Covid-19 lockdown effect on aerosol optical depth in Delhi National Capital Region, India

Coronavirus cases in India have been steadily increasing since March 2020. COronaVIrus Disease 2019 (COVID-19) has been managed by a variety of preventative measures. A prominent measure by the Government of India to prevent the spread of Coronavirus Disease 2019 (COVID-19) began on March 25, 2020, with a complete suspension of all outdoor activities throughout the country. Such complete lockdown has resulted in a decrease in anthropogenic emissions, which is partly due to restrictions on human activities. Delhi National Capital Region (NCR), a landlocked area, suffers from high amounts of aerosols due to both natural and anthropogenic sources. The present research focuses on changes in Aerosol Optical Depth (AOD) prior to and during lockdown (initial and second lockdown phases) around satellite cities (Faridabad, Ghaziabad, Gautam Budh Nagar and Gurugram) of Delhi using high-resolution MODIS AOD product. With the implementation of lockdown measures in phase I and phase III of the current study region, AOD decreased dramatically, while phase II and phase IV lockdown phases had a higher concentration of aerosol. An unexpected increase in AOD occurred during the second lockdown compared with the initial lockdown and before the lockdown. Overall, the average percentage change from 2019 to 2020 during first lockdown is -4.44%, while the average percentage change from 2020 to 2021 is 27.63%. © 2022 The Author(s). Published by Forum geografic.

Th17 overexpression in severe COVID-19: a prospective observational study.

INTRODUCTION: The objective of the study was to determine T-cell subtypes, Natural Killer cell activity and cytokines in COVID-19 patients with mild to moderate disease and compare them between patients who had recovered and those who had progressed to severe disease. METHODS: Peripheral blood samples of COVID-19 patients were collected at the time of hospital admission and after one week. These samples were analysed for interleukins (IL-6, IL-17a) using chemiluminescence ELISA. The T-cell subsets (T naïve, T regulatory, Th17, Th1, Th2, CD8+ T cells] were studied using flow cytometry. Mild, moderate and severe COVID-19 are defined as per CDC guidelines. RESULTS: Nineteen COVID-19-positive patients were enrolled between June 2020 to December 2021. Nine had mild COVID-19 and 10 had moderate COVID-19 at recruitment. All mild cases recovered without progression to severe disease, while five patients from the moderate group progressed to severe disease. Overall, there is a decrease in lymphocyte count in patients with moderate-severe disease, but the ratio of Th17 [5.91 (2.69-12.01)] was higher compared to Th1 [1.12 (0.27-3.13)] and Th2[2.34 (2-3.5)]. The high baseline level of IL-6 observed in patients with moderate disease leads to the proliferation of more Th17 type of CD4+ T-cells(p=0.002) and suppression of Treg cells. A higher Th17 subset leads to neutrophilic inflammation in patients with severe COVID-19. CONCLUSION: Interpretation conclusions: Higher baseline IL-6 leads to depletion of regulatory T-cells, Th1 Th2 CD4 cells. IL-6 leads to the proliferation of Th17 type of CD4+ subsets in moderate COVID-19. Higher Th17 cells in moderate COVID-19 patients lead to the production of IL-17a, which may result in intense neutrophilic inflammatory response and cytokine storm.

A comprehensive survey on the beliefs, perceptions, and clinical manifestations of pre and post Covid-19 vaccinations among physiotherapy students in the United Arab Emirates.

The World Health Organization has defined Coronavirus Disease (COVID-19) as an infectious pandemic, caused by a newly discovered SARS-CoV-2 virus. Students relied heavily on the internet, social media, parents, and friends, in addition to medical advice for information on its presentation, complications, prevention, and management. It is evident from the literature that healthcare professionals including students who play an important role in the healthcare system may be lacking important information on COVID-19 vaccinations. Thus, the study aims to identify and compare the pre-post covid-19 vaccination-related essential information among Physical Therapy university students. A cross-sectional survey was conducted among physiotherapy university students in the United Arab Emirates using a self-administrated structured questionnaire. The questionnaire comprised three sections covering beliefs, perceptions, and clinical manifestations of the pre- and post-COVID- 19 vaccination. The survey was shared with more than 300 students through email and social platforms during the time between January 2022 till December 2022. Most of the physiotherapy students believed the vaccines to be safe (71.3%) due to multiple reasons while others did not believe in the effectiveness of the vaccine (28.7%). Some students did report unusual symptoms (painful periods, hair loss, forgetfulness) after the vaccine (10%). Similar findings were reported for family members as well (14%). Students had a positive perception of the vaccine and reported willingness to take it even if not mandatory (68%). Some students did believe in the safety of the vaccine due to multiple reasons while some did not due to fear of long-term side effects and personal choices. The finding of the study could be useful to create confidence as well as awareness among physiotherapy students as they are often invited to aid during medical pandemics such as Covid 19. Also, higher rates of vaccination among healthcare professionals will impart higher acceptance in the medical organization due to safety guidelines. This could also help to counsel other students against fear and apprehension towards the vaccination of such kind in the future.

Nanotechnology Toolkit for Combating COVID-19 and Beyond.

The outbreak of SARS-CoV-2 is unlikely to be contained anytime soon with conventional medical technology. This beckons an urgent demand for novel and innovative interventions in clinical protocols, diagnostics, and therapeutics; to manage the current "disease X" and to be poised to counter its successor of like nature if one were to ever arise. To meet such a demand requires more attention to research on the viral-host interactions and on developing expeditious solutions, the kinds of which seem to spring from promising domains such as nanotechnology. Inducing activity at scales comparable to the viruses themselves, nanotechnology-based preventive measures, diagnostic tools and therapeutics for COVID-19 have been rapidly growing during the pandemic. This review covers the recent and promising nanomedicine-based solutions relating to COVID-19 and how some of these are possibly applicable to a wider range of viruses and pathogens. We also discuss the type, composition, and utility of nanostructures which play various roles specifically under prevention, diagnosis, and therapy. Further, we have highlighted the adoption and commercialization of some the solutions by large and small corporations alike, as well as providing herewith an exhaustive list on nanovaccines.

SARS-CoV-2 detection in human milk: a systematic review.

PURPOSE: To synthesize the current evidence for the presence of SARS-CoV-2 RNA in the human milk of mothers with confirmed COVID-19 and its potential role in neonatal SARS-CoV-2 infection. MATERIALS AND METHODS: Using terms related to novel coronavirus 2019 and human milk, a systematic search was performed in three electronic databases (PubMed, EMBASE, and Web of Science) for studies published between December 2019 and 15 October 2020. Published peer-reviewed studies reporting the results of RT-PCR for SARS-CoV-2 RNA in human milk in mothers with confirmed COVID-19 were included. Proportion meta-analysis of case series and prospective cohort studies was performed using STATA version 14.2 (StataCorp, College Station, TX) and pooled estimate (with 95% confidence interval) of overall incidence of SARS-CoV-2 transmission was calculated. RESULTS: We identified 936 records, of which 34 studies (24 case-reports, 10 cohort studies) were eligible for this systematic review. A total of 116 confirmed COVID-19 lactating women (88 in cohort and 28 in case-reports) underwent RT-PCR testing in human milk, and 10 (six in case reports) were detected to have SARS-CoV-2 RNA. The overall pooled proportion (from cohort studies) for SARS-CoV-2 RNA detection in human milk was 2.16% (95% CI: 0.0-8.81%, I2: 0%). Four studies (six patients) also reported the presence of SARS-CoV-2 specific antibodies (along with RT-PCR) in human milk. CONCLUSIONS: The limited low-quality evidence suggests that SARS-CoV-2 RNA is detected in human milk in an extremely low proportion, however, based on current evidence no conclusion can be drawn about its infectivity and impact on the infants. In concordance with World Health Organization recommendations, exclusive breastfeeding should be considered in all cases unless any other contraindication exists.

Impact on corneal morphology after cataract surgery with intracameral moxifloxacin in neglected hard cataracts.

AIM: To evaluate corneal morphology after use of 0.5% intracameral moxifloxacin (ICM) in cataract surgery in patients who presented late with hard cataracts. METHODS: Cross-sectional study conducted from June-2021 to December-2021 at a tertiary eye-care center. 90 patients over 60 years with high-risk characteristics for Covid-19, who presented late with higher grades of nuclear-sclerosis (NS), were included. They underwent phacoemulsification and 0.5%moxifloxacin (0.1 ml) was injected intracamerally at the end of surgery. Best-corrected visual acuity (BCVA), intraocular pressures (IOP), endothelial cell density (ECD), coefficient of variation in cell-area (CoV), hexagonality (Hex) and central corneal thickness (CCT) were measured preoperatively and postoperatively on day1, day7 and day30. Statistical analysis was done by Anova test. p-value<0.05 was considered significant. RESULTS: Mean age of presentation was 65.26±8.3 years. Mean preoperative BCVA (1/60-to-6/60), IOP (16.7±2.3 mm of Hg), CCT (523.93±39.6µ), ECD (2547±302.08cells/mm2), Hex (47.04±5.7%) and CoV (37.57±3.9) changed to BCVA (6/9-to-6/6), IOP (17.5±2.1 mm of Hg), CCT (538.42±36.9µ), ECD (2388.40±339.25cells/mm2), Hex (44.44±5.6%) and CoV (39.09±4.5) at day30 postoperative. Average rate of change at day30 was increase in CCT (2.89%), ECD loss (6.4%), decrease in Hex (4.9%) and increase in CoV (4.6%), though clinically insignificant. No case of endophthalmitis or toxic-anterior segment syndrome seen. CONCLUSION: 0.5% moxifloxacin (0.1 ml) is safe as intracameral antibiotic to prevent postoperative infection in high-risk patients. The reported changes in the corneal parameters were within the range of any routine surgeries of hard senile cataracts. No specific effect could be attributed to ICM.

Mortality audit of COVID-19 infection among children.

Background & objectives: As severe COVID-19 and mortality are not common in children, there is a scarcity of data regarding the cause of mortality in children infected with SARS-CoV-2. This study was aimed to describe the all-cause mortality and COVID-19 death (disease-specific mortality) in children with SARS-CoV-2 infection admitted to a paediatric COVID facility in a tertiary care centre. Methods: Data with respect to clinical, epidemiological profile and causes of death in non-survivors (0-12 yr old) of SARS-CoV-2 infection admitted to a dedicated tertiary care COVID hospital in north India between April 2020 and June 2021 were retrieved and analyzed retrospectively. Results: A total of 475 SARS-CoV-2-positive children were admitted during the study period, of whom 47 died [18 neonates, 14 post-neonatal infants and 15 children (1-12 yr of age)]. The all-cause mortality and COVID-19 death (disease-specific mortality) were 9.9 per cent (47 of 475) and 1.9 per cent (9 of 475), respectively. Underlying comorbidities were present in 35 (74.5%) children, the most common being prematurity and perinatal complications (n=11, 24%) followed by congenital heart disease (n=6, 13%). The common causes of death included septic shock in 10 (21%), COVID pneumonia/severe acute respiratory distress syndrome in nine (19%), neonatal illnesses in eight (17%), primary central nervous system disease in seven (15%) and congenital heart disease with complication in six (13%) children. Interpretation & conclusions: Our results showed a high prevalence of underlying comorbidities and a low COVID-19 death (disease-specific mortality). Our findings highlight that mortality due to COVID-19 can be overestimated if COVID-19 death and all-cause mortality in children infected with SARS-CoV-2 are not separated. Standardized recording of cause of death in children with SARS-CoV-2 infection is important.

COVID-19 vaccine confidence project for perinatal women (CCPP)-Development of a stepped-care model to address COVID-19 vaccine hesitancy in low and middle-income countries.

Background: COVID-19 vaccine hesitancy (CVH) is common among perinatal women in low and middle-income countries (LMICs), but it is often unaddressed. This could be due to a lack of feasible, scalable, and acceptable interventions and models for CVH in LMICs. Our study aimed to develop a CVH intervention model that can be implemented in LMICs using existing human healthcare resources. Methods: A literature review was conducted on aspects of vaccine hesitancy, pre-existing interventions, and models for addressing vaccine hesitancy (COVID-19 and non-COVID-19). The lead authors (RR and PKuk) formed a team consisting of vaccinators, experts, and stakeholders. Members shared their perspectives and proposals for various models and interventions that could be implemented in LMICs. A CVH intervention model was developed using a logic model, a WHO implementation toolkit, experts' feedback, and consensus. Results: A consensus was reached to develop a COVID-19 Vaccine Confidence Project for Perinatal Women (CCPP), which is a primary health care worker (HCWs)-based stepped-care model. The CCPP model includes HCW training, integration into ongoing COVID-19 vaccination programs, CVH screening, CVH intervention, and referral services suitable for implementation in LMICs. Conclusion: The CCPP project/model provides a practical approach that can help in the early detection and management of CVH. The model can be tailored to different healthcare settings to improve COVID-19 vaccine uptake among perinatal women in LMICs.

A novel multi-modal depression detection approach based on mobile crowd sensing and task-based mechanisms.

Depression has become a global concern, and COVID-19 also has caused a big surge in its incidence. Broadly, there are two primary methods of detecting depression: Task-based and Mobile Crowd Sensing (MCS) based methods. These two approaches, when integrated, can complement each other. This paper proposes a novel approach for depression detection that combines real-time MCS and task-based mechanisms. We aim to design an end-to-end machine learning pipeline, which involves multimodal data collection, feature extraction, feature selection, fusion, and classification to distinguish between depressed and non-depressed subjects. For this purpose, we created a real-world dataset of depressed and non-depressed subjects. We experimented with: various features from multi-modalities, feature selection techniques, fused features, and machine learning classifiers such as Logistic Regression, Support Vector Machines (SVM), etc. for classification. Our findings suggest that combining features from multiple modalities perform better than any single data modality, and the best classification accuracy is achieved when features from all three data modalities are fused. Feature selection method based on Pearson's correlation coefficients improved the accuracy in comparison with other methods. Also, SVM yielded the best accuracy of 86%. Our proposed approach was also applied on benchmarking dataset, and results demonstrated that the multimodal approach is advantageous in performance with state-of-the-art depression recognition techniques.

Clinical characteristics & outcome of SARS-CoV-2 infected neonates presenting to paediatric emergency.

Background & objectives: Data on neonatal COVID-19 are limited to the immediate postnatal period, with a primary focus on vertical transmission in inborn infants. This study was aimed to assess the characteristics and outcome of COVID-19 in outborn neonates. Methods: All neonates admitted to the paediatric emergency from August 1 to December 31, 2020, were included in the study. SARS-CoV-2 reverse transcription- (RT)-PCR test was done on oro/nasopharyngeal specimens obtained at admission. The clinical characteristics and outcomes of SARS-CoV-2 positive and negative neonates were compared and the diagnostic accuracy of a selective testing policy was assessed. Results: A total of 1225 neonates were admitted during the study period, of whom SARS-CoV-2 RT-PCR was performed in 969. The RT-PCR test was positive in 17 (1.8%). Mean (standard deviation) gestation and birth weight of SARS-CoV-2-infected neonates were 35.5 (3.2) wk and 2274 (695) g, respectively. Most neonates (11/17) with confirmed COVID-19 reported in the first two weeks of life. Respiratory distress (14/17) was the predominant manifestation. Five (5/17, 29.4%) SARS-CoV-2 infected neonates died. Neonates with COVID-19 were at a higher risk for all-cause mortality [odds ratio (OR): 3.1; 95% confidence interval (CI): 1.1-8.9, P=0.03]; however, mortality did not differ after adjusting for lethal malformation (OR: 2.4; 95% CI: 0.7-8.7). Sensitivity, specificity, accuracy, positive and negative likelihood ratios (95% CI) of selective testing policy for SARS-CoV-2 infection at admission was 52.9 (28.5-76.1), 83.3 (80.7-85.6), 82.8 (80.3-85.1), 3.17 (1.98-5.07), and 0.56 (0.34-0.93) per cent, respectively. Interpretation & conclusions: SARS-CoV-2 positivity rate among the outborn neonates reporting to the paediatric emergency and tested for COVID-19 was observed to be low. The selective testing policy had poor diagnostic accuracy in distinguishing COVID-19 from non-COVID illness.

Mucormycosis in the COVID-19 Environment: A Multifaceted Complication.

The second wave of coronavirus disease 2019 (COVID-19) caused severe infections with high mortality. An increase in the cases of COVID-19-associated mucormycosis (CAM) was reported predominantly in India. Commonly present in immunocompromised individuals, mucormycosis is often a life-threatening condition. Confounding factors and molecular mechanisms associated with CAM are still not well understood, and there is a need for careful research in this direction. In this review, a brief account of the diagnosis, management, and advancement in drug discovery for mucormycosis has been provided. Here, we summarize major factors that dictate the occurrence of mucormycosis in COVID-19 patients through the analysis of published literature and case reports. Major predisposing factors to mucormycosis appear to be uncontrolled diabetes, steroid therapy, and certain cancers. At the molecular level, increased levels of iron in COVID-19 might contribute to mucormycosis. We have also discussed the potential role and regulation of iron metabolism in COVID-19 patients in establishing fungal growth. Other factors including diabetes prevalence and fungal spore burden in India as contributing factors have also been discussed.

Nationwide implementation of a centralised telemedicine platform in Singapore to fight the COVID-19 pandemic.

INTRODUCTION: This study aims to share the experience of the Ministry of Health (Singapore) in deploying a centrally managed Telemedicine service to triage, and manage COVID-19 cases in the community during the COVID-19 Omicron wave. MATERIAL AND METHODS: Data from the deployed telemedicine system, Telemedicine Allocation and Reconciliation System, over a 14-week period (3 January 2022-10 April 2022) was analysed to determine the safety and efficacy of both the (i) National COVID-19 sorting logic algorithm and (ii) the use of a centralised telemedicine platform with privacy protection in a pandemic. RESULTS: There was a total of 47,754 children (aged 1-11 years old), 75,702 adolescents and adult patients (aged 12-69 years old) and 55,774 geriatric patients (aged > = 70 years old) who were directly managed by this platform. Amongst them, 64,961 were from the higher-risk special populations (pregnant, end-stage renal failure and immunocompromised and geriatric population).The total number of patients requiring escalations to public health institutions were 4212. This accounts for 1.32%, 3.00% and 2.35% of the children, teenagers and adults, and geriatric population respectively.

Mucormycosis in the COVID-19 Environment: A Multifaceted Complication

The second wave of coronavirus disease 2019 (COVID-19) caused severe infections with high mortality. An increase in the cases of COVID-19-associated mucormycosis (CAM) was reported predominantly in India. Commonly present in immunocompromised individuals, mucormycosis is often a life-threatening condition. Confounding factors and molecular mechanisms associated with CAM are still not well understood, and there is a need for careful research in this direction. In this review, a brief account of the diagnosis, management, and advancement in drug discovery for mucormycosis has been provided. Here, we summarize major factors that dictate the occurrence of mucormycosis in COVID-19 patients through the analysis of published literature and case reports. Major predisposing factors to mucormycosis appear to be uncontrolled diabetes, steroid therapy, and certain cancers. At the molecular level, increased levels of iron in COVID-19 might contribute to mucormycosis. We have also discussed the potential role and regulation of iron metabolism in COVID-19 patients in establishing fungal growth. Other factors including diabetes prevalence and fungal spore burden in India as contributing factors have also been discussed.

A case of successful desensitization using therapeutic plasma exchange in high-risk HLA incompatible kidney transplantation.

Advances in immune suppression therapies and desensitization have made possible kidney transplantation regardless of HLA incompatibility. Single antigen bead assay (SAB) is a semi-quantitative estimation of the amount of human leukocyte antigen (HLA) antibodies present in the recipient plasma, and mean fluorescence intensity (MFI) generated gives this rough estimation of the antibodies present in the recipient. Here we present a case of successful kidney transplantation in a patient who expressed DSA with high MFI. A 33-yr-old male, diagnosed with chronic kidney disease (CKD) on regular maintenance hemodialysis, opted for second kidney transplant with his sibling as prospective donor and was referred to the department of Transplant Immunology for histocompatibility testing. Patient had HLA incompatibility with multiple DSA identified by SAB. Patient undergone 20 sessions of plasma exchange till discharge and finally till 6 months graft was functioning well. The authors thus conclude that the option of a high-risk HLA incompatible kidney transplant can be offered to recipients with high MFI DSA, who wish to undergo transplantation for end stage renal disease.

Strengthening tobacco control policies during the COVID-19 pandemic in India.

Problem considered: The aim of this paper was to support policy makers to make informed decisions regarding public health response in general, and tobacco control interventions particularly, in the context of COVID-19. Methods: An online cross-sectional survey using a semi-structured questionnaire was conducted in the year 2020 with stakeholders in tobacco control and public health experts from private and government organizations. Information pertaining to background characteristics of study participants and impact of pandemic on tobacco use and means to leverage tobacco control policy was collected. Data was analysed using Microsoft excel 2010 and results are presented as frequencies and percentages along with key responses from open ended questions. Results: A total of 72 stakeholders were approached out of which, 46 (56.1%) responded and were included. About 32 (74.4%) of the participants thought that public health authorities had given advice on stopping tobacco use during COVID-19 pandemic. About 19 (43.2%) participants did not notice any change in level of interest in tobacco cessation during the pandemic while a majority 34(73.8%) agreed that COVID-19 pandemic had an impact on health seeking behaviour of patients with non-communicable diseases. Nearly half of participants, 21(48.8%) opined that tobacco industry was engaged in corporate social responsibilities during COVID-19. Conclusion: The stakeholders expressed that there is a good opportunity to further strengthen tobacco control activities during COVID-19 pandemic and also emphasized need to closely monitor tobacco industry interference during this time.

Nanotechnology Toolkit for Combating COVID‐19 and Beyond

The outbreak of SARS‐CoV‐2 is unlikely to be contained anytime soon with conventional medical technology. This beckons an urgent demand for novel and innovative interventions in clinical protocols, diagnostics, and therapeutics;to manage the current “disease X” and to be poised to counter its successor of like nature if one were to ever arise. To meet such a demand requires more attention to research on the viral‐host interactions and on developing expeditious solutions, the kinds of which seem to spring from promising domains such as nanotechnology. Inducing activity at scales comparable to the viruses themselves, nanotechnology‐based preventive measures, diagnostic tools and therapeutics for COVID‐19 have been rapidly growing during the pandemic. This review covers the recent and promising nanomedicine‐based solutions relating to COVID‐19 and how some of these are possibly applicable to a wider range of viruses and pathogens. We also discuss the type, composition, and utility of nanostructures which play various roles specifically under prevention, diagnosis, and therapy. Further, we have highlighted the adoption and commercialization of some the solutions by large and small corporations alike, as well as providing herewith an exhaustive list on nanovaccines. Herein, we provide a comprehensive review about nanomaterial‐based technologies for diagnosis and prevention of SARS‐Cov‐2. We also review the applicability of nanomaterial in vaccine development and how nanomaterials can be used as a therapeutic agent to inhibit infection and destroy coronaviruses.

Development and Validation of the RCOS Prognostic Index: A Bedside Multivariable Logistic Regression Model to Predict Hypoxaemia or Death in Patients with SARS-CoV-2 Infection.

Introduction: Previous COVID-19 prognostic models have been developed in hospital settings and are not applicable to COVID-19 cases in the general population. There is an urgent need for prognostic scores aimed to identify patients at high risk of complications at the time of COVID-19 diagnosis. Methods: The RDT COVID-19 Observational Study (RCOS) collected clinical data from patients with COVID-19 admitted regardless of the severity of their symptoms in a general hospital in India. We aimed to develop and validate a simple bedside prognostic score to predict the risk of hypoxaemia or death. Results: 4035 patients were included in the development cohort and 2046 in the validation cohort. The primary outcome occurred in 961 (23.8%) and 548 (26.8%) patients in the development and validation cohorts, respectively. The final model included 12 variables: age, systolic blood pressure, heart rate, respiratory rate, aspartate transaminase, lactate dehydrogenase, urea, C-reactive protein, sodium, lymphocyte count, neutrophil count, and neutrophil/lymphocyte ratio. In the validation cohort, the area under the receiver operating characteristic curve (AUROCC) was 0.907 (95% CI, 0.892-0.922), and the Brier Score was 0.098. The decision curve analysis showed good clinical utility in hypothetical scenarios where the admission of patients was decided according to the prognostic index. When the prognostic index was used to predict mortality in the validation cohort, the AUROCC was 0.947 (95% CI, 0.925-0.97) and the Brier score was 0.0188. Conclusions: The RCOS prognostic index could help improve the decision making in the current COVID-19 pandemic, especially in resource-limited settings with poor healthcare infrastructure such as India. However, implementation in other settings is needed to cross-validate and verify our findings.

D-dimer, an important pathophysiological factor of deadly diseases including SARS

Coronavirus 2019 (COVID-19) is an infectious viral disease with high grade of infectivity, caused by SARS (COV-2). COVID 19 infection was the first reported in Wuhan China. D-dimer is an important predictive tool often recommended for patients with severe Corona virus (COVID19) infection. In this systematic review, we aim to investigate the significance of D-dimer prediction in patients with COVID -19. We used research materials from PubMed, Medline, Embase to learn about D-dimer levels in COVID-19 patients and their effect on mortality.

A novel multi-modal depression detection approach based on mobile crowd sensing and task-based mechanisms

Depression has become a global concern, and COVID-19 also has caused a big surge in its incidence. Broadly, there are two primary methods of detecting depression: Task-based and Mobile Crowd Sensing (MCS) based methods. These two approaches, when integrated, can complement each other. This paper proposes a novel approach for depression detection that combines real-time MCS and task-based mechanisms. We aim to design an end-to-end machine learning pipeline, which involves multimodal data collection, feature extraction, feature selection, fusion, and classification to distinguish between depressed and non-depressed subjects. For this purpose, we created a real-world dataset of depressed and non-depressed subjects. We experimented with: various features from multi-modalities, feature selection techniques, fused features, and machine learning classifiers such as Logistic Regression, Support Vector Machines (SVM), etc. for classification. Our findings suggest that combining features from multiple modalities perform better than any single data modality, and the best classification accuracy is achieved when features from all three data modalities are fused. Feature selection method based on Pearson’s correlation coefficients improved the accuracy in comparison with other methods. Also, SVM yielded the best accuracy of 86%. Our proposed approach was also applied on benchmarking dataset, and results demonstrated that the multimodal approach is advantageous in performance with state-of-the-art depression recognition techniques.