Application of machine learning approaches to predict the impact of ambient air pollution on outpatient visits for acute respiratory infections

With a remarkable increase in industrialization among fast-developing countries, air pollution is rising at an alarming rate and has become a public health concern. The study aims to examine the effect of air pollution on patient's hospital visits for respiratory diseases, particularly Acute Respiratory Infections (ARI). Outpatient hospital visits, air pollution and meteorological parameters were collected from March 2018 to October 2021. Eight machine learning algorithms (Random Forest model, K-Nearest Neighbors regression model, Linear regression model, LASSO regression model, Decision Tree Regressor, Support Vector Regression, X.G. Boost and Deep Neural Network with 5-layers) were applied for the analysis of daily air pollutants and outpatient visits for ARI. The evaluation was done by using 5-cross-fold confirmations. The data was randomly divided into test and training data sets at a scale of 1:2, respectively. Results show that among the studied eight machine learning models, the Random Forest model has given the best performance with R2 = 0.606, 0.608 without lag and 1-day lag respectively on ARI patients and R2 = 0.872, 0.871 without lag and 1-day lag respectively on total patients. All eight models did not perform well with the lag effect on the ARI patient dataset but performed better on the total patient dataset. Thus, the study did not find any significant association between ARI patients and ambient air pollution due to the intermittent availability of data during the COVID-19 period. This study gives insight into developing machine learning programs for risk prediction that can be used to predict analytics for several other diseases apart from ARI, such as heart disease and other respiratory diseases. © 2022 Elsevier B.V.

Fake news believability: The effects of political beliefs and espoused cultural values

Fake news has led to a polarized society as evidenced by diametrically opposed perceptions of and reactions to global events such as the Coronavirus Disease 2019 (COVID-19) pandemic and presidential campaigns. Popular press has linked individuals' political beliefs and cultural values to the extent to which they believe in false content shared on social networking sites (SNS). However, sweeping generalizations run the risk of helping exacerbate divisiveness in already polarized societies. This study examines the effects of individuals' political beliefs and espoused cultural values on fake news believability using a repeated-measures design (that exposes individuals to a variety of fake news scenarios). Results from online questionnaire-based survey data collected from participants in the US and India help confirm that conservative individuals tend to exhibit increasing fake news believability and show that collectivists tend to do the same. This study advances knowledge on characteristics that make individuals more susceptible to lending credence to fake news. In addition, this study explores the influence exerted by control variables (i.e., age, sex, and Internet usage). Findings are used to provide implications for theory as well as actionable insights. © 2022 The Author(s)

Novel deep transfer learning model for COVID-19 patient detection using X-ray chest images.

Around the world, more than 250 countries are affected by the COVID-19 pandemic, which is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This outbreak can be controlled only by the diagnosis of the COVID-19 infection in early stages. It is found that the radiographic images are ideal for the fastest diagnosis of COVID-19 infection. This paper proposes an ensemble model which detects the COVID-19 infection in the early stage with the use of chest X-ray images. The transfer learning enables to reuse the pretrained models. The ensemble learning integrates various transfer learning models, i.e., EfficientNet, GoogLeNet, and XceptionNet, to design the proposed model. These models can categorize patients as COVID-19 (+), pneumonia (+), tuberculosis (+), or healthy. The proposed model enhances the classifier's generalization ability for both binary and multiclass COVID-19 datasets. Two popular datasets are used to evaluate the performance of the proposed ensemble model. The comparative analysis validates that the proposed model outperforms the state-of-art models in terms of various performance metrics.

Designerly Tele-Experiences: A New Approach to Remote Yet Still Situated Co-Design

The COVID-19 pandemic disrupted processes interaction designers took for granted, challenging some of our most commonplace design practices. Participatory and situated approaches have been impacted the most: where we engaged stakeholders in-person and in-context, during this time we must co-design remotely and in virtual environments. Such a dramatic change calls for new co-design methods. In this article, we present a novel remote strategy for involving stakeholders to co-design interactive technology: Designerly Tele-Experiences (DTE). Our methodological proposal enables participants to experience early design concepts in-the-wild as a provocation to contribute new ideas that resonate with their experiential preferences. Here we describe the rationale for DTE, unpack how it builds on and extends existing methods, and provide actionable guidelines from our experience of using it in our work. Our contribution will empower interaction designers to embrace participatory and situated approaches even when engaging stakeholders in person is not possible or desirable.

Asymptomatic infection and transmission of COVID-19 among clusters: systematic review and meta-analysis.

OBJECTIVES: Countries throughout the world are experiencing COVID-19 viral load in their populations, leading to potential transmission and infectivity of asymptomatic COVID-19 cases. The current systematic review and meta-analysis aims to investigate the role of asymptomatic infection and transmission reported in family clusters, adults, children and health care workers, globally. STUDY DESIGN: Systematic review and meta-analysis. METHODS: An online literature search of PubMed, Google Scholar, medRixv and BioRixv was performed using standard Boolean operators and included studies published up to 17 August 2021. For the systematic review, case reports, short communications and retrospective studies were included to ensure sufficient asymptomatic COVID-19 transmission data were reported. For the quantitative synthesis (meta-analysis), participant data from a collection of cohort studies focusing on groups of familial clusters, adults, children and health care workers were included. Inconsistency among studies was assessed using I2 statistics. The data synthesis was computed using the STATA 16.0 software. RESULTS: This study showed asymptomatic transmission among familial clusters, adults, children and health care workers of 15.72%, 29.48%, 24.09% and 0%, respectively. Overall, asymptomatic transmission was 24.51% (95% confidence interval [CI]: 14.38, 36.02) among all studied population groups, with a heterogeneity of I2 = 95.30% (P < 0.001). No heterogeneity was seen in the population subgroups of children and health care workers. The risk of bias in all included studies was assessed using the Newcastle Ottawa Scale. CONCLUSIONS: For minimising the spread of COVID-19 within the community, this study found that following the screening of asymptomatic cases and their close contacts for chest CT scan (for symptomatic patients), even after negative nucleic acid testing, it is essential to perform a rigorous epidemiological history, early isolation, social distancing and an increased quarantine period (a minimum of 14-28 days). This systematic review and meta-analysis supports the notion of asymptomatic COVID-19 infection and person-to-person transmission and suggests that this is dependent on the varying viral incubation period among individuals. Children, especially those of school age (i.e. <18 years), need to be monitored carefully and follow mitigation strategies (e.g. social distancing, hand hygiene, wearing face masks) to prevent asymptomatic community transmission of COVID-19.

Revised recommendations from the CSO-HNS taskforce on performance of tracheotomy during the COVID-19 pandemic - what a difference a year makes.

BACKGROUND: During the early part of the COVID-19 pandemic, the Canadian Society of Otolaryngology - Head & Neck Surgery (CSO-HNS) task force published recommendations on performance of tracheotomy. Since then, our understanding of the virus has evolved with ongoing intensive research efforts. New literature has helped us better understand various aspects including patient outcomes and health care worker (HCW) risks associated with tracheotomy during the COVID-19 pandemic. Accordingly, the task force has re-evaluated and revised some of the previous recommendations. MAIN BODY: Based on recent evidence, a negative reverse transcription polymerase chain reaction (RT-PCR) COVID-19 swab status is no longer the main deciding factor in the timing of tracheotomy. Instead, tracheotomy may be considered as soon as COVID-19 swab positive patients are greater than 20 days beyond initial symptoms and 2 weeks of mechanical ventilation. Furthermore, both open and percutaneous surgical techniques may be considered with both techniques showing similar safety and outcome profiles. Additional recommendations with discussion of current evidence are presented. CONCLUSION: These revised recommendations apply new evidence in optimizing patient and health care system outcomes as well as minimizing risks of COVID-19 transmission during aerosol-generating tracheotomy procedures. As previously noted, additional evidence may lead to further evolution of these and other similar recommendations.

Systematic review and meta-analysis of efficacy and safety of hydroxychloroquine and chloroquine in the treatment of COVID-19.

Repurposed drugs like hydroxycloroquine (HCQ) and chloroquine (CQ) are being tested for potential therapeutic role in COVID-19. We aimed to evaluate efficacy and safety of HCQ and CQ in COVID-19. Using PubMed, EMBASE, medRxiv, Google Scholar, clinicaltrials.gov, electronic search was carried out to identify relevant articles till June 2020 with re-evaluation in last week of November 2020. Observational and interventional clinical studies comparing efficacy of CQ or HCQ to standard management or other drug/s for SARS-CoV-2 infection patients were included. Cochrane review manager version 5.3 was used for synthesis of meta-analysis results. For randomized controlled trials, risk of bias was assessed using Cochrane Collaboration risk of bias assessment tool, version 2.0 (ROB-2). ROBINS-I was used for quality assessment of observational studies. Overall evidence quality generated by review was graded as per GRADE Recommendation. A total of 903 studies were screened. Nineteen studies were included in synthesis of meta-analysis with total of 4,693, 1,626, and 6,491 patients in HCQ/CQ, HCQ/CQ + AZ and control groups, respectively. HCQ/CQ treatment was associated with significantly increased rates of virological cure (OR = 2.08, 95%CI = 1.36-3.17; P = 0.0007) and radiological cure (OR = 3.89, 95%CI = 1.35 - 11.23; P = 0.01) compared to control. HCQ/CQ had no difference in unadjusted mortality rate (unadjusted OR = 0.98 95% CI = 0.70-1.37, P = 0.89, random effect model) and adjusted hazard ratio for mortality (adjusted HR = 1.05, 95%CI = 0.86--1.29; P = 0.64). However, a significant increase in odds of disease progression (OR = 1.77, 95%CI = 1.46-2.13; P < 0.00001) and QT prolongation (OR = 11.15, 95%CI = 3.95-31.44; P < 0.00001) was noted. The results with HCQ/CQ and azithromycin combination were similar to HCQ/CQ mono-therapy. In the light of contemporary evidence on effectiveness of HCQ/CQ, judicious and monitored use of HCQ/CQ for treatment of COVID-19 patients is recommended in low to middle income countries with emphasis on no mortality benefit. Registration number of Systematic review. Register in PROSPERO database: cRD42020187710.

Potential of graphene-based materials to combat COVID-19: properties, perspectives, and prospects.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a new virus in the coronavirus family that causes coronavirus disease (COVID-19), emerges as a big threat to the human race. To date, there is no medicine and vaccine available for COVID-19 treatment. While the development of medicines and vaccines are essentially and urgently required, what is also extremely important is the repurposing of smart materials to design effective systems for combating COVID-19. Graphene and graphene-related materials (GRMs) exhibit extraordinary physicochemical, electrical, optical, antiviral, antimicrobial, and other fascinating properties that warrant them as potential candidates for designing and development of high-performance components and devices required for COVID-19 pandemic and other futuristic calamities. In this article, we discuss the potential of graphene and GRMs for healthcare applications and how they may contribute to fighting against COVID-19.

Geographical variation in case fatality rate and doubling time during the COVID-19 pandemic.

Case fatality rate (CFR) and doubling time are important characteristics of any epidemic. For coronavirus disease 2019 (COVID-19), wide variations in the CFR and doubling time have been noted among various countries. Early in the epidemic, CFR calculations involving all patients as denominator do not account for the hospitalised patients who are ill and will die in the future. Hence, we calculated cumulative CFR (cCFR) using only patients whose final clinical outcomes were known at a certain time point. We also estimated the daily average doubling time. Calculating CFR using this method leads to temporal stability in the fatality rates, the cCFR stabilises at different values for different countries. The possible reasons for this are an improved outcome rate by the end of the epidemic and a wider testing strategy. The United States, France, Turkey and China had high cCFR at the start due to low outcome rate. By 22 April, Germany, China and South Korea had a low cCFR. China and South Korea controlled the epidemic and achieved high doubling times. The doubling time in Russia did not cross 10 days during the study period.

Prolonged persistence of SARS-CoV-2 in the upper respiratory tract of asymptomatic infected individuals.

BACKGROUND: Duration of persistence of SARS-CoV-2 in the upper respiratory tract of infected individuals has important clinical and epidemiological implications. AIM: We aimed to establish the duration and risk factors for persistence of SARS-CoV-2 in the upper respiratory tract of asymptomatic infected individuals. METHODS: Data of repeat rRT-PCR (real-time reverse transcription-polymerase chain reaction) test done for SARS-CoV-2 infected individuals at our institute at Jodhpur, India were analysed from 19 March to 21 May 2020. Duration of virus persistence was estimated with parametric regression models based on weibull, log-normal, log-logistic, gamma and generalized gamma distributions. Factors associated with prolonged viral persistence were analysed with the best-fitting model. RESULTS: Fifty-one SARS-CoV-2 infected individuals with repeat rRT-PCR test were identified with 44 asymptomatics. The asymptomatic individuals had median virus persistence duration of 8.87 days (95% CI: 7.65-10.27) and 95 percentile duration of 20.70 days (95% CI: 16.08-28.20). The overall median virus persistence including both symptomatic and asymptomatic individuals was found to be 9.18 days (95% CI: 8.04-10.48). Around one-fourth asymptomatics (10/44) demonstrated SARS-CoV-2 persistence beyond 2 weeks. Age <60 years and local transmission were found to be significantly associated with longer virus persistence among asymptomatic individuals on univariate regression but not in multivariate analysis. CONCLUSION: Recommended home isolation duration for SARS-CoV-2 infected individuals in India should be extended from 17 days to at least 3 weeks. Prolonged persistence of SARS-CoV-2 in a considerable proportion of asymptomatic individuals merits attention with regard to ensuring universal infection prevention precautions irrespective of symptomatic status.

Recommendations from the CSO-HNS taskforce on performance of tracheotomy during the COVID-19 pandemic.

INTRODUCTION: The performance of tracheotomy is a common procedural request by critical care departments to the surgical services of general surgery, thoracic surgery and otolaryngology - head & neck surgery. A Canadian Society of Otolaryngology - Head & Neck Surgery (CSO-HNS) task force was convened with multi-specialty involvement from otolaryngology-head & neck surgery, general surgery, critical care and anesthesiology to develop a set of recommendations for the performance of tracheotomies during the COVID-19 pandemic. MAIN BODY: The tracheotomy procedure is highly aerosol generating and directly exposes the entire surgical team to the viral aerosol plume and secretions, thereby increasing the risk of transmission to healthcare providers. As such, we believe extended endotracheal intubation should be the standard of care for the entire duration of ventilation in the vast majority of patients. Pre-operative COVID-19 testing is highly recommended for any non-emergent procedure. CONCLUSION: The set of recommendations in this document highlight the importance of avoiding tracheotomy procedures in patients who are COVID-19 positive if at all possible. Recommendations for appropriate PPE and environment are made for COVID-19 positive, negative and unknown patients requiring consideration of tracheotomy. The safety of healthcare professionals who care for ill patients and who keep critical infrastructure operating is paramount.