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This study uses social accounting matrix multipliers and structural path analyses to estimate effects of COVID-19 and related fiscal stimuli on five household groups. The COVID-19 lockdown increased poverty in Pakistan by 15%, which was addressed using a $1.5 billion, digitally implemented Ehsaas Emergency Cash (EEC) program that reached 14.8 million poor households. The study's models show that the largest multipliers from Ehsaas program finance were in agriculture, as a 1 Rupee shock adds 0.225 Rupee income to households. About 30% of that gain was estimated to go to poor farm families. In contrast, our models find that construction and trade growth added three times as much income to poor nonfarm and urban households as to farm households. However, those sectors added only one third as much total income as agriculture. From the structural path analysis, the importance of capital assets in generating income was seen, as was the possibility of greater poverty reduction from sectors with proportionally fewer intermediate inputs and more value added. © 2023 The Authors. Applied Economic Perspectives and Policy published by Wiley Periodicals LLC on behalf of Agricultural & Applied Economics Association.
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Background:Bevacizumab, an antiangiogenic drug, is being evaluated for the management of novel coronavirus disease (COVID-19) pneumonia among critically ill patients. The objective of this study was to assess the effectiveness of bevacizumab in severe COVID-19 pneumonia. Methods:This was a retrospective, observational study performed in 111 patients diagnosed with COVID-19 pneumonia. Bevacizumab was administered intravenously at 7.5 mg/kg along with standard care in a non-randomly selected subset of patients (n = 29) with evidence of acute respiratory distress syndrome (ARDS) within 72 hours of worsening of oxygenation. The primary outcome measure was intensive care unit (ICU)-related mortality. Results:Bevacizumab was administered for a median of 9.4 (4-24) days from the onset of symptoms and 2.2 (1-3) days from the day of ICU admission. Bevacizumab-treated patients showed a statistically significant improvement in PF ratio and reduction in radiological severity score. In the bevacizumab group, 13 (44.8%) of 29 patients died in ICU, and in the standard-of-care group, 37 (45.1%) of 82 patients died. The difference in clinical status assessed using the World Health Organization 7-category Ordinary Scale at 28 days between the bevacizumab group and the standard-of-care group was not statistically significant (odds ratio 1.02, 95% confidence interval 0.44-2.4, P = .94). Conclusion:Bevacizumab plus standard care was not superior to standard care alone in reducing mortality and improving clinical outcomes at day 28.
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Coronavirus (COVID-19) is an infectious illness due to serious respiratory trouble. It is impacted numerous humans and has asserted the living expectancy of a greater number of persons from all over the planet. The maturation period of this virus, on typically about 5-6 days but it might also be up to 2 weeks. Throughout this period, the individual may not feel any indications but could still be transmissible. A person could develop this disease if he/ she inhales the virus while a diseased person/ virus carrier within close vicinity sneezes or coughs otherwise tapping an infected place in addition to afterward again his/ her eyes, nose or mouth. To prevent this, the region of the COVID-19 patient must be decontaminated with virucidal disinfectants, such as and 0.05% sodium hypochlorite (NaClO) and ethanol-based products (at least 70%) an optional technique used is UV light sterilization. Ultraviolet (UV) sterilization technology is used to help reduce micro-organisms that can remain on surfaces after basic sprinkling to the minimum amount. The proposed work has established an UV robot or UV bot to perform decontamination in an operating room or in-patients room. Three 19.3-watt UV lights are positioned in a 360-degree circle on the UV bot platform. It used an integrated system based on a microprocessor and a metal frame to aid in navigation in a fixed path to avoid barriers. In addition, a sanitizer dispenser is also included to clean the viral organisms, which is spread through the water droplets of the patient. © 2022 IEEE.
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Objective: Coronavirus disease 2019 may be associated with a white spectrum of post recovery disease complications and health impairment. The objective of this study was to evaluate and assess the different perimeters of pulmonary Function Tests and late outcome of the disease after hospital discharge at 3 and 6 months among the patients admitted with swerve COVID Pneumonia. Method(s): Our analysis consisted of comparison of the FVC at 3 and 6 months after hospital discharge in order to evaluate the disease severity with time. Result(s): A total of 41 hospitalized patients had their Pulmonary Function Tests evaluated >70% of the patients had their FVC <80% at 3 months and >12% had their FVC <80% at 6 months. To study abnormality of spirometry in severe post COVID-19 patients who were discharge from ICU hospital and complete the follow up after one month 3, 6. CONCLUSION(S): In patients who developed moderate to severe pneumonia more than 70% had abnormal FVC at 3 months. These patients were to be identified and treated with optimal management and as a result only 12% of patients had long term impairment in FVC and long term sequel. Copyright © 2022, Anka Publishers. All rights reserved.
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The COVID-19 pandemic has seriously influenced all over the world and affectedthe health of people. In COVID-19 patients, physiological disorders develop like stress, anxiety, and insomnia. This study aimed to investigate sleep quality in COVID-19hospitalized patients of Muzaffarabad, Azad Jammu, and Kashmir. Pittsburg Sleep Quality Index (PSQI) was used to measure sleep quality. PSQI was a self-rated questionnaire scale that contained seven components generated by the combination of 19 individual items. The components included were subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbance, use of sleep medication and, daytime dysfunction. All components score from "0" to "3". The score "0" indicates no problem and the sum of the score 3 indicates severe difficulty. The seven components score was added to yield one global score. A score of 0 to 5 indicated no sleep disturbance and a score of more than 5 indicated sleep disturbance. The mean global score was 8.88+/-4.716 (Mean+/-SD). Current research revealed that 72.2% (n=73) ofpatients who had a global score of 5 or more than 5 had poor sleep quality and 27.8% (n=31) who had a score of less than 5 had good sleep quality (n=31) 13 male patients hada good quality of sleep and 36 male patients experienced a bad quality of sleep. In females, 18 female patients had a good quality of sleep and 37 female patients had a bad quality of sleep current study revealed that there was no association between gender and global PSQI, so sleep quality is independent of gender (chi2 =6.497, P =0.090, df = 3). Thisstudy also showed association between PSQI global score and age group. The 1st age group 15-32 year had a total of 48 patients. The study revealed that 54.16% (n=26) patients had bad sleep quality and 45.83% (n=22) patients had good sleep quality. The second age group from 33 to 55 years in which 76% (n=19) patients had bad sleep quality and 24% (n=06) patients had good sleep quality (r=0.342, P=0.001, df=6) showed that there is high relationship difference between increase group and sleep quality which showed that increase in age group, sleep quality become bad. The 3rd age group was over. Copyright © 2022 Authors. All rights reserved.
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Background: Despite its widespread usage, invasive positive pressure ventilation (IPPV) has a dismal track record in COVID-19 patients with SARDS. Currently, there is a paucity of evidence supporting the usefulness of noninvasive positive pressure ventilation (NIPPV) in the treatment of severe ARDS, as well as a significant risk of aerosol formation in patients with COVID-19 infection. Objective(s): This study aims to assess the efficacy and safety of NIPPV administration to COVID-19 patients. Method(s): The trial included 130 participants with moderate tosevere ARDS based to the Berlin criteria (PaO2/FiO2 ratio of 200mmHg, GCS > 13, respiratory breathing index (RBI) of 105, and no systemic issues). They were treated with NIPPV with awake proaning up to 12 hours per day at a hospital in Muzaffarabad. The addition of a heat and moisture exchanger (HME) and viral/bacterial filters to the expiratory limb of the ventilator circuit represented a minor improvement. Result(s): In an average of six days, the PaO2/FiO2 ratio indicates that the severity of ARDS has improved from moderate/severe to mild in 64 percent of patients. 36 percent of individuals who had a defined airway experienced IPPV or failure of NIV. During the study period, 1 % the of healthcare workers (HCW) were infected with COVID19. The delivery of NIPPV was associated with claustrophobia, nasal crusting, aspiration, and barotrauma (0.7 percent). Conclusion(s): In selected patients, NIV with awake proaning up to 12 hours per day can be employed to give respiratory support without the need for IPPV, hence eliminating the need for IPPV in those patients. However, larger-scale investigations are required to validate our findings. Copyright © 2022 Wolters Kluwer Medknow Publications. All rights reserved.
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It has been two years since vaccination for COVID-19 was launched worldwide. In Pakistan, the vaccination started in the beginning of 2020. Since then, several side effects were reported after vaccination, including soreness of the arm, fever, chills, malaise and diarrhoea. Axillary lymphadenopathy has been found to be associated with several conditions that include autoimmune disorders, infections, malignancy and some idiopathic causes. We present a rare case of a 30-y old female with recent recovery from COVID-19, who developed ipsilateral axillary lymphadenopathy after 15 days of Sinovac vaccination. Ultrasonography was done to confirm the diagnosis and its spread towards breast and cervical region. This case report discusses some key points and recommendations regarding unilateral axillary lymphadenopathy after COVID-19 vaccination. Copyright © 2022 Faculty of Anaesthesia, Pain and Intensive Care, AFMS. All rights reserved.
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Bacterial co-infections and secondary infections are common in respiratory viral infections. Since COVID-19 is a respiratory viral infection proportion of the bacterial infections are high which leads to significant mortality. If these organisms were Multidrug resistance (MDR) the situation become worse. In this mini-review, we analyze the bacterial co-infections& secondary infections, and MDR status in COVID-19 individuals Method: This mini-review was reviewed from articles published in PubMed, Scopus, and Google scholar indexed journals between January 2021 to January 2022. The keywords used for the search were "secondary bacterial infections in COVID-19 individuals", "MDR resistant bacteria in COVID-19", and "case reports on MDR infections in COVID-19 patients" Results: the proportion of bacterial co-infections and secondary infections are varied from region to region as low as 2.5% to 95% reported. MDR strains are high. Conclusion(s): Unnecessary use of antibiotics, prolonged hospital stay, and overburden on the health care system are the main reasons for increasing MDR strains. Copyright © 2022 Japan University of Health Sciences.
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Purpose: Online classes are one of the new innovative study methods that have been popularized in recent times. In the last few years there has been a great shift in the training methods. Online classes play a vital role during the pandemic, but its consequences cannot be ignored. Now-a-days online studies or learning turns out to be more and more practiced. It has become a trend especially during the period of COVID-19 lockdown in 2020 and 2021. It's very convenient as both, student and teacher, as they interact from their own places. Sampling Design: Here the researcher has used the purposive sampling method;data were collected on a sample unit of 100 students pursuing post-graduation from Chennai city. A researcher has used Google Forms for online questionnaire purposes with the intention to study the perception of Postgraduate students in an online class during pandemic situations. Understanding the student's perception using descriptive statistics with Chi-square analysis. The researcher has also used the telephone to collect the real data from the respondents. Finding(s): The researcher was observed significant differences between the fear of lack of knowledge and online offline environment among Male and female post-graduate students. A lot of students have started changing their mindset for work in the unorganized sector they earned money to help their family. Few students only they think differently and concentrate on creative and innovative ideas and also they have joined new courses like NPTEL Swayam. The majority of the students have faced stress and depression in the pandemic situation. Recommendations: This research helped stakeholders of the learning curve like Professors, Parents, Research Scholars, and students. Professors should understand the student's mindset in the pandemic situation. Whenever the teachers scheduled the class they should motivate, encourage and give safety measures. Apart from the syllabus, they are requested to share the real life inspirations. Conclusion(s): Postgraduate students all over the world facing stress and depression because of coronavirus, pandemic situations, lockdown and online classes. The researcher discovered that parents, management of the institution, and professors should take care of the future of all the students. We should always encourage, motivate, and proper guidance whenever they feel very sad and we try to reduce negative thoughts from the students' mind. Management of the Institution should insist that nothing is permanent in this world. Everything will change. Copyright © 2022 Wolters Kluwer Medknow Publications. All rights reserved.
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Introduction: Nipah virus (NiV) was reported for the first time from the Kampung Sungai Nipah village of Malaysia in 1998. Since then, there have been multiple outbreaks, all of them in South- and South-East Asia. According to the World Health Organization (WHO), up to 75% of Nipah infections were proven to be fatal. Nipah virus belongs to the group of Biosafety Level-4 pathogen associated with high case fatality rate (40-75%). Methodology:According to the PRISMA guidelines for 2020, we searched in four medical databases (PubMed, Google Scholar, EMBASE and Scopus) and selected relevant studies from the past twenty years till November 2021. Review:Nipah virus was first detected in Malaysia's Kampung Sungai Nipah in 1998. By May 1999, the Malaysia Ministry of Health in association with the Centers for Disease Control (CDC) reported a total of 258 cases with a case fatality rate of almost 40%. Nipah in Kozhikode:Experts from the Pune Institute and Bhopal's National Institute of High Security Animal Diseases had collected Bat samples from Pazhoor in Chathamangalam gram panchayat (where a 12-year-old died due to Nipah infection on September 5 carried antibodies of the virus). All Indian outbreaks have seen person-to-person transmission. The virus found in Kerala differed from those two variants in terms of genetic structure. It also differed by 1.96% from the Bangladesh variant. The difference with the Malaysian variant was 8.42%. While PCR is the most sensitive technique for diagnosing active NiV infection, NiV-specific IgM ELISA offers a serological option when PCR is not available. Conclusions:Understanding the fruit bat ecology, NiV illness seasonality, and the transmission risk of various intermediate species requires a One Health approach. The danger of reintroduction into animal or human populations cannot be handled without a thorough understanding of the wildlife reservoir.
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The world is infected from the deadliest pandemic disease humankind has ever seen. Several medical practitioners have been encountered with the corona virus and are constantly losing their lives in the fight. Hence, the main objective of this research work is to characterize the clinical features of the patients and construct a novel dataset for machine learning to classify them accurately prior to treatment. The positive patients can be identified on many characteristics and the principle data for this research is considered on the basis of the exploratory analysis done on the various risk factors that is also associated with the mortality in the hospitals. As an outcome, this article presents a supervised machine learning model incorporating the insights, symptoms and classification of the corona virus infected person. The proposed model and the dataset are tested against six well known classifiers on various levels of cross folding and percentage splits. The proposed dataset is also tested against the actual patient records and was found that the model accurately categorizes them prior to their treatment. The experimental results for proposed techniques showed higher performance and better accuracy further creating an impact on then identification of corona virus patients.
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Background: Understanding the burden of surgical site infection (SSI) requires comprehensive, reliable and comparable data. However, many hospitals do not routinely collect information on wound healing after the patient leaves hospital. Aim: To evaluate five post-discharge surveillance strategies that collect patient/carer reported outcomes on wound healing following adult and paediatric surgery. Method: Between March 2020 and February 2021, colleagues from five specialist hospitals in England collaborated to collect baseline and compliance data for the different methods of postdischarge surveillance. The five methods included were telephone follow-up;postal questionnaires;postal questionnaires and contacting non-responders by telephone to asking patients to install a postoperative app on their personal smartphone (Medopad, Huma) and using a SSI surveillance text link, which did not need to be installed (Isla, Islacare Ltd). Results: Overall, 1432 patients out of 2116 patients provided information about their wound after discharge. The group of patients who were asked to install an app on their smart device had the lowest return rate for information on their wound, while the system that used a text link and did not need to be installed had one of the highest return rates. Conclusion: Understanding baseline practice and evaluating different methods of discharge surveillance may help to drive improvement in this area. Our early findings suggest that in practice, a SSI surveillance approach using a text link and photos, such as Isla, which is used in hospital before discharge by staff and post-discharge by patients warrants further attention.
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Autism spectrum disorder (ASD) affects one out of every 54 children, according to statistics. In this paper, we use the Raspberry Pi to build a system that evaluates the efficiency of a Smart monitor for helping children with Autism Spectrum Disorder (ASD) learn and improve their quality of life. Many autistic children are very motivated and interested in Computers and smart monitors. Assistive technology systems like these encourage children with autism to communicate more. Our proposed framework demonstrates that it can support children with ASD by teaching them new skills. It helps them in making choices, respond, and tell parents what they are interested in, identify their needs, think, and maybe even feel. We implement and evaluate the performance of a new system based on Internet of Things (IOT) for supporting learning and improving the quality of life for children with Autism Spectrum Disorder (ASD). Moreover using this System the ASD kids can easily learn any Subjects with ease. Strategies for supporting the large number of students with autism spectrum disorder (ASD) in the area of literacy © 2021 IEEE.
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Background:As the knowledge about the risk factors and treatment options of COVID 19 is still evolving, we attempted to study the clinical characteristics, comorbidities and laboratory markers in 98 COVID nonsurvivors from a tertiary care centre in Tamilnadu. Methods: In this retrospective observational study, we included 98 cases of laboratory confirmed COVID non survivors in Velammal medical College Hospital and Research Institute, Madurai between June 20, 2020 to October 10, 2020. Information on demography, clinical features, risk factors, laboratory and radiological findings and treatment details was extracted from medical records. Results:A total of 98 patients (Median age 63 years, 73.5% males) were included. Comorbidities were present in nearly 80% of pa- tients, with hypertension being the most common comorbidity, followed by diabetes and coronary heart disease. The most common symptoms on admission were fever, cough and breathlessness. Biochemical and hematological markers taken at the time of admis- sion and 24 hours before death were analysed. Initial laboratory findings of non-survivors demonstrated higher WBC count, neutro- philia, lymphopenia, raised AST, ALT, ferritin, IL6 and procalcitonin. Throughout hospitalization, there was consistent rise in inflamma- tory markers and rise in blood urea and low serum albumin was observed. Low molecular weight Heparin, steroids, antiviral fabipiravir, azithromycin and noninva- sive ventilation was given in 70% patients. Patients who were intubated were ad- ministered tocilizumab in addition to the above treatment. Mean days of hospitali- zation was 9 days. Average survival time was 13 days. Most common cause of death was ARDS and respiratory failure. [Formula presented] Conclusions:This retrospective study identified the important laboratory markers which predicts mortality in adults. Progressive high neutrophil count, lymphocyto- penia, low serum albumin, elevated ALT, blood urea, raised LDH, D-dimer, ferritin and procalcitonin are significantly associated with mortality
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The technological advances made possible by the Internet, coupled with the unforeseen critical circumstances set in motion by the Covid-19 pandemic, have greatly increased the generation and transmission of medical images every day. Medical image transmission over an unsecured public network threatens the privacy of sensitive patient information. We have, in this paper, designed a new secure color medical image encryption algorithm based on binary plane decomposition, DNA (deoxyribonucleic acid) computing, and the chaotic Rössler dynamical system. At first, a bit-by-bit swap is performed on twenty four binary planes of the input image and encoded using DNA encoding rules. Thereafter, the Rössler system is used to modify the pixel values of the encoded image, which is subsequently decoded. Finally, the ciphered image is obtained by pixel-by-pixel permutation using position sequences. An innovative approach is used to compute keys from the color components of the input image. Extensive performance experiments of the proposed technique is conducted with metrics such as key sensitivity, key space, correlation coefficients (horizontal, diagonal and vertical directions), histograms, information entropy, number of pixel changes rate (NPCR), information entropy, unified average changing intensity (UACI), and encryption time. Comparative analyses have demonstrated that the proposed algorithm is fast, robust and competitive. © 2022, Tech Science Press. All rights reserved.
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Aim: Covid infection after first and second dose of vaccination was assessed in comparison to unvaccinated SARS-CoV-2 infection patients. Methodology: Patients were divided into two groups: Those who had not got any immunizations and those who had received vaccines that were prescribed. Individuals who have taken second dose of either the mRNA vaccine or the viral vector vaccine and have a positive COVID-19 within 14 days of receiving their second dose are deemed fully immunised. Results: Among 180 patients, the males were 75% and 25% was females. In our study, 16.7% (30/180) patients still suffered from COVID-19 despite of the fact that they were vaccinated, but the ratio of immune patients was greater i.e. 83.3% (150/180).The severity of the symptoms in vaccinated patients was much lesser and in some cases almost nil. 144/180 (80%) patients did not suffer from any severe symptoms after vaccination. 33/180 (18.3%) patients showed moderate symptoms while 3/180 (1.7%) showed severe symptoms. In the analysis of severity of symptoms of non vaccinated patients, 70% (126/180) showed severe symptoms, 25% (45/180) showed moderate and 5% (9/180) patients showed low symptoms. Conclusion: People without vaccination have more severe symptoms whereas COVID patients with vaccination had a reduced mortality rate and milder symptoms.
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Aim: To study the severity of symptoms, rates of mortality and morbidity in COVID patients with and without previous pulmonary pathology. Methodology: The cohort study consisted of 244 patients and nearly all the individuals had underlying diseases. Data collection forms included demographic data, medical history, history of exposure to infection, symptoms, signs, laboratory findings, HRCT results, treatment measures especially history of corticosteroid use, and duration of illness. Results: In 244 patients, 180 patients were having the pulmonary pathology and other 64 were having no pulmonary pathology. 77.2% (139/180) of the patients showed severe symptoms in the previous pulmonary pathology while 21.8% (10/64) showed severe symptoms in the group with no pulmonary pathology. 16.1% (29/180) patients died because of COVID and were also having pulmonary pathology. While 10.9% (7/64) patients died in the group having no pulmonary pathology. Conclusion: In this study, 16.1% patients died of COVID with pulmonary pathology. While 10.9% patients died having no pulmonary pathology. 77.2% of the patients showed severe symptoms with previous pulmonary pathology while 21.8% showed severe symptoms with no pulmonary pathology.
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How should empirical researchers conduct controlled, remote 'lab' studies in the uncontrolled, noisy conditions of each participant's own home? Volatility in participant home environments, hardware, internet connection, and surrounding distractions takes the 'controlled' out of controlled studies. This paper recounts our in-The-Trenches mitigations for designing and conducting two complex controlled studies under COVID, in which participants, from home, interactively localized faults in an AI system. The studies with our COVID-era mitigations in 5 categories-Privacy/Security, Data Collection, Control, Technology Issues, Payment-ultimately produced crisp results beyond what we thought possible under such uncontrolled circumstances. © 2021 IEEE.