ABSTRACT
The current study examines the air quality trends in response to Covid-19-induced lockdowns at various locations in Delhi. The primary pollutants like NO2, CO, and PM10 have shown reductions during the lockdown phase, but the magnitude varied significantly in different places. Also, during the lockdown, air quality in some areas of Delhi exceeded National Ambient Air Quality Standards. Secondary pollutants like O3 have shown mixed trends due to complex atmospheric processes and dependence on relative proportions of VOC and NOx levels. A total of six sites, including traffic, industrial, and residential sites, have been studied. The diurnal behavior of pollutants also differed significantly around different places. During the lockdown, Ashok Vihar, a traffic-influenced area, showed a decrease in O3 (~ 40%), while at DTU (Traffic site), O3 levels increased (~ 48%). The industrial sites Okhla and Wazirpur also showed different trends during the lockdown;O3 in Wazirpur decreased by 50%, whereas Okhla increased by 25%. NOx concentration was lesser in 2020 at all the stations compared to 2019, indicating the positive impact of the lockdown on air pollution due to vehicular emissions. The Approximate Envelope Method estimates the secondary fraction of PM2.5. This fraction of PM is dominated in the lockdown year in the residential site, while it remains unchanged in the traffic site and increased by 11% in the industrial area. Despite being not so far from each other, these sites show very different patterns of pollutants during lockdown episodes. © 2023, The Author(s) under exclusive licence to Institute of Earth Environment, Chinese Academy Sciences.
ABSTRACT
Prognostic markers are the biomarkers used to measure the disease progression and patient outcome regardless of treatment in coronavirus disease 2019 (COVID-19). This study aimed to analyze laboratory parameters as prognostic markers for the early identification of disease severity. In this study, 165 patients attending Sukraraj Tropical and Infectious Disease Hospital with COVID-19 were enrolled and divided into severe and non-severe groups. The demographic data, underlying co-morbidities, and laboratory findings were analyzed and compared between severe and non-severe cases. The correlation between the disease criticality and laboratory parameters was analyzed. Cut-off values of parameters for severe patients were speculated through the receiver operating characteristics (ROC) curve, and regression analysis was performed to determine the risk factors. Patients with severe COVID-19 infection had significantly higher absolute neutrophil count, neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), ferritin, positive carbohydrate reactive protein (CRP), glucose, urea, creatinine, and aspartate aminotransferase, while lower absolute lymphocyte count, absolute eosinophil count (AEC), and red blood cell count in comparison to non-severe infection. ROC analysis gave a cut-off value (sensitivity, specificity) of age, AEC, NLR, PLR, and ferritin as 47.5 years (70.2, 64.7%), 335 cells/mm(3) (74, 67%) 3.3 (68.4, 63.7%), 129 (77.2, 51%), and 241 ng/mL (74.0%, 65.0%) respectively. Risk factor analysis showed higher age, low AEC, high ferritin, and positive CRP as independent risk factors associated with severe COVID-19 infection. Hematological and inflammatory markers, including novel NLR and PLR, should be assessed to aid clinicians in the early identification of severe cases, prioritization of cases, and effective management to decrease the mortality of COVID-19 patients.
ABSTRACT
The Covid-19 has presented an unprecedented challenge to public health worldwide. However, residents in different countries showed diverse levels of Covid-19 awareness during the outbreak and suffered from uneven health impacts. This study analyzed the global Twitter data from January 1st to June 30(th), 2020, to answer two research questions. What are the linguistic and geographical disparities of public awareness in the Covid-19 outbreak period reflected on social media? Does significant association exist between the changing Covid-19 awareness and the pandemic outbreak? We established a Twitter data mining framework calculating the Ratio index to quantify and track awareness. The lag correlations between awareness and health impacts were examined at global and country levels. Results show that users presenting the highest Covid-19 awareness were mainly those tweeting in the official languages of India and Bangladesh. Asian countries showed more disparities in awareness than European countries, and awareness in Eastern Europe was higher than in central Europe. Finally, the Ratio index had high correlations with global mortality rate, global case fatality ratio, and country-level mortality rate, with 21-31, 35-42, and 13-18 leading days, respectively. This study yields timely insights into social media use in understanding human behaviors for public health research.
ABSTRACT
The novel coronavirus (COVID-19) outbreak has been announced as a “Public Health Emergency of International Concern” and further identified as a pandemic by the World Health Organization. Considering the unprecedented spread of the disease across the world, the development of noncontact and unobtrusive methods for quick screening of potential carriers is the need of the hour. The chapter describes a multimodal approach for rapid screening of potential COVID-19 carriers based on symptomatic sensing using a combination of sensors, followed by generation of a metric to indicate the severity of symptoms. The proposed system is likely to be a significant addition to the present body of systems to scan COVID-19 carriers. © 2022, Springer Nature Switzerland AG.
ABSTRACT
Since the early detection of COVID-19 infection in December 2019, the number of infected persons has been increasing day by day. In this present scenario, people worldwide are reorganizing their life taking safety precautions like doing frequent sanitization, wearing face masks, and avoiding social gathering to protect themselves from getting infected as the proven vaccine or lifesaving drugs are yet to be discovered. However, deficiency of face mask and their reusability have become a key issue because the used masks need to be discarded after some time. In this background, we propose the design of a self-powered (no external power source) face mask which does not require to be sterilized. The proposed mask is comprised of two differently charged tribo-series materials with outer electrocution layer. Different combinations of tribo-series (+ and −) materials have been chosen based on their triboelectric properties to generate static electricity. Nanofibers have been considered for their ability to generate a sufficient amount of triboelectricity. Multilayer of electrospun nanofiber-based tribo-materials such as polyvinylidene fluoride (PVDF)-nylon and PVDF-poly(ethyl methacrylate) has been used due to the effective air filtration property of nanofibers and generating tribo electricity. In addition, the generated charge via utilization of contact electrification and electrostatic induction is amplified using a suitable energy harvesting circuit. The design of an outer electrocution layer has been made keeping a few nm distances in between the tribo-layers and the electrocution layer to avoid short-circuiting. Metallic nonwoven fabric has been taken in practice to design the outer electrocution layer. In this practice, the harvesting of triboelectric energy has been done using a suitable charging circuit which can generate sufficient voltage (few volts) to trigger the outer electrocution layer. During the wearer’s inhalation and exhalation, the inner tribo-layers produce triboelectric charges due to mechanical agitation between the layers. Additionally, acoustic or air vibration during talking and different facial expressions of the volunteer will also take part in the generation of effective triboelectric power. The viruses get electrocuted once the droplets containing viruses come in contact to the mask’s outer layer. In addition, the fitting comfort and the breathing permeability of the proposed mask are also ensured. In this chapter, we shall explain the face mask’s design and present the analysis results of different physiological inputs for the efficacy of the mask for killing the deadly virus. © 2022, Springer Nature Switzerland AG.
ABSTRACT
In this work, an all-fiber pyro- and piezo-electric nanogenerator (PPNG) is designed using multiwall carbon nanotube (MWCNT) doped poly(vinylidene fluoride) (PVDF) electrospun nanofibers as the active layer and an interlocked conducting micro-fiber based electrode for converting both thermal and mechanical energies into useful electrical power. The PPNG generates high electrical throughput (output voltage similar to 35 V, maximum power density similar to 34 mu W cm(-2) and power conversion efficiency (eta(piezo)) similar to 19.3%) with an ultra-fast response time of similar to 10 ms. Owing to the higher piezoelectric charge co-efficient (;d(33);similar to 51.3 pC N-1) and figure of merit (FoM approximate to 5.95 x 10(-11) Pa-1) of PVDF-MWCNT nanofibers in comparison to the neat PVDF nanofibers (;d(33);similar to 22 pC N-1 and FoM approximate to 9.7 x 10(-12) Pa-1) the PPNG operates a range of consumer electronic components such as capacitors and light emitting diodes. Furthermore, the electroactive phase content (similar to 87%) is improved in the active layer due to the interfacial interaction between the surface charges at from the pi-electron cloud of the MWCNT and -CH2- dipoles of the PVDF chain. Additionally, the PVDF-MWCNT nanofibers possess fifteen times higher pyroelectric coefficient (similar to 60 nC m(-2) K-1) compared to that of neat PVDF nanofibers (4 nC m(-2) K-1). As a result, the PPNG is capable of converting very large temperature fluctuations (Delta T similar to 14.30 K) to electrical energy (such as the open-circuit voltage of 250 mV and a short-circuit current of 83 pA). Besides this, it is capable of detecting very low-level thermal fluctuations (as low as Delta T similar to 5.4 K) with responsivity of similar to 1.48 s and possesses very high mechano-sensitivity (similar to 7.5 V kPa(-1)) which makes it feasible for use as a biomedical sensor since the body temperature and bio-mechanical signals (such as breathing temperature, pulse rate, vocal cord vibrations, coughing sound, and so on) have an immense signature of health conditions. As a proof-of-concept, the all-fiber PPNG is employed as a biomedical sensor by integrating with the Internet of Things (IoT) based human health care monitoring system as well as for remote care of infectious diseases (e.g., applicable for pneumonia, COVID-19) by transferring the pulse response, body temperature, coughing and laughing response wirelessly to a smartphone.
ABSTRACT
Background: The pathological agent of Coronavirus disease 2019 (COVID-19) is a novel coronavirus termed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). COVID-19 has its origin in Wuhan, China, and spread to other provinces of China and subsequently to other countries resulting in a pandemic worldwide. The virus is extremely contagious and causes pneumonia and respiratory failure. Since its emergence, researchers around the world are trying to develop vaccines and find suitable drugs for the treatment of COVID-19. Objective: To give an overview of the various therapeutic agents for COVID-19 such as vaccines and drugs that are in preclinical stage or under different stages of clinical trials. Results: As per World Health Organization (WHO), there are 137 vaccines under development to date, out of which few vaccines have successfully completed preclinical studies and reached clinical trials. According to the present scenario, only one coronavirus vaccine (sputnik-V) has been approved by the Ministry of Health of the Russian Federation. Till date, there are no United States Food and Drug Administration (USFDA) approved drugs to treat COVID-19 patients. However, depending on patient's condition, different drugs such as antiviral agents like Remdesivir, antimalarial drugs like Hydroxychloroquine, antibiotics like Azithromycin and corticosteroids like Dexamethasone are being applied and some of them have proved to be effective up to a certain extent. Conclusion: Although several vaccines for COVID-19 are under development and various drugs have been tried for its treatment, an ideal drug candidate or a vaccine is still lacking. Almost all the big pharmaceutical companies are associated with one or more research initiatives in order to develop vaccines and drugs. Many of them are going through clinical stages, expecting a positive outcome by the end of 2020.