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The conventional methods used for the diagnostics of viral infection are either expensive and time-consuming or not accurate enough and dependent on consumable reagents. In the presence of pandemics, a fast and reagent-free solution is needed for mass screening. Recently, the diagnosis of viral infections using infrared spectroscopy has been reported as a fast and low-cost method. In this work a fast and low-cost solution for corona viral detection using infrared spectroscopy based on a compact micro-electro-mechanical systems (MEMS) device and artificial intelligence (AI) suitable for mass deployment is presented. Among the different variants of the corona virus that can infect people, 229E is used in this study due to its low pathogeny. The MEMS ATR-FTIR device employs a 6 reflections ZnSe crystal interface working in the spectral range of 2200-7000 cm-1. The virus was propagated and maintained in a medium for long enough time then cell supernatant was collected and centrifuged. The supernatant was then transferred and titrated using plaque titration assay. Positive virus samples were prepared with a concentration of 105 PFU/mL. Positive and negative control samples were applied on the crystal surface, dried using a heating lamp and the spectrum was captured. Principal component analysis and logistic regression were used as simple AI techniques. A sensitivity of about 90 % and a specificity of about 80 % were obtained demonstrating the potential detection of the virus based on the MEMS FTIR device. © 2023 SPIE.
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An innovative tool in the field of e-learning, augmented reality applications help students learn more quickly inside of online classrooms. Due to the rapid spread of COVID-19, conventional methods of instruction had to be put on hold at the outset of the pandemic. In light of the recent COVID-19 epidemic in Asia, this research explores college students' perspective on online education using augmented reality software. Based on the idea of planned behavior, this research developed a conceptual model to investigate the attitudes and intentions of college students about the use of an augmented reality app for course-related e-learning. Information from 135 Asian college students was analyzed using structural equation modeling. Students' attitudes and a sense of agency over their own actions had the greatest impact on their propensity to embrace augmented reality applications for e-learning, whereas subjective norms had a very little role, as seen by the study's findings. These findings validate students' interest in and acceptance of cutting-edge education methods like augmented reality applications. © 2023 NSP Natural Sciences Publishing Cor.
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The aim of this study is to assess the influence of living in nursing homes on COVID-19-related mortality, and to calculate the real specific mortality rate caused by COVID-19 among people older than 20 years of age in the Balaguer Primary Care Centre Health Area during the first wave of the pandemic. We conducted an observational study based on a database generated between March and May 2020, analysing COVID-19-related mortality as a dependent variable, and including different independent variables, such as living in a nursing home or in the community (outside nursing homes), age, sex, symptoms, pre-existing conditions, and hospital admission. To evaluate the associations between the independent variables and mortality, we calculated the absolute and relative frequencies, and performed a chi-square test. To avoid the impact of the age variable on mortality and to assess the influence of the "living in a nursing home" variable, we established comparisons between infected population groups over 69 years of age (in nursing homes and outside nursing homes). Living in a nursing home was associated with a higher incidence of COVID-19 infection, but not with higher mortality in patients over 69 years of age (p = 0.614). The real specific mortality rate caused by COVID-19 was 2.270/00. In the study of the entire sample, all the comorbidities studied were associated with higher mortality; however, the comorbidities were not associated with higher mortality in the infected nursing home patients group, nor in the infected community patients over 69 years of age group (except for neoplasm history in this last group). Finally, hospital admission was not associated with lower mortality in nursing home patients, nor in community patients over 69 years of age.
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Purpose: The present study aimed to study the immunogenicity of the ChAdOx1 nCoV-19 vaccine in patients with hematologic malignancies. Materials and Methods: This prospective cohort study of hematology patients aimed to evaluate their antibody levels against the receptor-binding domain of the severe acute respiratory syndrome coronavirus 2 spike protein and seroconversion rates following two doses of the ChAdOx1 nCoV-19 vaccine. Between June and July 2021, we enrolled 61 patients and included 44 patients in our analysis. Antibody levels were assessed 8 and 4 weeks after the first and second injections, respectively, and compared with those of a healthy group. Results: Eight weeks after the first dose, the geometric mean antibody level was 1.02 binding antibody units (BAU)/mL in the patient group and 37.91 BAU/mL in the healthy volunteer group (p<0.01). Four weeks after the second dose, the geometric mean antibody level was 9.44 BAU/mL in patients and 641.6 BAU/mL in healthy volunteers (p<0.01). The seroconversion rates 8 weeks after the first dose were 27.27% and 98.86% in the patient and healthy volunteer groups, respectively (p<0.001). The seroconversion rate 4 weeks after the second dose was 47.73% in patients and 100% in healthy volunteers. Factors leading to lower seroconversion rates were rituximab therapy (p=0.002), steroid therapy (p<0.001), and ongoing chemotherapy (p=0.048). Factors that decreased antibody levels were hematologic cancer (p<0.001), ongoing chemotherapy (p=0.004), rituximab (p<0.001), steroid use (p<0.001), and absolute lymphocyte count <1,000/mm3 (p=0.009). Conclusion: Immune responses were impaired in individuals with hematologic malignancies, particularly patients undergoing ongoing therapy and B-cell-depleting therapy. Additional vaccinations should be considered for these patients, and further investigated.
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Rapid improvements in healthcare services and affordable IoT in the past decade have been a big help in dealing with the issue of fewer medical facilities. Unfortunately, some people still choose not to get immunized, thus fear and reluctance remain a part of human existence despite widespread vaccination initiatives. Therefore, it is important to screen this group of potential spreaders as soon as possible since they may become infected and transfer viruses to others. It is in this context that the pharmaceutical sector might benefit from highly developed health monitoring systems. This work has created and tested a multi-node architecture based on Fog computing to perform real-time initial screening and recording of such individuals, therefore addressing the demand and reducing the unpredictability of the scenario. In addition to capturing photographs of the subject's face, the suggested device also recorded the subject's current body temperature and GPS locations. As an added bonus, the suggested system could upload information to a remote server over the internet. To test the viability of the proposed system, a thorough examination of the existing work environment was carried out, including implementation and evaluations. From the results of the statistical analysis, it was seen that the suggested IoT Fog-enabled ecosystem may be put to good use. © 2023 IEEE.
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The study of this review focus on effective herbal medicine against COVID-19. There have been many such plants on which a lot of research has been done earlier, and these have been very good for health as we know that the current situation of the whole world is very serious with the novel COVID-19 virus epidemic. Hence, people consume a lot of herbal medicine to increase their immunity, such as kadha (brewing), and it is also very effective against this viral infection. If we take brewing in the proper dose, research should be done from clinical trials. We have been taking many medicines since old times and have been doing research on them which is Antiviral and useful in different types of infection caused by bacteria, viruses, microbes, etc. The plant's diversity included their chemical constituents, showing the promise of their therapeutic level against the antiviral activity, without any toxicity with plasma concentration. Many plants show effectively against viral infections that are Flavonoids, Glycosides, polyphenols, alkaloids, etc.. Still, any clinical trials on humans do not prove their proper research on them, but the Chinese system of medicine claimed that Traditional Chinese medicine improves the COVID-19 patient. According to this review, we aim to collate data of plants the various large in the quantity of natural active constituents from individual medicinal plant species that may have potential therapeutic efficacy. The continuing development of novel antiviral drugs needs to isolate and synthesize more new active constituents. © 2021 by the authors.
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The recent pandemic, covid-19 has largely affected people's lives, health, and productivity. The first case of Covid-19 was recorded on December 31, 2019, in Wuhan, China. Since then, the number of cases has increased exponentially, and subsequently, numerous precautions have been taken to prevent and cure the virus. By May 26, 2021, totally, 168 million cases were reported worldwide, with 3.49 million deaths, and the pandemic is currently underway, with people continuing to get affected and fighting for their lives from this deadly virus. The World Health Organization (WHO) has also released various precautions and vaccines to combat the pandemic, but these are insufficient to reduce the number of infected cases or save people's lives. The proposed research study discusses about the utilization of artificial intelligence (AI), machine learning (ML), and data science techniques for gaining a better understanding of covid-19 virus. This technological advancement can easily make proper judgments about covid-19, as well as the predictions on confirmed & recovered cases and deaths were made by using this technology. The datasets also include previous and current information about covid-19. The proposed research study also discusses about a tool called "Prophet.” Prophet is a Facebook open-source tool, which uses the Sklearn model API. The proposed study initially creates a prophet instance and then use its fit and predict methods. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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Background: Mass vaccination serves as an effective strategy to combat the COVID-19 pandemic. Vaccine hesitancy is a recognized impediment to achieving a vaccination rate necessary to protect communities. However, solutions and interventions to address this issue are limited by a lack of prior research. Methods: Over 200 patients from 18 Michigan counties participated in this study. Each participant received an initial survey, including demographical questions and knowledge and opinion questions regarding COVID-19 and vaccines. Participants were randomly assigned an educational intervention in either video or infographic format. Patients received a post-survey to assess changes in knowledge and attitudes. Paired sample t-tests and ANOVA were used to measure the effectiveness of the educational interventions. Participants also elected to complete a 3-month follow-up survey. Results: Patients showed increased knowledge after the educational intervention in six out of seven COVID-19 topics (p < 0.005). There was increased vaccine acceptance after the intervention but no difference in the effectiveness between the two intervention modalities. Post-intervention, more patients believed in CDC recommendations (p = 0.005), trusted the vaccine (p = 0.001), believed the vaccines had adequate testing (p = 0.019), recognized prior mistreatment in the medical care system (p = 0.005), agreed that a source they trust told them to receive a vaccine (p = 0.015), and were worried about taking time off of work to get a vaccine (p = 0.023). Additionally, post-intervention, patients were less concerned about mild reactions of the virus (p = 0.005), the rapid development of the vaccines (p < 0.001), and vaccine side effects (p = 0.031). Data demonstrated that attitude and knowledge improved when comparing pre-educational intervention to follow-up but decreased from post-intervention to follow-up. Conclusion: The findings illustrate that educational interventions improved COVID-19 and vaccine knowledge among patients and that the knowledge was retained. Educational interventions serve as powerful tools to increase knowledge within communities and address negative views on vaccination. Interventions should be continually utilized to reinforce information within communities to improve vaccination rates.
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COVID-19 , Pandemics , Humans , Prospective Studies , Michigan , COVID-19/prevention & control , VaccinationABSTRACT
Background: Coronavirus disease 2019 (COVLD-19), the global pandemic that has spread throughout the world, is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Given the limited scientific evidence on the manifestations and potential impact of this virus on pregnancy, we decided to report this case. Case presentation: The patient was a 38 year-old Iranian woman with a triplet pregnancy and a history of primary infertility, as well as hypothyroidism and gestational diabetes. She was hospitalized at 29 weeks and 2 days gestational age due to elevated liver enzymes, and finally, based on a probable diagnosis of gestational cholestasis, she was treated with ursodeoxycholic acid. On the first day of hospitalization, sonography was performed, which showed that biophysical scores and amniotic fluid were normal in all three fetuses, with normal Doppler findings in two fetuses and increased umbilical artery resistance (pulsatility index [PI] > 95%) in one fetus. On day 4 of hospitalization, she developed fever, cough and myalgia, and her COVID-19 test was positive. Despite mild maternal symptoms, exacerbated placental insufficiency occurred in two of the fetuses leading to the rapid development of absent umbilical artery end-diastolic flow. Finally, 6 days later, the patient underwent cesarean section due to rapid exacerbation of placental insufficiency and declining biophysical score in two of the fetuses. Nasopharyngeal swab COVID-19 tests were negative for the first and third babies and positive for the second baby. The first and third babies died 3 and 13 days after birth, respectively, due to collapsed white lung and sepsis. The second baby was discharged in good general condition. The mother was discharged 3 days after cesarean section. She had no fever at the time of discharge and was also in good general condition. Conclusion(s): This was a complicated triplet pregnancy, in which, after maternal infection with COVID-19, despite mild maternal symptoms, exacerbated placental insufficiency occurred in two of the fetuses, and the third fetus had a positive COVID-19 test after birth. Therefore, in cases of pregnancy with COVID-19 infection, in addition to managing the mother, it seems that physicians would be wise to also give special attention to the possibility of acute placental insufficiency and subsequent fetal hypoxia, and also the probability of vertical transmission.Copyright © 2022 Goldstein and Associates. All rights reserved.
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Background: Bacterial coinfection contributes to increase morbidity and morbidity of viral respiratory infections and may lead to fatal outcome during its course of illness. Aims and Objectives: The main objective of this study was to determine the bacteriological profile of COVID-19 patients admitted in hospital, their antibiotic susceptibility, and their association with severity. Materials and Methods: The present study was retrospective observational cross-sectional study of all patients admitted for COVID-19 at Gandhi Medical College and Hamidia Hospital, Bhopal (MP) between (March 2020 and December 2020). Demographic, comorbid conditions, and microbiological data were compared HBD and intensive care unit (ICU) admissions and role secondary coinfection in severity and mortality. Results: Thirty percentages of percent of patients showed bacterial growth, Staphylococcus aureus was most common, followed by Pseudomonas aeruginosa. Mean±SD of age was 43.6±21.6. Antibiotic resistance of cefoxitin, cotrimoxazole, and azithromycin was seen in maximum Gram-positive growth, whereas sensitivity for linezolid and gentamicin was present in 10--16% cases. Highest antibiotic resistance in Gram-negative growth was seen for ceftozidime, amikacin, imipenem, and meropenem, whereas sensitivity of colistin antibiotic was highest in Gram-negative growth. Conclusion: Coinfection rates increase in patients admitted to the ICU, despite frequent prescription of broad-spectrum antibiotics. Infectious diseases practitioners carry the burden of life-saving and provide for societal trust that is effective antibiotic therapy in the face of these changes. With a growing body of evidence supporting short-course, antimicrobial therapy "Shorter Is Better" should be the new mantra. [ABSTRACT FROM AUTHOR] Copyright of Asian Journal of Medical Sciences is the property of Manipal Colleges of Medical Sciences 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 abstract 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 abstract. (Copyright applies to all Abstracts.)
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Coronavirus disease 2019 (COVID-19) is a rising respiratory sickness. It causes harsh pneumonia and is considered to cover higher collisions in the healthcare domain. The diagnosis at an early stage is more complex to get accurate treatment for reducing the stress in the clinical sector. Chest X-ray scan is the standard imaging diagnosis test employed for pneumonia disease. Automatic detection of COVID-19 helps to control the community outbreak but tracing this viral infection through X-ray results in a challenging task in the medical community. To automatically detect the viral disease in order to reduce the mortality rate, an effective COVID-19 detection method is modelled in this research by the proposed manta-ray multi-verse optimization-based hierarchical attention network (MRMVO-based HAN) classifier. Accordingly, the MRMVO is the incorporation of manta-ray foraging optimization and multi-verse optimizer. Based on the segmented lung lobes, the features are acquired from segmented regions in such a way that the process of COVID-19 detection mechanism is carried out with the features acquired from interested lobe regions. The proposed method has good performance with the measures, such as accuracy, true positive rate and true negative rate with the values of 93.367, 89.921 and 95.071%. [ABSTRACT FROM AUTHOR] Copyright of Computer Journal is the property of Oxford University Press / USA 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 abstract 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 abstract. (Copyright applies to all Abstracts.)
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Background: As of June 2021, the United States had been greatly affected by the global COVID-19 pandemic. This study aims to explore self-care measures during the pandemic, the impact of the pandemic, and attitudes toward COVID-19 vaccination among residents living in rural Alabama. Methods: Focus group interviews were conducted in designated local communities in the rural areas of Alabama in September 2020. Recruited from a pool of individuals living in a local community, focus group members voluntarily participated in this study after providing informed consent. A semi-structured interview revolved around the following topics: (1) the impact of the pandemic on participants' health and health care access, (2) self-care activities during the the pandemic, and (3) opinions on COVID-19 vaccination. Results: Three major themes and corresponding subthemes were identified: (1) self-care activities during the pandemic with four subthemes: physical health care, relationships with others, hygiene maintenance, and keeping informed;(2) impact of the pandemic with two subthemes: negative mental health and online services and activities;and (3) attitude toward COVID-19 vaccine with three subthemes: perceived challenges, suggestions about accessibility, and willingness to be vaccinated. Conclusion: Our findings warrant joint actions and efforts from policy makers and health care practitioners to engage in strategic intervention mapping to promote positive health behaviors and ultimately reduce COVID-19 transmission, number of cases, and adverse outcomes. For example, health care providers and practitioners may offer psychosocial services and regular mental health checkups. Increased infrastructure (e.g., funding and technology) is pivotal for providing online health services. (PsycInfo Database Record (c) 2023 APA, all rights reserved)
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The recent pandemic, covid-19 has largely affected people's lives, health, and productivity. The first case of Covid-19 was recorded on December 31, 2019, in Wuhan, China. Since then, the number of cases has increased exponentially, and subsequently, numerous precautions have been taken to prevent and cure the virus. By May 26, 2021, totally, 168 million cases were reported worldwide, with 3.49 million deaths, and the pandemic is currently underway, with people continuing to get affected and fighting for their lives from this deadly virus. The World Health Organization (WHO) has also released various precautions and vaccines to combat the pandemic, but these are insufficient to reduce the number of infected cases or save people's lives. The proposed research study discusses about the utilization of artificial intelligence (AI), machine learning (ML), and data science techniques for gaining a better understanding of covid-19 virus. This technological advancement can easily make proper judgments about covid-19, as well as the predictions on confirmed & recovered cases and deaths were made by using this technology. The datasets also include previous and current information about covid-19. The proposed research study also discusses about a tool called "Prophet.” Prophet is a Facebook open-source tool, which uses the Sklearn model API. The proposed study initially creates a prophet instance and then use its fit and predict methods. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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An impending branch of computer science is artificial intelligence. It plays an important role in the construction of smart machines that are capable of performing sophisticated operations. One of the key characteristics of artificial intelligence is its ability to make decisions on its own and rationalize the solution, helping us to achieve a certain goal. Our human race has faced many threats in the form of epidemics and pandemics, which have proved to be almost incurable in the past. Nevertheless, science and its evolving technologies have given us some hope to fight such threats. One such pandemic that our human race is facing in the current times is COVID-19. This deadly disease is rapidly spreading across the whole world endangering the lives of humans. Amid the chaos, we desperately need to stop the spread, or at least take adequate counter-active measures to detect this virus at its early stage. Deep learning, a subset of artificial intelligence provides many models which helps in the automation of the task of detecting viruses in humans mainly with the help of image processing. In detecting COVID-19, deep learning is a breakthrough, which has helped us in our proposed system. This system makes use of chest radiographs (CXR) to detect the presence of the virus in the human body thereby lowering the risk of spread which is fairly high in manual detection methods. The CXRs are one of the most common imaging tests in the clinical field, which helps in detecting the presence of cold, cough, shortness of breath in the lungs, and so on. The proposed model is very efficient when it comes to detecting problems in the lungs with the help of image processing. We propose an improvised neural network derived from the Convolutional Neural Network which works similar to the human brain structure to detect and process the CXR images efficiently and at faster rates. The neural network mimics the functioning of the brain, where self-learning and decision making are its key features. The image data sets are a collection of CXR images which have a RGB value of 1. This approach is proven to be safer and better than the manual testing methods that are currently deployed. As the traditional methods for detecting COVID-19 virus is tedious, and not fairly accurate, automating this task can help in giving accurate results with reduced risk of spread of disease through physical contact. © 2022 Scrivener Publishing LLC.
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OBJECTIVE: To analyze the effects of in-person attendance at an academic conference held during the Covid-19 pandemic on the health of the attendees, as assessed based on symptoms such as fever and cough attributed to infection with the Covid-19 virus. METHODS: A questionnaire was used to survey the members of the Japan Society of Obstetrics and Gynecology (JSOG) about their health during the period from August 7 to August 12, 2022, after the 74th Annual Congress of the JSOG, which was held August 5 to 7. RESULTS: Our survey yielded responses from 3054 members (1566 of whom had attended the congress in person and 1488 of whom had not attended in person); 102 (6.5%) of the in-person attendees and 93 (6.2%) of the people who did not attend in person reported problems with their health. No statistically significant difference was found between these two groups (p = 0.766). In a univariate analysis of factors affecting the presence of health problems, attendees with age ≥60 years had significantly fewer health problems than attendees who were in their 20s (odds ratio: 0.366 [0.167-0.802; p = 0.0120]). In a multivariate analysis, attendees who had received four vaccine shots had significantly fewer health problems than attendees who had received three shots (odds ratio: 0.397 [0.229-0.690, p = 0.0010]). CONCLUSION: Congress attendees who took precautions at the congress to avoid being infected and who had a high vaccination rate did not develop significantly more health problems associated with in-person attendance at the congress.
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COVID-19 , Female , Humans , Middle Aged , Pregnancy , Odds Ratio , Pandemics , SARS-CoV-2 , Surveys and Questionnaires , Congresses as TopicABSTRACT
Objectives: Patients with hematological malignancies have a high risk of mortality from coronavirus disease 2019 (COVID-19). This study aimed to investigate the impact of COVID-19 on mortality rates in patients with various hematological malignancies and to determine risk factors associated with all-cause mortality. Methods: A multicenter, observational retrospective analysis of patients with hematological malignancies infected with COVID-19 between July 2020 and December 2021 was performed. Demographic data, clinical characteristics, and laboratory parameters were recorded. Patients were grouped as non-survivors and survivors. All-cause mortality was the primary outcome of the study. Results: There were 569 patients with a median age of 59 years. Non-Hodgkin lymphoma (22.0%) and multiple myelomas (18.1%) were the two most frequent hematological malignancies. The all-cause mortality rate was 29.3%. The highest mortality rates were seen in patients with acute myeloid leukemia (44.3%), acute lymphoid leukemia (40.5%), and non-Hodgkin lymphoma (36.8%). The non-survivors were significantly older (p<0.001) and had more comorbidities (p<0.05). In addition, there were significantly more patients with low lymphocyte percentage (p<0.001), thrombocytopenia (p<0.001), and high CRP (p<0.001) in the non-survived patients. Age ≥ 65years (p=0.017), cardiac comorbidities (p=0.041), and continuation of ongoing active therapy for hematological cancer (p<0.001) were the independent risk factors for the prediction of mortality. Conclusions: In patients with hematological malignancies, coexistent COVID-19 leads to a higher mortality rate in elderly patients with more comorbidities. Acute myeloid and lymphoid leukemia and non-Hodgkin lymphoma have the highest mortality rates. Older age, cardiac diseases, and continuation of ongoing active therapy for hematological cancer are the independent risk factors for mortality in hematological malignancy patients with COVID-19.
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Aims The success of COVID-19 vaccination depends on public acceptance of the vaccine. It is necessary to evaluate the factors affecting vaccine acceptance to increase the acceptance of vaccination. The current study aimed to determine the relationships between the three components of the COM-B (capability, motivation, and opportunity) model and the explanatory domains of each component. Instrument & Methods In this cross-sectional study, 1102 adults aged 18 years and older were selected through multi-stage sampling and received an online questionnaire on the WhatsApp platform in February 2021. Structure equation modeling was used to investigate the factors affecting vaccine acceptance. Findings Of the 1102 respondents, 938 respondents (85.1%) wanted to get vaccinated. The main indicators for the COM-B components were "behavioral regulation”(capability), "subjective norms and social support” (opportunity) and "social role” (motivation). Opportunity strongly predicted motivation (93%) and Covid-19 vaccine acceptance (74%). Motivation and capability were mediator for opportunity on vaccine acceptance. Conclusion Providing environmental and interpersonal conditions by creating capability and motivation in people increases vaccine acceptance. © 2022, the Authors.
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South Africa is one of the countries in Africa that has a high COVID-19 virus infection rate. The government of South Africa introduced the COVID Alert SA App, a contact tracing mobile application (App), to reduce the spread of the COVID-19 virus. This paper reports on the challenges users experienced when using the COVID Alert SA App. Using the design-reality gap model, the study analyzed online user reviews of the App and government reports. The qualitative data were analyzed using thematic analysis to highlight insights on the challenges of using the COVID Alert SA App. The findings indicate that public awareness was a major limitation of the App, amongst others, including a lack of trust relating to privacy and security when using the App, and a lack of technical support. The insights can be useful for developers, researchers, policymakers, and other stakeholders to improve the adoption and use of the contact tracing App to reduce the spread of the COVID-19 virus. [ FROM AUTHOR]
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Objective: Many neurological symptoms due to central nervous system, peripheral nervous system and musculoskeletal system damage have been reported in more than a third of patients with coronavirus disease-2019 (COVID-19). Although optic neuritis has been reported in patients with COVID-19, they are extremely rare. The aim of this study was screening optic nerve involvement in COVID-19 with visual evoked potential (VEP) in asymptomatic patients without a history of visual impairment. Materials and Methods: Pattern reversal VEP measurements were made in 101 adult patients with COVID-19 without a history of visual impairment after they completed COVID-19 treatments and the quarantine period. VEPs were recorded with the 4-channel electromyography-evoked device in a dark room. P100 latencies and amplitudes were analyzed by the same neurologist. Results: A total of 34 (33.7%) patients had P100 latency prolongation. There was no significant difference in terms of gender, age or outpatient/inpatient treatment status. There was no significant correlation between the time of polymerase chain reaction diagnosis and VEP values. Conclusion: Contrary to previous studies, asymptomatic optic nerve involvement after COVID-19 was detected by VEP measurements. Prolongation of P100 latency shows the probable linkage between COVID-19 virus and angiotensin converting enzyme 2 receptors in human eyes.
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T1he Covid-19 virus pandemic has resulted in a fairly large scale of sufferers and deaths. For more than a year, Covid-19 Pandemic in Indonesia has killed more than 45,000 people. In order to prevent the spread of Covid-19 virus, it surely requires public policies issued at the national and regional levels. Through a normative research approach and covered by the Post-Positivism paradigm, it shows that public policies issued nationally and regionally are needed in synergy and integration to be able to regulate and determine so that citizens become obedient and together overcome the Covid-19 Virus Pandemic. There are two ways to deal with the Covid-19 virus, namely by using penal and using non-penal facilities. Both facilities are carried out together so that they are integrative and provide maximum results. © The Authors, published by EDP Sciences.