Evaluating the Knowledge of and Behavior Toward COVID-19 and the Possibility of Isolating at a City Level: Survey Study

BACKGROUND

Mass testing campaigns were proposed in France during the first wave of the COVID-19 pandemic to detect and isolate asymptomatic individuals infected by SARS-CoV-2. During mass testing in Saint-Étienne (February 2021), we performed a survey of the general population.

OBJECTIVE

We evaluated, on the scale of a city's population, the literacy level about SARS-CoV-2 transmission, barrier gesture respect, and isolation acceptability or possibility in case of SARS-CoV-2 infection.

METHODS

We used the validated CovQuest-CC questionnaire. Data were analyzed and correlated with volunteer characteristics and their SARS-CoV-2 screening results using multivariate analysis.

RESULTS

In total, 4707 participants completed the CovQuest-CC questionnaire. Multivariate analysis revealed that female sex was a determinant of a higher score of knowledge about SARS-CoV-2 transmission (adjusted β coefficient=0.14, 95% CI 0.04-0.23; corrected P=.02). Older ages of 50-59 years (adjusted β coefficient=0.25, 95% CI 0.19-0.31; corrected P<.001) and ≥60 years (adjusted β coefficient=0.25, 95% CI 0.15-0.34; corrected P<.001) were determinants of a higher score on barrier gesture respect compared to ages 20-49 years considered as reference. Female sex was also a determinant of a higher score on barrier gesture respect (adjusted β coefficient=0.10, 95% CI 0.02-4.63; corrected P<.001). The knowledge score was correlated with the score on barrier gesture respect measures (adjusted β coefficient=0.03, 95% CI 0.001-0.004; corrected P=.001). Older ages of 50-59 years (adjusted β coefficient=0.21, 95% CI 0.13-0.29; corrected P<.001) and ≥60 years (adjusted β coefficient=0.25, 95% CI 0.1-0.38; corrected P<.001) were determinants of a higher score on isolation acceptability or possibility compared to the age of 20-49 years considered as reference. Finally, the knowledge score regarding SARS-CoV-2 transmission was significantly associated with a lower risk of RT-PCR (reverse transcriptase-polymerase chain reaction) positivity (adjusted odds ratio 0.80, 95% CI 0.69-0.94; corrected P<.03), implying that a 1-point increase in the knowledge score lowers the risk of positivity by 20% on average.

CONCLUSIONS

This study identified factors associated with health literacy regarding SARS-CoV-2 infection in asymptomatic individuals in a large French city's population. We can confirm that in the context of the COVID-19 pandemic, the determinants of better health literacy are not the same as those in other contexts. It seems critical to obtain a more detailed understanding of the determinants of individual citizens' behavior, as part of a strategy to combat the large-scale spread of the virus. The harsh experience of this pandemic should teach us how to nurture research to structure customized interventions to encourage the adoption of ad hoc behaviors to engage citizens in adapting behaviors more favorable to their health.

Incidence of asymptomatic COVID-19 positivity in cancer patients and effects on therapy

PURPOSE

The coronavirus disease 2019 (COVID-19) pandemic is posing unprecedented challenges for patient care, especially for cancer patients. This study looks at asymptomatic (AS) COVID-19 positivity in cancer patients and its effects on their care.

METHODS

We conducted a retrospective chart review of AS patients testing positive for COVID-19 upon screening at Fox Chase Cancer Center between January 2020 and September 2020. Relationships between positive tests and demographics, clinical characteristics, and treatment delays were investigated using conditional logistic regression or Mantel-Haenszel tests.

RESULTS

Among 4143 AS patients who underwent COVID-19 testing, 25 (0.6%) were COVID-19 positive (cases) and these were matched to 50 controls. The median age was lower in the cases compared to that of the controls (64 vs 70 years old, p = 0.04). Of the cases, 10 patients (40%) never underwent their planned oncologic intervention [6/10 (60%) did not require the planned intervention once deemed okay to proceed]. Of the controls, only 1 patient (2%) did not undergo the planned intervention. Of these 15 COVID-19 positive patients who underwent the planned intervention, 11 (73.3%) had a delay related to COVID-19, with a mean delay duration of 18 days (range: 0-49, SD: 16.72).

CONCLUSION

Cancer patients had lower incidence of AS COVID-19 than general population. Delays that occur due to AS COVID screening are not very long and serve as a tool to limit spread of virus. Further studies will be important in addressing delays in cancer care and concerns of patient safety as the pandemic continues.

Screening Hesitancy of a Universal Voluntary-based Rapid Antigen Test for coronavirus disease 2019 (COVID-19) During Omicron Wave in Hong Kong

BACKGROUND

The Hong Kong government distributed rapid antigen test (RAT) kits to households across the city and called for a universal voluntary testing exercise for three consecutive days during the Omicron wave to identify infected persons early for quarantine and disrupt transmission chains in the community. We conducted a survey to evaluate the participation rates and explore the determinants of voluntary RAT adoption and hesitancy.

METHODS

This cross-sectional survey was conducted through computer-assisted telephone interviews from 19 May to 16 June 2022 using an overlapping dual-frame telephone number sampling design. Information on willingness to adopt voluntary RAT, four themes of personal qualities, attitudes toward the government's health policies, incentives to motivate RAT adoption, and personal sociodemographic factors were collected. Logistic regression analysis was used to examine the factors associated with RAT adoption.

RESULTS

Of the 1010 participants, 490 successfully responded to the fixed-line and 520 to the mobile phone survey, with response rates of 1.42% and 1.63% and screen hesitancy rates of 36.1% and 39.3%, respectively. Participants of adoption RAT were those aged 30-49 years, with high perceived COVID-19 infection severity, ≥ 3 doses of COVID-19 vaccination, and more agreement with the health policies on material resources and quarantine orders. Individuals who were less risk seeking and more altruistic reported a higher adoption of voluntary RAT.

CONCLUSIONS

Understanding the willingness to participate in a voluntary universal testing programme might shed light on effective ways to minimise screening hesitancy in future public health strategies and campaigns.

The Capacity of Artificial Intelligence in COVID-19 Response: A Review in Context of COVID-19 Screening and Diagnosis

Artificial intelligence (AI) has been shown to solve several issues affecting COVID-19 diagnosis. This systematic review research explores the impact of AI in early COVID-19 screening, detection, and diagnosis. A comprehensive survey of AI in the COVID-19 literature, mainly in the context of screening and diagnosis, was observed by applying the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. Data sources for the years 2020, 2021, and 2022 were retrieved from google scholar, web of science, Scopus, and PubMed, with target keywords relating to AI in COVID-19 screening and diagnosis. After a comprehensive review of these studies, the results found that AI contributed immensely to improving COVID-19 screening and diagnosis. Some proposed AI models were shown to have comparable (sometimes even better) clinical decision outcomes, compared to experienced radiologists in the screening/diagnosing of COVID-19. Additionally, AI has the capacity to reduce physician work burdens and fatigue and reduce the problems of several false positives, associated with the RT-PCR test (with lower sensitivity of 60-70%) and medical imaging analysis. Even though AI was found to be timesaving and cost-effective, with less clinical errors, it works optimally under the supervision of a physician or other specialists.

No evidence for added value of introducing mandatory COVID-19 testing for international travellers entering Norway with a valid EU digital COVID certificate

BACKGROUND

As a response to the emergence of the new Omicron SARS-CoV-2 variant, on December 3, 2021, mandatory testing after entry to Norway was extended to include international travellers with a valid COVID-19 certificate. We aim to validate if mandatory testing upon arrival increased the proportion of travellers confirmed with a positive COVID-19 test after entry.

METHODS

We used individual level data on registered travellers linked with data on COVID-19 testing and confirmed COVID-19 cases. The proportions of confirmed cases among international travellers before and after the requirement were introduced was analysed with an interrupted times series design.

RESULTS

The proportion of travellers with an EU COVID-19 certificate tested at an official test station increased from 3% to 43% after mandatory testing was introduced. However, the proportion of all travellers confirmed with COVID-19 rose only marginally with 0.14 percentage point directly after the intervention (p-value .06). The results are limited by the absence of data on antigen tests taken by the traveller at home and missing data from travellers without a valid Norwegian ID.

CONCLUSIONS

Our findings suggest that the benefit of mandatory testing of all international travellers to Norway was marginal in the period directly after the emergence of the omicron variant. This result must be understood in the context of free of charge testing at official test centres, a government recommendation on a low threshold to test when experiencing symptoms in addition to limited surveillance of the compliance of the test after arrival requirement.

Optical Monitoring of Breathing Patterns and Tissue Oxygenation: A Potential Application in COVID-19 Screening and Monitoring

The worldwide outbreak of the novel Coronavirus (COVID-19) has highlighted the need for a screening and monitoring system for infectious respiratory diseases in the acute and chronic phase. The purpose of this study was to examine the feasibility of using a wearable near-infrared spectroscopy (NIRS) sensor to collect respiratory signals and distinguish between normal and simulated pathological breathing. Twenty-one healthy adults participated in an experiment that examined five separate breathing conditions. Respiratory signals were collected with a continuous-wave NIRS sensor (PortaLite, Artinis Medical Systems) affixed over the sternal manubrium. Following a three-minute baseline, participants began five minutes of imposed difficult breathing using a respiratory trainer. After a five minute recovery period, participants began five minutes of imposed rapid and shallow breathing. The study concluded with five additional minutes of regular breathing. NIRS signals were analyzed using a machine learning model to distinguish between normal and simulated pathological breathing. Three features: breathing interval, breathing depth, and O₂Hb signal amplitude were extracted from the NIRS data and, when used together, resulted in a weighted average accuracy of 0.87. This study demonstrated that a wearable NIRS sensor can monitor respiratory patterns continuously and non-invasively and we identified three respiratory features that can distinguish between normal and simulated pathological breathing.

Effect of waiting time for COVID-19 screening on postoperative outcomes of type A aortic dissection: An institutional study

BACKGROUND

Since November 2020, all patients undergoing emergency surgery at our hospital have been subjected to preoperative reverse transcription polymerase chain reaction (RT-PCR) screening to prevent nosocomial COVID-19 infection, with admission to the operating room requiring a negative result. Herein, we compared the pre- and postoperative outcomes of acute type A aortic dissection surgery before and after implementing the RT-PCR screening for all patients.

METHODS

We compared the postoperative results of 105 patients who underwent acute type A aortic dissection emergency surgery from January 2019 to October 2020 (Group I) and 109 patients who underwent the surgery following RT-PCR screening from November 2020 to March 2022 (Group II).

RESULTS

The average waiting time from arrival at the hospital to admission to the operating room was 36 and 81 min in Groups I and II, respectively. Ruptured cardiac tamponade was observed preoperatively in 26.6% and 21.1% of Groups I and II patients, respectively. The preoperative waiting time due to RT-PCR screening did not contribute to the cardiac tamponade. Surgical complications such as bleeding (reopened chest), respiratory failure, cerebral neuropathy, or mediastinitis did not increase significantly. The number of deaths 30 days after surgery (Group I = 13 and Group II = 3) showed no significant difference between the groups. There were no cases of nosocomial COVID-19 infections.

CONCLUSIONS

Preoperative COVID-19 screening is an important method to prevent nosocomial infections. The associated waiting time did not affect the number of preoperative ruptures or affect postoperative complications or mortality.

Evaluation of a COVID-19 Rapid Antigen Testing Program in a Supervised Community Distance Learning Setting for K-8 Students

BACKGROUND

School-based COVID-19 testing is a potential strategy to limit COVID-19 transmission among youth in congregate settings such as schools, sports programs, and summer camps. The purpose of this study is to evaluate the feasibility and effectiveness of frequent rapid antigen testing at a supervised distance-learning setting for elementary and middle school children while their schools were closed.

METHODS

This evaluation examines participation rates and testing data in addition to qualitative analysis of focus groups from a Los Angeles City-sponsored rapid antigen testing pilot program. In total, 434 children and staff were enrolled in the 13-week pilot program in the spring of 2021.

RESULTS

In this pilot program, 2482 rapid antigen tests were administered, resulting in 3 positive test results, 1 of which was a false positive (confirmed by polymerase chain reaction testing) and 0 outbreaks or community spread.

CONCLUSIONS

Throughout this pilot program, implementing rapid antigen tests allowed for the quick identification and isolation of potentially COVID-19-positive children, improved perceived safety for parents and staff who interact with children, and demonstrated the ability for staff and non-health care professionals in a school-based setting to implement a widespread COVID-19 screening program with minimal training.

Does imbalance in chest X-ray datasets produce biased deep learning approaches for COVID-19 screening?

Background

The health crisis resulting from the global COVID-19 pandemic highlighted more than ever the need for rapid, reliable and safe methods of diagnosis and monitoring of respiratory diseases. To study pulmonary involvement in detail, one of the most common resources is the use of different lung imaging modalities (like chest radiography) to explore the possible affected areas.

Methods

The study of patient characteristics like sex and age in pathologies of this type is crucial for gaining knowledge of the disease and for avoiding biases due to the clear scarcity of data when developing representative systems. In this work, we performed an analysis of these factors in chest X-ray images to identify biases. Specifically, 11 imbalance scenarios were defined with female and male COVID-19 patients present in different proportions for the sex analysis, and 6 scenarios where only one specific age range was used for training for the age factor. In each study, 3 different approaches for automatic COVID-19 screening were used: Normal vs COVID-19, Pneumonia vs COVID-19 and Non-COVID-19 vs COVID-19. The study was validated using two public chest X-ray datasets, allowing a reliable analysis to support the clinical decision-making process.

Results

The results for the sex-related analysis indicate this factor slightly affects the system in the Normal VS COVID-19 and Pneumonia VS COVID-19 approaches, although the identified differences are not relevant enough to worsen considerably the system. Regarding the age-related analysis, this factor was observed to be influencing the system in a more consistent way than the sex factor, as it was present in all considered scenarios. However, this worsening does not represent a major factor, as it is not of great magnitude.

Conclusions

Multiple studies have been conducted in other fields in order to determine if certain patient characteristics such as sex or age influenced these deep learning systems. However, to the best of our knowledge, this study has not been done for COVID-19 despite the urgency and lack of COVID-19 chest x-ray images. The presented results evidenced that the proposed methodology and tested approaches allow a robust and reliable analysis to support the clinical decision-making process in this pandemic scenario.

Supplementary Information

The online version contains supplementary material available at (10.1186/s12874-022-01578-w).

Before the COVID-Vaccine-Vulnerable Elderly in Homecare

BACKGROUND

At the beginning of 2020, the COVID-19 virus was spreading all over the world. Frail elderly were at risk for illness and death. Isolation seemed to be the best solution. The aim of this paper was to describe how the lockdown affected elderly homecare patients.

METHODS

We used an international self-reported screening instrument built on well-documented risk factors adapted to COVID-19. We considered ethical, legal, and practical concerns. The research included telephone interviews with 30 homecare patients.

RESULTS

Seventy percent lived alone. Seventy-three percent of the sample suffered from major comorbidity. Cardiovascular disorder was the most frequent diagnosis. Nineteen (63.3%) needed help for personal care. Several of the participants were lonely and depressed. The homecare teams struggled to give proper care. The health authorities encouraged the population to reduce their outside physical activities to a minimum. The restrictions due to COVID-19 affected daily life and several respondents expressed uncertainties about the future.

CONCLUSIONS

It is important to describe the patients' experiences in a homecare setting at the initiation of lockdowns due to COVID-19. The isolation protected them from the virus, but they struggled with loneliness and the lack of physical contact with their loved ones. In the future, we need to understand and address the unmet needs of elderly homecare patients in lockdown.

Lean Principles to Improve Quality in High-Throughput COVID-19 Testing Using SwabSeq: A Barcoded Sequencing-Based Testing Platform

OBJECTIVE

To describe and quantify the effect of quality control (QC) metrics to increase testing efficiency in a high-complexity, Clinical Laboratory Improvement Amendments-certified laboratory that uses amplicon-based, next generation sequencing for the clinical detection of SARS-CoV-2. To enable rapid scalability to several thousands of specimens per day without fully automated platforms, we developed internal QC methods to ensure high-accuracy testing.

METHODS

We implemented procedures to increase efficiency by applying the Lean Six Sigma model into our sequencing-based COVID-19 detection.

RESULTS

The application of the Lean Six Sigma model increased laboratory efficiency by reducing errors, allowing for a higher testing volume to be met with minimal staffing. Furthermore, these improvements resulted in an improved turnaround time.

CONCLUSION

Lean Six Sigma model execution has increased laboratory efficiency by decreasing critical testing errors and has prepared the laboratory for future scaling up to 50,000 tests per day.

Variations by race/ethnicity and time in Covid-19 testing among Veterans Health Administration users with COVID-19 symptoms or exposure

Racial/ethnic disparities in coronavirus disease 2019 (COVID-19) hospitalization and mortality have emerged in the United States, but less is known about whether similar differences exist in testing, and how this changed as COVID-19 knowledge and policies evolved. We examined racial/ethnic variations in COVID-19 testing over time among veterans who sought care for COVID-19 symptoms or exposure. In the national population of all Veterans who sought Veterans Health Administration (VHA) care for COVID-19 symptoms or exposure (n = 913,806), we conducted multivariate logistic regressions to explore race/ethnicity-by-time period differences in testing from 3/1/2020-11/25/2020, and calculated predicted probabilities by race/ethnicity and time period. Early in the pandemic (3/1/2020-4/6/2020) when testing was limited and there was less awareness of racial/ethnic disparities, non-Hispanic Black, Hispanic, and other non-White racial/ethnic minority Veterans who sought care from VHA for COVID-19 symptoms or exposure were more likely than non-Hispanic White Veterans to receive a COVID-19 test (p < 0.05). In subsequent time periods (4/7/2020-11/25/2020), testing was similar among all racial/ethnic groups. Among Veterans with COVID-19 symptoms or exposure, non-Hispanic Black and Hispanic patients were just as likely, and in some cases, more likely, to receive a COVID-19 test versus non-Hispanic White patients. The United States faced testing shortages at the start of the third wave of the pandemic; additional shortages are likely to emerge as the pandemic continues to peak and ebb. It is important to ensure that racial/ethnic minorities and others at greater risk for infection continue to have access to COVID-19 testing with each of these peaks.

A novel combined dynamic ensemble selection model for imbalanced data to detect COVID-19 from complete blood count

BACKGROUND

As blood testing is radiation-free, low-cost and simple to operate, some researchers use machine learning to detect COVID-19 from blood test data. However, few studies take into consideration the imbalanced data distribution, which can impair the performance of a classifier.

METHOD

A novel combined dynamic ensemble selection (DES) method is proposed for imbalanced data to detect COVID-19 from complete blood count. This method combines data preprocessing and improved DES. Firstly, we use the hybrid synthetic minority over-sampling technique and edited nearest neighbor (SMOTE-ENN) to balance data and remove noise. Secondly, in order to improve the performance of DES, a novel hybrid multiple clustering and bagging classifier generation (HMCBCG) method is proposed to reinforce the diversity and local regional competence of candidate classifiers.

RESULTS

The experimental results based on three popular DES methods show that the performance of HMCBCG is better than only use bagging. HMCBCG+KNE obtains the best performance for COVID-19 screening with 99.81% accuracy, 99.86% F1, 99.78% G-mean and 99.81% AUC.

CONCLUSION

Compared to other advanced methods, our combined DES model can improve accuracy, G-mean, F1 and AUC of COVID-19 screening.

The Role of Diagnostic Management in COVID-19 Screening of Asymptomatic Patients Admitted for Elective Surgery

BACKGROUND

Due to the high risk of COVID-19 transmission by asymptomatic patients, the aim of this study was to evaluate chest computed tomography (CT) and blood differential test as an additional COVID-19 screening tool for patients undergoing elective or urgent surgery.

PATIENTS AND METHODS

The preoperative assessment of 118 patients hospitalized from June to July 2020 included real-time reverse transcriptase polymerase chain reaction RNA test before elective surgery or rapid antigen test in emergency patients. The diagnostics were supplemented by chest CT and a complete blood count with a blood smear in all patients.

RESULTS

None of the hospitalized patients had molecular, serological or radiographic symptoms of COVID-19 infection. The chest CT revealed non-COVID-19 pathologies in a total of 48 patients. Leukocytosis and lymphopenia were typical of emergency patients.

CONCLUSION

Routine chest CT scans have no benefit in screening for potential COVID-19 changes in asymptomatic patients. Blood differential tests are readily available, which makes them more helpful in COVID-19 screening.

ET-NET: an ensemble of transfer learning models for prediction of COVID-19 infection through chest CT-scan images

The COVID-19 virus has caused a worldwide pandemic, affecting numerous individuals and accounting for more than a million deaths. The countries of the world had to declare complete lockdown when the coronavirus led to community spread. Although the real-time Polymerase Chain Reaction (RT-PCR) test is the gold-standard test for COVID-19 screening, it is not satisfactorily accurate and sensitive. On the other hand, Computer Tomography (CT) scan images are much more sensitive and can be suitable for COVID-19 detection. To this end, in this paper, we develop a fully automated method for fast COVID-19 screening by using chest CT-scan images employing Deep Learning techniques. For this supervised image classification problem, a bootstrap aggregating or Bagging ensemble of three transfer learning models, namely, Inception v3, ResNet34 and DenseNet201, has been used to boost the performance of the individual models. The proposed framework, called ET-NET, has been evaluated on a publicly available dataset, achieving 97.81 ± 0.53 % accuracy, 97.77 ± 0.58 % precision, 97.81 ± 0.52 % sensitivity and 97.77 ± 0.57 % specificity on 5-fold cross-validation outperforming the state-of-the-art method on the same dataset by 1.56%. The relevant codes for the proposed approach are accessible in: https://github.com/Rohit-Kundu/ET-NET_Covid-Detection.

Residual-Shuffle Network with Spatial Pyramid Pooling Module for COVID-19 Screening

Since the start of the COVID-19 pandemic at the end of 2019, more than 170 million patients have been infected with the virus that has resulted in more than 3.8 million deaths all over the world. This disease is easily spreadable from one person to another even with minimal contact, even more for the latest mutations that are more deadly than its predecessor. Hence, COVID-19 needs to be diagnosed as early as possible to minimize the risk of spreading among the community. However, the laboratory results on the approved diagnosis method by the World Health Organization, the reverse transcription-polymerase chain reaction test, takes around a day to be processed, where a longer period is observed in the developing countries. Therefore, a fast screening method that is based on existing facilities should be developed to complement this diagnosis test, so that a suspected patient can be isolated in a quarantine center. In line with this motivation, deep learning techniques were explored to provide an automated COVID-19 screening system based on X-ray imaging. This imaging modality is chosen because of its low-cost procedures that are widely available even in many small clinics. A new convolutional neural network (CNN) model is proposed instead of utilizing pre-trained networks of the existing models. The proposed network, Residual-Shuffle-Net, comprises four stacks of the residual-shuffle unit followed by a spatial pyramid pooling (SPP) unit. The architecture of the residual-shuffle unit follows an hourglass design with reduced convolution filter size in the middle layer, where a shuffle operation is performed right after the split branches have been concatenated back. Shuffle operation forces the network to learn multiple sets of features relationship across various channels instead of a set of global features. The SPP unit, which is placed at the end of the network, allows the model to learn multi-scale features that are crucial to distinguish between the COVID-19 and other types of pneumonia cases. The proposed network is benchmarked with 12 other state-of-the-art CNN models that have been designed and tuned specially for COVID-19 detection. The experimental results show that the Residual-Shuffle-Net produced the best performance in terms of accuracy and specificity metrics with 0.97390 and 0.98695, respectively. The model is also considered as a lightweight model with slightly more than 2 million parameters, which makes it suitable for mobile-based applications. For future work, an attention mechanism can be integrated to target certain regions of interest in the X-ray images that are deemed to be more informative for COVID-19 diagnosis.

Comparative analysis of chemical breath-prints through olfactory technology for the discrimination between SARS-CoV-2 infected patients and controls

BACKGROUND

We identified a global chemical pattern of volatile organic compounds in exhaled breath capable of discriminating between COVID-19 patients and controls (without infection) using an electronic nose.

METHODS

The study focused on 42 SARS-CoV-2 RT-qPCR positive subjects as well as 42 negative subjects. Principal component analysis indicated a separation of the study groups and provides a cumulative percentage of explanation of the variation of 98.3%.

RESULTS

The canonical analysis of principal coordinates model shows a separation by the first canonical axis CAP1 (r² = 0.939 and 95.23% of correct classification rate), the cut-off point of 0.0089; 100% sensitivity (CI 95%:91.5-100%) and 97.6% specificity (CI 95%:87.4-99.9%). The predictive model usefulness was tested on 30 open population subjects without prior knowledge of SARS-CoV-2 RT-qPCR status. Of these 3 subjects exhibited COVID-19 suggestive breath profiles, all asymptomatic at the time, two of which were later shown to be SARS-CoV-2 RT-qPCR positive. An additional subject had a borderline breath profile and SARS-CoV-2 RT-qPCR positive. The remaining 27 subjects exhibited healthy breath profiles as well as SARS-CoV-2 RT-qPCR test results.

CONCLUSIONS

In all, the use of olfactory technologies in communities with high transmission rates as well as in resource-limited settings where targeted sampling is not viable represents a practical COVID-19 screening approach capable of promptly identifying COVID-19 suspect patients and providing useful epidemiological information to guide community health strategies in the context of COVID-19.

30-Day postoperative COVID-19 outcomes in 398 patients from regional hospitals utilising a designated COVID-19 minimal surgical site pathway

INTRODUCTION

Postoperative pulmonary complications and mortality rates during the COVID-19 pandemic have been higher than expected, leading to mass cancellation of elective operating in the UK. To minimise this, the Guy's and St Thomas' Hospital NHS Foundation Trust elective surgery hub and the executive team at London Bridge Hospital (LBH) created an elective operating framework at LBH, a COVID-19 minimal site, in which patients self-isolated for two weeks and proceeded with surgery only following a negative preoperative SARS-CoV-2 polymerase chain reaction swab. The aim was to determine the rates of rates of postoperative COVID-19 infection.

METHODS

The collaboration involved three large hospital trusts, covering the geographic area of south-east London. All patients were referred to LBH for elective surgery. Patients were followed up by telephone interview at four weeks postoperatively.

RESULTS

Three hundred and ninety-eight patients from 13 surgical specialties were included in the analysis. The median age was 60 (IQR 29-71) years. Sixty-three per cent (252/398) were female. In total, 78.4% of patients had an American Society of Anesthesiologists grade of 1-2 and the average BMI was 27.2 (IQR 23.7-31.8) kg/m2. Some 83.6% (336/402) were 'major' operations. The rate of COVID-19-related death in our cohort was 0.25% (1/398). Overall, there was a 1.26% (5/398) 30-day postoperative all-cause mortality rate. Seven patients (1.76%) reported COVID-19 symptoms, but none attended the emergency department or were readmitted to hospital as a result.

CONCLUSION

The risk of contracting COVID-19 in our elective operating framework was very low. We demonstrate that high-volume major surgery is safe, even at the peak of the pandemic, if patients are screened appropriately preoperatively.

False Negative Mitigation in Group Testing for COVID-19 Screening

After lifting the COVID-19 lockdown restrictions and opening businesses, screening is essential to prevent the spread of the virus. Group testing could be a promising candidate for screening to save time and resources. However, due to the high false-negative rate (FNR) of the RT-PCR diagnostic test, we should be cautious about using group testing because a group's false-negative result identifies all the individuals in a group as uninfected. Repeating the test is the best solution to reduce the FNR, and repeats should be integrated with the group-testing method to increase the sensitivity of the test. The simplest way is to replicate the test twice for each group (the 2Rgt method). In this paper, we present a new method for group testing (the groupMix method), which integrates two repeats in the test. Then we introduce the 2-stage sequential version of both the groupMix and the 2Rgt methods. We compare these methods analytically regarding the sensitivity and the average number of tests. The tradeoff between the sensitivity and the average number of tests should be considered when choosing the best method for the screening strategy. We applied the groupMix method to screening 263 people and identified 2 infected individuals by performing 98 tests. This method achieved a 63% saving in the number of tests compared to individual testing. Our experimental results show that in COVID-19 screening, the viral load can be low, and the group size should not be more than 6; otherwise, the FNR increases significantly. A web interface of the groupMix method is publicly available for laboratories to implement this method.

Federated learning for COVID-19 screening from Chest X-ray images

Today, the whole world is facing a great medical disaster that affects the health and lives of the people: the COVID-19 disease, colloquially known as the Corona virus. Deep learning is an effective means to assist radiologists to analyze the vast amount of chest X-ray images, which can potentially have a substantial role in streamlining and accelerating the diagnosis of COVID-19. Such techniques involve large datasets for training and all such data must be centralized in order to be processed. Due to medical data privacy regulations, it is often not possible to collect and share patient data in a centralized data server. In this work, we present a collaborative federated learning framework allowing multiple medical institutions screening COVID-19 from Chest X-ray images using deep learning without sharing patient data. We investigate several key properties and specificities of federated learning setting including the not independent and identically distributed (non-IID) and unbalanced data distributions that naturally arise. We experimentally demonstrate that the proposed federated learning framework provides competitive results to that of models trained by sharing data, considering two different model architectures. These findings would encourage medical institutions to adopt collaborative process and reap benefits of the rich private data in order to rapidly build a powerful model for COVID-19 screening.

A Case Series: Successfully Preventing COVID-19 Outbreak in a Residential Community Setting at a Drug and Alcohol Addiction Treatment Center

Coronavirus disease 2019 (COVID-19) has reduced the capacity of many addiction treatment centers, limiting access to safe, continual treatment for people with substance use disorders (SUD) in the setting of a pandemic. Here, we describe the COVID-19 screening process of a residential addiction treatment center in rural Connecticut that has had no outbreaks, closures, or reductions in capacity since the pandemic began. Out of 420 patients screened for COVID-19 from 1 February to 1 July, five patients tested positive for COVID-19: four prior to entering its residential community setting, and one after entering the residential community, resulting in no COVID-19 spread to other patients. Patient 1 presented from home and tested positive during screening prior to entry into the community. The primary care provider for patient 2 notified staff of a recent pos-itive COVID-19 test prior to the patient's arrival on-site. Patient 3 had a COVID-19 infection in the weeks prior to arrival and tested positive during initial screening. Patient 4 tested positive af-ter coming from another addiction treatment facility that was shut down due to a COVID-19 outbreak. Patient 5 tested negative for COVID-19 during initial screening, entered the residential community, and later tested positive. It is imperative that in-person support for SUD continues during the pandemic. This case report highlights the importance of implementing a variety of tools in an effective screening process, including polymerase chain reaction screening and daily symptomology and temperature screening, which may help prevent further closures or reductions in capacity of addiction treatment centers during the COVID-19 pandemic or future outbreaks.

Olfactory and Gustatory Dysfunction as an Early Identifier of COVID-19 in Adults and Children: An International Multicenter Study

OBJECTIVE

To evaluate the prevalence and characteristics of olfactory or gustatory dysfunction in coronavirus disease 2019 (COVID-19) patients.

STUDY DESIGN

Multicenter case series.

SETTING

Five tertiary care hospitals (3 in China, 1 in France, 1 in Germany).

SUBJECTS AND METHODS

In total, 394 polymerase chain reaction (PCR)-confirmed COVID-19-positive patients were screened, and those with olfactory or gustatory dysfunction were included. Data including demographics, COVID-19 severity, patient outcome, and the incidence and degree of olfactory and/or gustatory dysfunction were collected and analyzed. The Questionnaire of Olfactory Disorders (QOD) and visual analog scale (VAS) were used to quantify olfactory and gustatory dysfunction, respectively. All subjects at 1 hospital (Shanghai) without subjective olfactory complaints underwent objective testing.

RESULTS

Of 394 screened subjects, 161 (41%) reported olfactory and/or gustatory dysfunction and were included. Incidence of olfactory and/or gustatory disorders in Chinese (n = 239), German (n = 39), and French (n = 116) cohorts was 32%, 69%, and 49%, respectively. The median age of included subjects was 39 years, 92 of 161 (57%) were male, and 10 of 161 (6%) were children. Of included subjects, 10% had only olfactory or gustatory symptoms, and 19% had olfactory and/or gustatory complaints prior to any other COVID-19 symptom. Of subjects with objective olfactory testing, 10 of 90 demonstrated abnormal chemosensory function despite reporting normal subjective olfaction. Forty-three percent (44/102) of subjects with follow-up showed symptomatic improvement in olfaction or gustation.

CONCLUSIONS

Olfactory and/or gustatory disorders may represent early or isolated symptoms of severe acute respiratory syndrome coronavirus 2 infection. They may serve as a useful additional screening criterion, particularly for the identification of patients in the early stages of infection.

A clinical pathway for pre-operative screening of COVID-19 and its influence on clinical outcome in patients with traumatic fractures

PURPOSE

Coronavirus disease 2019 (COVID-19) has become a worldwide pandemic. The toughest issue traumatic orthopaedic surgeons are faced with is how to maintain a balance between adequate COVID-19 screening and timely surgery. In this study, we described our experience with pre-operative COVID-19 screening in patients with traumatic fractures. Furthermore, we analysed the clinical results of fracture patients undergoing confined or emergency surgery during the COVID-19 outbreak.

METHODS

This was a case series study. Patients with traumatic fractures who were admitted to our hospital for surgery were enrolled in this study during the COVID-19 outbreak from March to April 2020. All patients were enrolled and managed using the standardized clinical pathway we designed for preoperative COVID-19 screening. Clinical, laboratory and outcome data were analysed.

RESULTS

The average surgery waiting time from injury to surgery was 8.7 ± 3.4 days. The average waiting time from admission to surgery was 5.3 ± 2.8 days. These average waiting times were increased by 4.1 days and 2.0 days, respectively, compared with 2019 data. Cardiovascular complications, venous thromboembolism and pneumonia occurred in one, two and one patient, respectively. Three and two patients developed pre-operative and postoperative fevers, respectively.

CONCLUSIONS

We introduced a novel clinical pathway for pre-operatively screening of COVID-19 in traumatic orthopaedic patients. The delay in surgery caused by COVID-19 screening was minimized to a point at which reasonable and acceptable clinical outcomes were achieved. Doctors should pay more attention to perioperative complications, such as cardiovascular complications, venous thromboembolism, pneumonia and fever.