ABSTRACT
Introduction: Coronavirus Disease-2019 (COVID-19) has affected healthcare access to population around the world. India also had its own set of problems for patients with disruption of healthcare services during the pandemic. This also brought in unique challenges for ophthalmologists who adapted to new challenges to provide quality care to the patients including those reporting for cataract surgery. Aim: To find out cataract surgery trends and demographic variables during lockdown and unlocking periods of COVID-19 pandemic. Materials and Methods: This cross-sectional hospital-based study was conducted at Ophthalmology department of a tertiary care centre in eastern India, from January 2020 to March 2022. Trends of cataract surgery including numbers, demographic factors, visual acuity at presentation, difference during first and second lock and unlock periods etc were compared during various lock and unlock period over more than two years. Results: A total of 3,843 patients were planned for surgery and 3,594 patients underwent cataract surgery. A total of 218 patients reported being positive for COVID-19 preoperatively and voluntarily dropped out from surgery. A total of 24 patients were found to be positive during preoperative Reverse Transcriptase Polymerase Chain Reaction (RT-PCR) workup and were excluded from surgery. Seven patients didn't report for the surgery. A total of 59 patients reported febrile illness during one month postoperative period. There was dip in cataract surgery during lockdown periods (from 178.33 every month in pre COVID-19 period to near zero during first lockdown period) but recovery was much faster during second unlock period compared to first unlock period. Conclusion: The study concludes that there was drastic decrease in number of patients undergoing cataract surgery during COVID-19 pandemic. Predominantly young, male patients who had advanced morphology of cataracts with poor visual acuity accessed healthcare set-up for cataract surgery during initial lock and unlock period. Similar trend was seen during second lock and unlock period with rapid recovery of numbers and demography of cataract surgery patients to pre-COVID-19 levels. [ FROM AUTHOR] Copyright of Journal of Clinical & Diagnostic Research is the property of JCDR Research & Publications Private Limited and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)
ABSTRACT
Today, it is impossible for a being to fathom living without a vehicle for transportation of any kind. All governments have put into place numerous regulations on the use of well-maintained vehicles to stop this, but there are always exceptions. The world is transitioning to an automated system that requires little human interaction as a result of the COVID-19 pandemic. This intelligent system involves identifying the predicting trends in the market analysis based on the expenses and revenues patterns of a particular group of people in a city or location. This the system needs to offer the insight into the direction for decision making of the market on demand of vehicle as per the supply with respect to the type of roads, season, and gender and age group patterns. Apartfrom this, the tax rules make a huge difference in this context. In some zones, many governments encourage by giving lots of subsidies or give tax relaxations to certain cc vehicles. In the future, based on the distance travelled, the system can impose tax fair or toll plaza fee. © 2023, IGI Global. All rights reserved.
ABSTRACT
Monitoring patient's blood oxygen saturation (SpO(2)) levels using pulse oximeter is important to physician. SpO(2) is also one of the major parameter that is being monitored to assess the respiratory health in Covid-19 infected patients during the ongoing pandemic. In pulse oximeters, the motion artifacts (MA), due to voluntary or involuntary movement of patient, will disturb the morphology of the photoplethysmographic (PPG) signals acquired through a finger/forehead sensor resulting in inaccurate SpO(2) values. The current work is focused on an efficient adaptive filtering method for MA reduction, which uses a wavelet reconstructed secondary MA noise as reference signal. It eliminates the use of an external sensor to be employed for estimating MA signal. This method while reducing the MA restored the PPG morphology and respiratory components facilitating accurate estimation SpO(2), heart rate (HR).
ABSTRACT
Background: Lockdown during COVID-19 led to teachers and children shifting to online classes, using visual display terminals (VDTs) for education, resulting in increased screen time. The present study was done to assess and understand the nature and magnitude of the problem and to suggest preventive or remedial measures. Methods: A questionnaire-based cross-sectional study was conducted. The questionnaire was prepared for an online survey (using Google Forms) and circulated among school children belonging to different schools across India using multiple groups on social media. Results: A total of 3327 participants from 46 schools across India participated in the survey. We found a marked rise in cumulative screen time for both teachers and students before and during the lockdown. There was a threefold increase in the number of participants with a cumulative screen time 6 h or more compared to the pre-COVID era. Teachers (older participants) had worse symptom scores than students. Larger screens, like televisions, were better VDTs compared to smartphones, tablets, or laptops. Conclusions: School administrators and policymakers should pay due attention to institutionalizing the guidelines about class duration, appropriate screens, and stipulating break duration during online classes, which will continue to remain the predominant mode of education for teachers and students alike, at least in the near future.
ABSTRACT
The entire world has been affected by the outbreak of COVID-19 since early 2020. Human carriers are largely the spreaders of this new disease, and it spreads much faster compared to previously identified coronaviruses and other flu viruses. Although vaccines have been invented and released, it will still be a challenge to overcome this disease. To save lives, it is important to better understand how the virus is transmitted from one host to another and how future areas of infection can be predicted. Recently, the second wave of infection has hit multiple countries, and governments have implemented necessary measures to tackle the spread of the virus. We investigated the three phases of COVID-19 research through a selected list of mathematical modeling articles. To take the necessary measures, it is important to understand the transmission dynamics of the disease, and mathematical modeling has been considered a proven technique in predicting such dynamics. To this end, this paper summarizes all the available mathematical models that have been used in predicting the transmission of COVID-19. A total of nine mathematical models have been thoroughly reviewed and characterized in this work, so as to understand the intrinsic properties of each model in predicting disease transmission dynamics. The application of these nine models in predicting COVID-19 transmission dynamics is presented with a case study, along with detailed comparisons of these models. Toward the end of the paper, key behavioral properties of each model, relevant challenges and future directions are discussed.
ABSTRACT
Today we can no longer imagine our lives without a vehicle for any means of transportation. They play a very important role in everyone's life. But as their importance in our lives grows, so does the fraud and antisocial activity associated with these vehicles. License plate forgeries, car theft, antisocial activity in stolen vehicles are times to improve detection skills and tracking capabilities. This framework will help how to trace a suspicious and fraudulent vehicle. And with the COVID pandemic, the world is moving towards an autonomous system that requires minimal human intervention. Our goal in this document is to use computer vision technology to create a reliable, autonomous and affordable system. This allows you to identify or track a vehicle that has been fraudulent or stolen.
ABSTRACT
Human life gets interrupted a lot when a communicable disease starts in a society. People are alerted a lot on a different basis and eventually, it leads to difficulty for continuing their normal life. This paper is focused on a communicable disease, the COVID-19, which gave an outbreak for all world counties into a state where their fellow human had to stop their daily job and stay back at home. Common people find it difficult to get treatment when they are identified as positive and also most of them lack the awareness of post covid recovery. The idea of this work is to create a healthcare system that initiates right from the covid test, appropriate treatment according to severity, post-recovery, and vaccination awareness and jabs. These units will have less human interaction and they will be fully automated till in need of pure doctor consultation. The automated system is programmed to identify the infection, its severity and prescribe the treatment accordingly, and follow up recovery needs. On-side, automated vaccination system will allow direct walk-in, identify the customer and do the needful. © 2021 Institute of Physics Publishing. All rights reserved.