category, gender and education level affected the knowledge of COVID-19 prevention and control. The average score was statistically significant (P<0.05). The survey area, occupation category, age and education level affected the knowledge of plague prevention and control, and the average score was statistically significant (P<0. 05). Conclusion People in Qinghai have poor knowledge of COVID - 19 prevention and control, but have good knowledge of plague prevention and control. Health education and health promotion activities on COVID - 19 and plague prevention and control should be increased in the future. © 2023, Editorial Department of Medical Pest Control. All rights reserved.

Designing an Empathy Training for Depression Prevention Using Virtual Reality and a Preliminary Study

As virtual reality (VR) is labeled by many as 'an ultimate empathy machine,' immersive VR applications have the potential to assist in empathy training for mental healthcare such as depression [21]. In responding to the increasing numbers of diagnosed depression throughout COVID-19, a first-person VR adventure game called 'Schwer' was designed and prototyped by the authors' research team to provide a social support environment for depression treatment. To continue the study and assess the training effectiveness for an appropriate level of empathy, this current article includes a brief survey on data analytics models and features to accumulate evidence for the next phase of the study, an interactive game-level design for the 'Reconstruction' stage, and a preliminary study with data collection. The preliminary study was conducted with a post-game interview to evaluate the design of the levels and their effectiveness in empathy training. Results showed that the game was rated as immersive by all participants. Feedback on the avatar design indicated that two out of three of the non-player characters (NPCs) have made the intended effect. Participants showed mostly positive opinion towards their experienced empathy and provided feedback on innovative teleport mechanism and game interaction. The findings from the literature review and the results of the preliminary study will be used to further improve the existing system and add the data analytics model training. The long-term research goal is to contribute to the healthcare field by developing a dynamic AI-based biofeedback immersive VR system in assisting depression prevention. © 2023 IEEE.

[Improvement of China's legal system for public health emergency management from the perspective of lifecycle management].

A crucial lesson gained through the pandemic preparedness and response to COVID-19 is that all measures for epidemic control must be law-based. The legal system is related not only to public health emergency management per se but also to all aspects of the institutional supporting system throughout the lifecycle. Based on the lifecycle emergency management model, this article analyses the problems of the current legal system and the potential solutions. It is suggested that the lifecycle emergency management model shall be followed to establish a more comprehensive public health legal system and to gather the intelligence and consensus of experts with different expertise, including epidemiologists, sociologists, economists, jurist and others, which will collaboratively promote the science-based legislation in the field of epidemic preparedness and response for the establishment of a comprehensive legal system for public health emergency management and with Chinese characteristics.

The effect of eating restaurant prepared food on BMI: evidence from China during the COVID-19 pandemic

Leveraging the unexpected variation in the frequency of eating restaurant prepared food due to the COVID-19 pandemic, we seek to identify and estimate the causal relationship between the frequency of eating restaurant prepared food and people's BMI. We use first-differencing and instrumental variable approaches to correct for potential endogeneity bias due to both the time-invariant and time-varying unobserved factors. Our results show eating more restaurant prepared food has a positive and statistically significant effect on BMI, and in addition to other channels that have been identified in the literature, mood-boosting is another channel through which eating restaurant prepared food leads to weight gain. Heterogeneous effect analysis further shows that eating restaurant prepared food is more likely to have an impact on those people who lead a more stressful lifestyle before the pandemic.

Effect of Different Factors on the Quality of Life and Sequelae of COVID-19 Patients after Discharge

Background The continued spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remains an international public health emergency, resulting in a significant global disease burden. The long-term effects of SARS-CoV-2 infection in humans and the long-term prognosis of patients with coronavirus disease 2019 (COVID-19) after discharge remain unclear. We aimed to assess the quality of life (QoL) and sequelae in patients with COVID-19 after discharge from the hospital by conducting multiple follow-up visits to understand the long-term effects of SARS-CoV-2 on patients' health and its possible influencing factors. Methods COVID-19 patients discharged from Huoshenshan Hospital (Wuhan, China) between February 15 and April 5, 2020, were followed up at 6, 9, and 12 months after discharge. They completed questionnaires on postdischarge QoL and sequelae under the guidance of medical staff with professional training. The demographic and clinical characteristics of the COVID-19 patients were analyzed using descriptive statistics. A generalized estimating equation model was used to analyze the QoL-related factors. The χ2 test (or Fisher exact test) and multivariate logistic regression analysis were used to analyze the sequelae and influencing factors. Results A total of 175 patients participated in at least 1 follow-up visit, and 120 completed all 3 follow-up visits. Patients diagnosed with severe and critically ill COVID-19 had worse mental conditions (χ2 = 7.653, P = 0.022) than those with the nonsevere type (not severe or critical) and were more likely to feel fatigued (χ2 = 4.836, P = 0.028). Female patients had a higher risk of sleep disturbance (χ2 = 10.026, P = 0.002) and dyspnea (χ2 = 5.672, P = 0.017) and had more difficulty returning to their original work and life (χ2 = 8.922, P = 0.003) than male patients. Patients with diabetes had a worse appetite (χ2 = 4.669, P = 0.031) and were more prone to sleep disturbance (χ2 = 4.417, P = 0.036) after discharge. The proportion of patients with at least 1 sequela increased from 29.76% (50/168) at 6 months to 51.11% (69/135) at 9 months (χ2 = 14.305, P < 0.001). Compared with the nonsevere type, patients diagnosed with severe and critically ill COVID-19 had an odds ratio (OR) of 4.325 (95% confidence interval [CI], 1.215-15.401) for memory decline. Female patients had an OR of 4.632 (95% CI, 1.716-12.501) for joint or muscle pain. Patients with hypertension had an OR of 3.014 (95% CI, 1.193-7.615) for joint or muscle pain. Conclusion One year after discharge, there were still some patients with varying degrees of decline in QoL and sequelae, which occurred in all follow-up visits. Moreover, QoL and sequelae after discharge were related to sex, clinical classification of COVID-19, and underlying diseases. © Wolters Kluwer Health, Inc. All rights reserved.

Federated Learning for Medical Imaging Segmentation via Dynamic Aggregation on Non-IID Data Silos

A large number of mobile devices, smart wearable devices, and medical and health sensors continue to generate massive amounts of data, making edge devices' data explode and making it possible to implement data-driven artificial intelligence. However, the "data silos” and other issues still exist and need to be solved. Fortunately, federated learning (FL) can deal with "data silos” in the medical field, facilitating collaborative learning across multiple institutions without sharing local data and avoiding user concerns about data privacy. However, it encounters two main challenges in the medical field. One is statistical heterogeneity, also known as non-IID (non-independent and identically distributed) data, i.e., data being non-IID between clients, which leads to model drift. The second is limited labeling because labels are hard to obtain due to the high cost and expertise requirement. Most existing federated learning algorithms only allow for supervised training settings. In this work, we proposed a novel federated learning framework, MixFedGAN, to tackle the above issues in federated networks with dynamic aggregation and knowledge distillation. A dynamic aggregation scheme was designed to reduce the impact of current low-performing clients and improve stability. Knowledge distillation was introduced into the local generator model with a new distillation regularization loss function to prevent essential parameters of the global generator model from significantly changing. In addition, we considered two scenarios under this framework: complete annotated data and limited labeled data. An experimental analysis on four heterogeneous COVID-19 infection segmentation datasets and three heterogeneous prostate MRI segmentation datasets verified the effectiveness of the proposed federated learning method. © 2023 by the authors.

Co-Evolutionary Location-Routing Model of Medical Isolation Areas for Major Public Health Emergencies Considering the Uncertainty of Future Traffic Environment

With the continuous development of the COVID-19 pandemic, the selection of locations for medical isolation areas has not always been optimal for the timely transportation of infected people, or those suspected of being infected. This has resulted in failure to control the rate of spread of infection cases in time. To address this problem, this paper proposes a co-evolutionary location-routing optimization (CELRO) model of medical isolation areas for use in major public health emergencies to develop a rapid location-routing scheme for epidemic isolation, including the selection of locations of medical isolation facilities per area and the optimal route per vehicle to each infected person. Specifically, this paper solves the following two sub-problems: (i) calculate the shortest transportation times and corresponding routes from any medical isolation area to any person infected or suspected of being infected, and (ii) calculate the location scheme for distribution of isolation areas. Different from previous studies, the vehicle operating characteristics and the interference of uncertainty of the traffic environment are considered in the proposed model. To find an appropriate scheme for location of medical isolation areas with the shortest travel times, a co-evolutionary clustering algorithm (CECA), which is a combination of some separated evolutionary programming operations, is proposed to solve the model. Various network sizes and uncertainty combinations are used to design some comparative tests, which aim to verify the effectiveness of the proposed model. In the experiment section, CELRO reduced travel time by at least 14% compared with other methods. This finding can provide an effective theoretical basis for optimizing the spatial layout of medical isolation areas or the location planning of new medical facilities. © National Academy of Sciences.

Smart Mirror Activated by User's Face Recognition with Simulation of Artificial Intelligence Classifier

This paper presented a simple and easy-To-use intelligent mirror with the activated function by face recognition. Firstly, the function of face recognition was realized by the OpenMV platform, and the recognition information was transmitted to the main controller, i.e., Loongson 1C Zhilong development board. The main controller connected to the Django server through the distant communication function of ESP8266 module. The user's schedules were acquisitioned by such a communication pathway and analyzed by the main controller. Finally, the recognized user's business or traveling schedule was shown on a screen located in the rear of a semitransparent mirror. For strangers of this smart mirror, the successful rate of strangers was 100%. For the user, the successful rate of strangers was 90% and accuracy of user's recognition was 100% in 120 times of tests. Furthermore, Adaptive Neuro Fuzzy Inference System supports a nice performance for Automatic classification in computer simulation. The COVID-19 pandemic is still threatening human beings. A smart mirror with the function of face recognition activation is a non-Touching solution for avoiding the infections to support an idea for elevating human health. © 2023 Global IT Research Institute (GiRI).

A new autophagy-driven protective pathway of Haematococcus astaxanthin against chemical damage in wistar rats with gentamicin-induced acute kidney injury

Astaxanthin was established to conserve kidney function and subcellular structure through anti-oxidation and/or the free radical scavenging system, yet little research linked a new protective effect to autophagy or lysosomes. We pre-fed Wistar rats with natural astaxanthin, β-carotene, or placebo and induced acute kidney injury using gentamicin, before examining renal tissues and measuring physiological indices. Qualitative evidence from histopathological and subcellular images, along with quantitative evidence showing treatment effects on blood urea nitrogen and serum creatinine (p < 0.01), indicated that esterified Haematococcus astaxanthin surpassed β-carotene at effectively counteracting chemical damage and protecting the kidneys from injury. Proliferation of enlarged lysosomes and mediation analysis results revealing enhanced lysosomal acid phosphatase activity were consistent with the hypothesized autophagy-lysosomal pathway being up-regulated by astaxanthin intake (p < 0.05). In conclusion, the protective effect of astaxanthin against acute kidney injury exerted through the autophagy-lysosomal detoxification pathway, which totally different from the anti-oxidation and/or conventional SOD-dependent free radical scavenging system, was demonstrated with strong evidence. In light of the pandemic outbreak of novel coronavirus pneumonia associated with a virus preferentially targeting the renal tubular cells, dietary astaxanthin may help bring down incidence rate of coronavirus disease, cases of acute kidney injury secondary to the disease, and mortality rate from acute kidney injury, especially when a standard of care treatment for the infectious disease is pending. © 2023 Elsevier B.V.

Multi-subject collaborative prevention and control of adolescent myopia in China

Improving the system of adolescent myopia prevention and control and promoting adolescent healthy development is one of the main directions of healthy China construction in the new era. The paper reviewed national myopia policies and local practices and proposed reflections on the high burden and complex etiology of myopia among adolescents as well as unclear role and lack of coordination mandate during the COVID-19 epidemic. Based on the synergy theory through the analysis of the functional positioning of multiple subjects in the prevention and control of myopia the paper highlighted the multi-party linkage of government schools medical institutions communities families and markets profiling the resources and advantages of each subject as well as dynamic management of adolescent myopia as well as a multi-subject collaborative prevention and control system with national unity clear rights and responsibilities and long-term cooperation. © 2023 Journal of Chinese Agricultural Mechanization. All rights reserved.

Assessment of aerosol persistence in ICUs via low-cost sensor network and zonal models.

The COVID-19 pandemic raised public awareness about airborne particulate matter (PM) due to the spread of infectious diseases via the respiratory route. The persistence of potentially infectious aerosols in public spaces and the spread of nosocomial infections in medical settings deserve careful investigation; however, a systematic approach characterizing the fate of aerosols in clinical environments has not been reported. This paper presents a methodology for mapping aerosol propagation using a low-cost PM sensor network in ICU and adjacent environments and the subsequent development of the data-driven zonal model. Mimicking aerosol generation by a patient, we generated trace NaCl aerosols and monitored their propagation in the environment. In positive (closed door) and neutral-pressure (open door) ICUs, up to 6% or 19%, respectively, of all PM escaped through the door gaps; however, the outside sensors did not register an aerosol spike in negative-pressure ICUs. The K-means clustering analysis of temporospatial aerosol concentration data suggests that ICU can be represented by three distinct zones: (1) near the aerosol source, (2) room periphery, and (3) outside the room. The data suggests two-phase plume behavior: dispersion of the original aerosol spike throughout the room, followed by an evacuation phase where "well-mixed" aerosol concentration decayed uniformly. Decay rates were calculated for positive, neutral, and negative pressure operations, with negative-pressure rooms clearing out nearly twice as fast. These decay trends closely followed the air exchange rates. This research demonstrates the methodology for aerosol monitoring in medical settings. This study is limited by a relatively small data set and is specific to single-occupancy ICU rooms. Future work needs to evaluate medical settings with high risks of infectious disease transmission.

Parallel coordinate visualization of edge bundling based on comprehensive index evaluation of media platform: Take the comparative analysis of industry big data in the post-epidemic era as an example

The outbreak of Covid-19 in specific areas characterized with global industrial chain reconstruction, grasps the epidemic prevention and control, while the growth of economics is the key point of government management in the post-epidemic time scale. In the last two years, various industries were affected by the outbreak of the new champions league experience "determination to keep factories and workers idle - to return to work and production - not to return to work and production”, which significantly changes the industrial performances. Both industry change and the development of the pattern of economic evaluation are equally important. This study used media platform composite index and edge parallel coordinates visualization method of combining the bundle, selected in 2020 and 2021, 11 industry information volume in 7 platform, through the medium of agenda building industry change from comparative analysis of two developing and development situation. This paper indicated that the major factors influencing the change of media attention in the course of the epidemic were the degree of social risk and the basic needs of the public. The epidemic had a great impact on the development of all industries, and the continuous improvement of the industry's ability to deal with major risks became the main trend of future development. © 2022 SPIE.

Analysis of the Status and Influencing Factors of Online Learning

During the COVID-19 prevention and control period, large-scale online education was the largest digital transformation practice in education in human history. This study launched a questionnaire survey on primary and high school students. The survey was conducted from four aspects: demographics, online learning preparation, the online learning situations, and online learning experience. This study thoroughly investigated the status and problems of students' online learning and analysed the characteristics of students' online learning and the differences amongst grades. The study found that students have high adaptability and continuance intention to online learning. This study found that students also had some learning difficulties in the process of online learning, mainly manifested by lack of interaction, difficulty in concentration, and lack of learning initiative. There were significant differences among different grades. The overall situation of junior high school students' online learning is better than that of primary school students and senior high school students. © 2022, Canadian Network for Innovation in Education. All rights reserved.

Visualization of Parallel Coordinates Based on Comprehensive Index Evaluation of Media Platforms and Economic Psychology

After experiencing problems such as shutdown and limited offline activities caused by the COVID-19 pandemic, various industries have taken the initiative to take self-help measures such as Internetization, which makes the industry economy change significantly in the post-pandemic era and makes it necessary to re-evaluate the industry economic pattern. However, online public opinion is diverse and platform content is complex. Therefore, it is essential to observe economic activities from the network information platform and complete the screening and purification of information. In order to improve the degree of quantification, and deepen the understanding of data, this paper solves the above problems through parallel coordinate visualization. At the same time, the lines in the parallel axis are used to indicate the amount and specific trend of industry information, which not only reflects the role of parallel coordinate visualization methods in industry dynamic analysis and real-time display but also makes industry development forecasts more feasible. © 2022 The authors and IOS Press.

Analysis of Sars-Cov-2-Specific T-Cell Responses Using Novel Single- Cell Multiplexed Isolight in Covid-19 Convalescents

Purpose: COVID-19 has poor outcomes in transplant recipients with reduced antibody responses. However, the exact cellular immune response against SARS-CoV-2 remains largely unclear. We developed novel assays to analyze differential cellular immune responses in individual subjects and groups. Method(s): We assessed the T cell proliferative responses against spike, membrane, and nuclear proteins of SARS-CoV-2, or a mixture of all these peptides (mix) using 3H-thymidine incorporation and CFSE dilution assays. We have also established a SARS-CoV-2-specific multiplexed cytokine IsoLight at single-cell resolution. This is a very powerful technology that employs IsoPlexis' IsoCodechip with 12,000 micro-chambers. Each microchamber is pre-coated with a 32-plex antibody array to capture secreted cytokines. The results were evaluated using IsoSpeak software. Result(s): COVID-19 convalescent subjects (n=3) showed a very strong proliferative response to S/M/N and mix peptides of SARS-CoV-2 when compared to uninfected normal subjects who had only marginal proliferative responses. CFSE dilution assays demonstrated that spike and mix proteins markedly increased the proliferation of CD3 cells comprised of both CD4 and CD8 subsets. In the IsoLight assay, single-cell functional heterogeneity mapping 3D tSNE analysis showed a distinct combinatorial cytokine secretion pattern in stimulated cells compared to unstimulated controls (Fig.1). Polyfunctional activity topography-Principal component analysis (PAT-PCA) revealed that IFN-g, IL2, and MIP-1b drove the polyfunctional heterogeneity. When the percentage of polyfunctional cells (>=2 cytokines/cell), and polyfunctional strength index (PSI) were evaluated, CD8 cells secreted high levels of effector and chemoattractive cytokines while CD4 cells secreted effector and stimulatory cytokines. Most importantly, the depth and breadth of T cell responses, particularly the cytokine polyfunctionality correlated with the severity of the disease the patients had experienced. Conclusion(s): This novel COVID19-specific IsoLight cytokine assay is a powerful technology that can be utilized for in-depth analysis of T cell polyfunctionality at the single-cell level and for further differentiating the anti-SARS-CoV-2 immune capabilities of vulnerable individuals such as transplant patients.

Age Estimation with Synthetic Mask Generation Based on MobileNet and Facial Keypoint Detection

Facial age estimation is one of the most important tasks in the field of face recognition and recommendation system. Since the COVID-19 pandemic, people have been required to wear masks, which can be a challenge for traditional recognition methods. In this paper, an improved convolutional neural network architecture based on MobileNet is proposed to perform age estimation. For the challenge of masked faces, an innovative mask generation method using face keypoint detection is adopted, extracting the key points of the faces in order to add synthetic masks to simulate the real situations. Then we compare the estimation results of the original images and the synthetic images. Our method is applied to the WIKI Face dataset containing more than 150,000 images, and achieves MAE of 3.79 and 6.54 on unmasked and masked faces, respectively, which demonstrates the effectiveness of the proposed model. © 2022 IEEE.

Semen parameters and sex hormones as affected by SARS-CoV-2 infection: A systematic review.

BACKGROUND: Impaired semen quality and reproductive hormone levels were observed in patients during and after recovery from coronavirus disease 2019 (COVID-19), which raised concerns about negative effects on male fertility. Therefore, this study systematically reviews available data on semen parameters and sex hormones in patients with COVID-19. METHODS: Systematic search was performed on PubMed and Google Scholar until July 18th, 2022. We identified relevant articles that discussed the effects of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on male fertility. RESULTS: A total number of 1,684 articles were identified by using a suitable keyword search strategy. After screening, 26 articles were considered eligible for inclusion in this study. These articles included a total of 1,960 controls and 2,106 patients. When all studies were considered, the results showed that the semen parameters and sex hormone levels of patients infected with SARS-CoV-2 exhibited some significant differences compared with controls. Fortunately, these differences gradually disappear as patients recover from COVID-19. CONCLUSION: While present data show the negative effects of SARS-CoV-2 infection on male fertility, this does not appear to be long-term. Semen quality and hormone levels will gradually increase to normal as patients recover.

A Triangle Framework among Subgraph Isomorphism, Pharmacophore and Structure-function Relationship

Coronavirus disease 2019 (COVID-19) has gained utmost attention in the current time from academic research and industrial practices because it continues to rage in many countries. Pharmacophore models exploit molecule topological similarity as well as functional compound similarity so that they can be reliable via the application of the concept of bioisosterism. In this work, we analyze the targets for coronavirus protein and the structure of RNA virus variation, thereby complete the safety and pharmacodynamic action evaluation of small-molecule anti-coronavirus oral drugs. Common pharmacophore identifications could be converted into subgraph querying problems, due to chemical structures can also be converted to graphs, which is a knotty problem pressing for a solution. We adopt simplified representation pharmacophore graphs by reducing complete molecular structures to s to detect isomorphic topological patterns and further to improve the substructure retrieval efficiency. Our threefold architecture subgraph isomorphism-based method retrieves query subgraphs over large graphs. First, by means of extracting a sequence of subgraphs to be matched and then comparing the number of vertex and edge between the potential isomorphic subgraphs and the query graph, we lower the computational scaling markedly. Afterwards, the directed vertex and edge matrix recording vertex and edge positional relation, directional relation and distance relation has been created. Then, on the basis of permutation theorem, we calculate the row sum of vertex and edge adjacency matrix of query graph and potential sample. Finally, according to equinumerosity theorem, we check the eigenvalues of the vertex and edge adjacency matrices of the two graphs are equinumerous. The topological distance could be calculated based on the graph isomorphism and the subgraph isomorphism can be implemented after the combination of the subgraph. The proposed quantitative structure-function relationships (QSFR) approach can be effectively applied for pharmacophoric patterns identification. The framework of new drug development for covid-19 has been established based on this triangle. © 2022 ACM.

A Bibliometric Analysis on Research Trends of Digital Literacy in Higher Education from 2012 to 2021

Digital literacy is a multidimensional concept that encompasses a complex integration of knowledge, skills, attitudes, and cognition dimensions, which gains increased attention in the context of higher education. The objective of this study is to analyze the scientific production of digital literacy in higher education from 2012 to 2021 based on the Scopus database, and reveal the current research trends on this subject. To this end, a bibliometric study was carried out, which first investigated some variables that addressed different features, from the distribution of publications to the most productive countries/regions and the prolific publication venues, and continued with the analysis of the authors and the keywords co-occurrence through VOSviewer software. The results show that the most frequently explored themes in the area of digital literacy can be detected, which focused on the integration of digital technology, ontology research and the educational practices of digital literacy, and the effectiveness evaluation of digital literacy in the time of the COVID-19 pandemic. The findings of this study are beneficial for researchers to gain a comprehensive understanding of digital literacy in the domain of higher education, and provide new directions for future research © 2022, International Journal of Emerging Technologies in Learning.All Rights Reserved.

Measuring aerosols in the operating theatre and beyond using a real-time sensor network.

The ability to measure and track aerosols in the vicinity of patients with suspected or confirmed COVID-19 is highly desirable. At present, there is no way to measure and track, in real time, the sizes, dispersion and dilution/disappearance of aerosols that are generated by airway manipulations such as mask ventilation; tracheal intubation; bronchoscopy; dental and gastro-intestinal endoscopy procedures; or by vigorous breathing, coughing or exercise. We deployed low-cost photoelectric sensors in five operating theatres between surgical cases. We measured and analysed dilution and exfiltration of aerosols we generated to evaluate air handling and dispersion under real-world conditions. These data were used to develop a model of aerosol persistence. We found significant variation between different operating theatres. Equipment placement near air vents affects air flows, impacting aerosol movement and elimination patterns. Despite these impediments, air exchange in operating theatres is robust and prolonged fallow time before theatre turnover may not be necessary. Significant concentrations of aerosols are not seen in adjoining areas outside of the operating theatre. These models and dispersion rates can predict aerosol persistence in operating theatres and other clinical areas and potentially facilitate quantification of risk, with obvious and far-reaching implications for designing, evaluating and confirming air handling in non-medical environments.