ABSTRACT
Background: The development of a specific curative drug or prophylactic and vaccine is urgently required to cure COVID-19. Sulfonamide and its derivatives are famous for their multi-faceted antibiotic and antiviral activities against verities of a pathogen. Objective(s): The objective of this study is to find new potential molecules for COVID-19 treatment. We tested some sulfonamide molecules (including antiviral compounds) as SARS CoV-2 Mpro in-hibitors. Method(s): In this study, the Density Functional Theory (DFT) and Docking study have been util-ized for protein-small molecule affinity prediction. The SwissADME server was used for pharma-cokinetics and drug-like likeness prediction, and the Pred-hERG server was employed for cardio-toxicity prediction. Result(s): In this study, sixteen sulfonamides have been investigated in silico, with a perspective to obtaining a potential anti-covid compound. The sulfonamides have been subjected to molecular docking with SARS CoV-2 Mpro, mainly responsible for viral infection and replication. We discov-er the molecular flexibility and charge distribution profoundly affecting the binding of the compounds to the protein. Moderately flexible (six rotatable bond) and less polar (sufficient hydropho-bic) sulfonamide are favorable for strong binding with the enzyme. Here, the bioavailability proper-ties like adsorption, distribution, metabolism, excretion, pharmacokinetics, and potential toxicity of these compounds have also been checked. Conclusion(s): Low cardio-toxicity and high bioavailability make these sulfonamides a good anti-COVID-19 drug option. The sulfonamide 16 was found to be the best.Copyright © 2022 Bentham Science Publishers.
ABSTRACT
We introduce a SEIRD compartmental model to analyze the dynamics of the pandemic in Bangladesh. The multi-wave patterns of the new infective in Bangladesh from the day of the official confirmation to August 15, 2021, are simulated in the proposed SEIRD model. To solve the model equations numerically, we use the RK-45 method. Primarily, we establish some theorems including local and global stability for the proposed model. The analysis shows that the death curve simulated by the model provides a very good agreement with the officially confirmed death data for the Covid-19 pandemic in Bangladesh. Furthermore, the proposed model estimates the duration and peaks of Covid-19 in Bangladesh which are compared with the real data.
ABSTRACT
Massive vaccination is very important to end the coronavirus disease 2019 (COVID-19) pandemic. This study determined the willingness to receive a COVID-19 vaccine by the university students of Bangladesh and identified their apprehension about the effectiveness and safety of COVID-19 vaccines. Students were invited to complete an online cross-sectional survey (April 3 to June 10, 2021) to explore the intention to receive a COVID-19 vaccine and other factors regarding the responsiveness of the COVID-19 vaccine. Among the 191 respondent students, 52.9% willingly agreed to receive a vaccine, where the remaining was either not decided yet (27.7%) or was not intended to get vaccinated (15.7%). The odd of getting a vaccine were only 1.15. About 83.2% of students were conscious about the severity of COVID-19 and many students responded that they are well-versed about vaccine activity (67.5%) and risk factors (66%). Among the approved vaccines, most students preferred the Oxford-AstraZeneca COVID-19 vaccine ChAdOx1 (38.7%) and Pfizer-BioNTech COVID-19 vaccine BNT162b2 (34%). As some of the students still have lesser intent to accept vaccines, public health officials need to be more proactive to focus on vaccine safety and benefits to enhance vaccine coverage among university students of Bangladesh. © 2022, Intelektual Pustaka Media Utama. All rights reserved.
ABSTRACT
Background: Coronavirus disease 2019 (COVID-19) caused by Severe Acute Respiratory Syndrome Corona Virus-2 (SARS-CoV-2) is in Pandemic form and has affected people of 215 countries. It produces symptoms like fever, cough, shortness of breath, sore throat, headache, loss of taste, smell or appetite and many other rare symptoms. But the most important symptom is shortness of breath due to hypoxia. In a normal individual oxygen saturation (SpO(2)) is at least 95% and patient feels shortness of breath when SpO(2) falls below 90% with some exception. SARS-CoV-2, a newly emergent coronavirus has the peculiarity to produce silent hypoxia, meaning SpO 2< 90% or less like 80%, 70%, 60% without shortness of breath. Silent hypoxia can be diagnosed by monitoring SpO(2) with pulse oximeter. For management of COVID-19, early symptoms like fever & cough, SpO(2) should be monitored by pulse oximeter, followed by immediate correction of hypoxia by O-2 supplementation and prophylactic oral or injectable anticoagulant to prevent thromboembolism and thus death rate can be reduced. Case summary: A 72-year-old man presented with the complaints of fever and headache followed by cough, fatigue, anorexia, loss of taste and appetite in next few days but no shortness of breath. The patient was clinically diagnosed as a case of COVID-19 & positive result of Real time-Polymerase Chain Reaction (RT-PCR) test confirmed the diagnosis. From the first day, SpO(2) was regularly monitored with pulse oximeter and SpO(2) on day 1, it was 96-98%. On day 8, SpO(2) fell to 89-93%, pulse 96/min, respiratory rate>30/min, temperature 101o F, taste sensation was reduced. According to sign and symptoms, the patient was diagnosed as COVID-19 with severe pneumonia. Management was started at home with continuous monitoring, lying in prone position for 5-6 hours/day, supplemental oxygenation to maintain level of SpO(2) between 94-96%, injectable anticoagulant enoxaparin to prevent venous thromboembolism (VTE) and disseminated intravascular coagulation (DIC) was given. Prophylactic antibiotics and symptomatic treatment were also given. Results: According to this case report, patient's SpO(2) was monitored by pulse oximeter on first day;on day 08, SpO(2) fell to 89-93% & on day 10, further dropped to 85-88% which indicated severe pneumonia but there was no complaint of breathlessness as it was silent hypoxia. Sometimes the patient spent 30 minutes or more in toilet and SpO(2) used to fall to 82-83% without any subjective shortness of breath but with only mild heaviness of chest and cough. Therefore SpO(2) monitoring by pulse oximeter is essential in early diagnosis of silent hypoxia. Correction of hypoxia by supplemental oxygenation and prevention of VTE and DIC by using anticoagulant was the mainstay of treatment and patient had significant improvement on day 14. The patient was managed completely at home except X-ray being done in a hospital. Conclusion: Fall of SpO(2) in COVID-19 i.e. hypoxia (usually present as shortness of breath) or silent hypoxia can be diagnosed early by pulse oximeter or smart phone pulse oximetry apps. Early management by isolation, supplemental oxygenation and oral/injectable anticoagulation can prevent further events like Acute Respiratory Distress Syndrome (ARDS), respiratory failure followed by multiple organ failure (that may cause death). The authors advocate further clinical trial and research.
ABSTRACT
Air pollution and COVID-19 both are the most provocative issue nowadays. Air pollution holds a dangerous impact on the COVID-19 issue as well as human health. The urban cities like Dhaka are under stress to remain habitable. With the huge density of transportation and population, air quality index is to be monitored minutely and the impact of the COVID-19 pandemic is to be observed. It is required to develop an Internet of Things based remote monitoring system to observe the air particularity in the different areas of the Dhaka city and make a comparison between the before and during the COVID-19 Pandemic. The platform aims to track out the concentration of gases in the Dhaka City like carbon monoxide (CO), nitrogen di-oxides (NO2) on real-time that provides air quality index (AQI). Using Arduino based Node MCU and the sensors are to detect substantive conditions of gases. ESP-32 Wi-Fi module is used to send the data to the server so that it can be accessed from anywhere. The data is taken before and during COVID-19 period with the developed IoT platform. It shows the difference between the CO and NO2 emission on the impact of the pandemic with the measured value. This study will help us to make further decisions and action regarding air pollution. © 2021 IEEE.