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In this article, we present a Markov Bernoulli Lomax (MB-L) model, which is obtained by a countable mixture of Markov Bernoulli and Lomax distributions, with decreasing and unimodal hazard rate function (HRF). The new model contains Marshall- Olkin Lomax and Lomax distributions as a special case. The mathematical properties, as behavior of probability density function (PDF), HRF, rth moments, moment generating function (MGF) and minimum (maximum) Markov-Bernoulli Geometric (MBG) stable are studied. Moreover, the estimates of the model parameters by maximum likelihood are obtained. The maximum likelihood estimation (MLE), bias and mean squared error (MSE) of MB-L parameters are inspected by simulation study. Finally, a MB-L distribution was fitted to the randomly censored and COVID-19 (complete) data. © 2023 by the authors.
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Background: Laboratory biomarkers are amongst the best imperative predictors of disease outcomes in hospital-admitted COVID-19 patients. Although data is available in this regard at a global level, there is a paucity of information in Ethiopia. Thus, this study aimed to assess the laboratory biomarkers association with death among COVID-19 patients in Ethiopia. Methods: A health facility-based longitudinal study was conducted from 2020 to 2022 among RT-PCR-confirmed COVID-19 patients admitted and on treatment follow-up at COVID-19 treatment hospitals in Addis Ababa. A robust Poisson regression model was fitted to assess the association between demographic, clinical, and laboratory factors and death. Significance was determined at p<0.05, and variables with p < 0.15 in bivariate analyses were included in the final multivariable models. Incidence rate ratio (IRR) with a 95% confidence interval (CI) was used to describe associations. Results: Of the 2357 COVID-19 patients, 248 (10.5%) died. The median age of participants was 59 (IQR= 45- 70) years, and the majority (64.9%) of them were male. Lower median RBC was observed among those who died at 4.58 (4.06-5.07) as compared to those who survived at 4.69 (4.23-5.12) whereas high median (IQR) WBC was a predictor of mortality with 11.2 (7.7-15.9). After adjusting for confounders, death was associated with age >74 years having adjusted incidence rate ratio [aIRR (95%CI): 2.46 (1.40-4.34)], and critical clinical situations [aIRR (95% CI): 4.04 (2.18-7.52)]. Conclusion: Our results demonstrate that abnormal liver function tests, abnormal white blood cells, age of the patients, and clinical status of the patients during admission are associated with unfavorable outcomes of COVID-19. Hence, timely monitoring of these laboratory results at the earliest phase of the disease was highly commendable.
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COVID-19 , DeathABSTRACT
This paper critically analyzes the challenges of psychological adjustment faced by international students and explores coping mechanisms and support services that can help them overcome these challenges. The essay first introduces the background information on international students and highlights the importance of psychological adjustment for their well-being and academic success. The challenges of psychological adjustment, including cultural, academic, social adjustment, and language barrier, are discussed in detail. The essay then explores coping mechanisms, including problem-focused coping, emotion-focused coping, seeking social support, and cultural adjustment programs, and the support services, including counseling services and international student services, that can help international students adjust to their new environment. Finally, the essay evaluates the effectiveness of these coping mechanisms and support services, emphasizing the importance of cultural competence in providing effective support services. This essay has practical implications for higher education institutions in providing tailored support to international students and highlights the need for future research to explore the effectiveness of coping mechanisms and support services for different groups of international students and the impact of the COVID-19 pandemic on their psychological adjustment. © 2023 NSP Natural Sciences Publishing Cor.
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Over the past two years, the world has witnessed one of the worst pandemics due to the outbreak of coronavirus (covid19), which has infected hundreds of millions and claimed the lives of millions across the globe. If we have learned anything from this pandemic, it is that the actual healthcare systems are unreliable under situations of enormous pressure. Accordingly, the present investigation tackles smart healthcare paradigm as a solution to transform the classical healthcare model into a sustainable one. Therefore, this paper reviews the most advances on remote healthcare monitoring technologies and introduces a novel smart home architecture combined with cloud computing and machine learning to create a sustainable solution for healthcare. Furthermore, a case study of a patient with heart disease is suggested to highlight the importance of using machine learning to automate medical monitoring at home. Additionally, an investigation of human behavior using neural network transformers is suggested as a perspective of the research in hand to examine patients' activities at home using surveillance camera thus constructing a resilient remote healthcare model. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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The purpose of this study is to measure the effect of the number of infections with the Covid-19 virus on the number of recovery cases using the method Panel data. The real data was relied on for seven sections (Erbil, Dohuk, Karkh, Rusafa, Diwaniyah, Karbala, Najaf) for a period of six months from January to June 2021. It was concluded that the best model that represents the data is the Pooled regression model (PRM). As well as the presence of a significant effect between the number of injuries and the number of recovery cases. © 2022 DAV College. All rights reserved.
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Steroidal products have been found useful in inflammations associated with Covid 19. Prednisolone is one readily available steroid, which is often found as uncoated normal release tablets. Modified release prednisolone may be desirable in Covid 19 for sustained actions. This is expected to reduce dosing frequency and enhance compliance. This study is concerned with development of controlled release prednisolone using coating technology with bio-compatible, cross-linked starch-albumin films. Starches and proteins are excellent film formers with good flexibility, transparency, and bio-compatibility. The cross-linked starch-albumin films were prepared using glycerol as the plasticizer: starch (A), starch-albumin (B), starch-albumin cross-linked with formaldehyde at 1 % (C), 5 % (D) and 10 % (E). Equilibrium moisture sorption (EMS) at 100 % relative humidity, equilibrium swelling (ESC) in buffer solutions of pHs 2, 7 and 9, and DSC thermal properties were evaluated. In-vitro drug release from the film coated prednisolone tablets were evaluated in 0.1N HCl, water and phosphate buffer 8.0 as dissolution media. Films showed ESC in the order A>D>E>B>C;D>C>A>E>B and A>D>C>B>E in acidic, neutral and alkali media respectively. EMS was in the order B>E>A>D>C;with slight shift in the melting temperatures. In-vitro release at 240 min varied from 78 to 117 % (E>D>C>A>B);19 to 60 % (D>B>C>E>A) and 49 to 60 % (B>A>C>D>E) in 0.1N HCl, water and PBS respectively. Cross-linking improved the stability and swelling of films. The in-vitro release in alkaline medium suggests their usefulness for controlled drug delivery. New pH-responsive polymers, with improved physicochemical properties for coating prednisolone tablets were developed. Copyright © 2007, Nat. Inst. for Pharmaceutical Research and Development. All rights reserved.
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Background: The COVID-19 pandemic has led to widespread vaccination with effective results and a great safety profile. However, as the vaccination rate has increased, more cases of autoimmune diseases after the COVID-19 vaccine have been described. We present a systematic review of ANCA-associated glo-merulonephritis after the COVID-19 vaccine. Objectives: To summarize the existing evidence on ANCA-associated glomeru-lonephritis after the COVID-19 vaccine. Methods: We searched all studies from inception till January 2 7, 2022, that described ANCA-associated biopsy-proven glomerulonephritis after COVID-19 vaccine through Embase and Medline. Methodological quality was evaluated with the 4 domains tool. We included 13 patients from 2 case series and 9 case reports. We extracted demographics, history, lab results, outcomes. We then applied descriptive statistics. Results: 46% of the patients were males and 54% were females. The median age was 74 years. 54% developed symptoms after the second dose of the 2-dose vaccine. The median interval between the vaccine and the symptom onset was 10.5 days. 85% had anti-MPO antibodies, and the rest-anti-PR3 antibodies. 31% of patients had persistent creatinine (Cr) elevation on follow-up, and 3 patients were requiring hemodialysis. Of those 3 patients, 1 patient had normal renal function prior to presentation, and the rest had chronic kidney disease. The summary of the cases is presented in Table 1. Conclusion: Although the causality cannot be established on current evidence, the COVID-19 vaccine can probably trigger glomerulonephritis associated with ANCA, primarily anti-MPO type. We need a bigger cohort to identify patients predisposed for disease development or relapse after the COVID-19 vaccine.
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Context: The impact of coronavirus disease 2019 (COVID-19) pandemic on vaccine-preventable diseases, including diphtheria, may hamper the previous gains made in the eradication of the disease. Aims: We report the epidemiological profile, clinical features, laboratory findings, and hospitalization outcomes amongst cases of diphtheria managed at Federal Medical Centre, Katsina, Nigeria during the first wave of COVID-19 pandemic. Settings and Design: This was a retrospective review of cases of diphtheria managed between July and December 2020. Methods and Material: We extracted the clinical (socio-demographics, clinical features, and hospitalization outcomes) and laboratory findings (full blood counts, electrolytes, urea and creatinine) from the record of the children. Statistical Analysis Used: Using SPSS, we carried out a descriptive analysis and applied binary logistic regression to determine factors associated with death. Level of statistical significance was set at P < 0.05. Results: A total of 35 cases of diphtheria were admitted and managed from 1 July to 31 December 2020. The mean age of the children was 7.6 +/- 3.1 years. Males were 15 (42.9%). There were 24 deaths (case fatality of 68.6%). Clinical findings were comparable between survivors and non-survivors except the bull neck, which was more common among non-survivors (P = 0.022). The median duration of hospitalization was shorter in those that died (P = 0.001). The age, sex, immunization status, leukocytosis, and biochemical features of renal impairments were not predictive of deaths. Prescence of bull neck was predictive of death (adjusted odds ratio 2.115, 95% CI 1.270, 3.521). Conclusions: The study shows a high number of cases of diphtheria over a short period of six months with high mortality. Amongst the clinical and laboratory variables, only presence of bull neck was predictive of death.
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Trends in routine laboratory tests, such as high white blood cell and low platelet counts, correlate with COVID-19-related intensive care unit (ICU) admissions. Other related biomarkers include elevated troponin, alanine aminotransferase, and aspartate transaminase levels (liver function tests). To this end, the aim of this study was to investigate the effect of changes in laboratory test parameters on ward-based and ICU COVID-19 patients. A total of 280 COVID-19 patients were included in the study and were divided based on admission status into ICU (37) or ward (243) patients. ICU admission correlated significantly with higher levels of several tested parameters, including lactate dehydrogenase, creatinine, D-dimer, creatine kinase, white blood cell count, and neutrophil count. In conclusion, routine laboratory tests offer an indication of which COVID-19 patients are most likely to be admitted to the ICU. These associations can assist healthcare providers in addressing the needs of patients who are at risk of COVID-19 complications.
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COVID-19 , Critical Care , Hospitalization , Humans , Intensive Care Units , Retrospective StudiesABSTRACT
Background: Infectious diseases have been a constant threat to people's health and survival, at least thirty re-emerging and emerging diseases (Parks, 2009) are known to be of public health importance posing a burden to the health system;in addition, emergence of COVID-19 further tested the resilience of the health system to respond to public health emergencies (NCDC, 2020). This study assessed the effect of COVID-19 on use of maternal and child health (MNCH) services with objectives being the impact on family planning use, antenatal care visits, facility-based delivery and child related services such as immunization, child nutrition and outpatient clinic in FMC Gusau. Data from units offering MNCH services for six months, three months pre-covid-19 index case (January to March) and three months post covid-19 index case (April to June), corresponding to the period of lockdown, in addition same periods in the previous year (2019) was retrieved and entered into Statically package for social sciences (SPSS) now IBM statistic, comparison was made using comparable period of the year as well as a pre and post Covid index case. Over the six-months period, aggregate data shows that hospital visit for all categories of maternal newborn and child health reduced three months (April, May and June) post covid index case in the facility and subsequent proclamation of lockdown in the State, as compared to three-months pre-covid (January, February and first three weeks of March) Despite the additional burden imposed by the emergence of COVID-19 in FMC Gusau and the Attendant stretched on health system, the resilience of the health system was brought to fore, however with support from Federal ministry of health, National Centre for disease control and other agencies, FMC Gusau was able to use the COVID-19 emergency to strengthen service provision.
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Background: Health care providers (HCPs) have always been a common target of stigmatization during widespread infections and COVID-19 is not an exception. Aim: This study aims to investigate the prevalence of stigmatization during the COVID-19 pandemic among HCPs in seven different countries using the Stigma COVID-19 Healthcare Providers tool (S19-HCPs). Design: Cross-sectional. Methods: The S19-HCPs is a self-administered online survey (16-item) developed and validated by the research team. The participants were invited to complete an online survey. Data collection started from June-July 2020 using a convenience sample of HCPs from Iraq, Jordan, Egypt, Saudi Arabia, Indonesia, Philippines, and Kuwait. Results: A total number of 1726 participants were included in the final analysis. The majority of the study participants were Jordanians (22%), followed by Kuwaitis (19%), Filipinos (18%) and the lowest participants were Indonesians (6%). Other nationalities were Iraqis, Saudis, and Egyptians with 15%, 11% and 9% respectively. Among the respondents, 57% have worked either in a COVID-19 designated facility or in a quarantine center and 78% claimed that they had received training for COVID-19. Statistical significance between COVID-19 stigma and demographic variables were found in all aspect of the S19-HCPs. Conclusion: The findings of this study demonstrated high levels of stigmatization against HCPs in all the included seven countries. On the other hand, they are still perceived positively by their communities and in their utmost, highly motivated to care for COVID-19 patients. Educational and awareness programs could have a crucial role in the solution of stigmatization problems over the world.
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A smart classroom is the merger of knowledge used at the teacher's desk and in front of the classroom with students' attendance and a reallocation that allows the effective usage of that knowledge. Currently, data communication skills and the Internet of Things are already global in the area of teaching. Therefore, they started significantly to change the way of teaching and learning. In this paper, a new method for controlling and communicating with the smart classroom was achieved with a level of security and efficiency using the internet of things technology to control all devices of the classroom such as air conditioner, data show, lights, and so on. the nodemcu ESP8266 board was used in this paper which is more suitable for controlling the classroom for the reason of low cost and accurate result and easy to connect to the internet. In This method, the user can control all classroom components from any place in the world. The contribution of this paper is that within the era of coronavirus and with electronic teaching it is essential to deal with everything remotely without touching any switch or plug and this method applies this idea. The discussion shows that the system is effective, low cost, accurate and secure without error. © 2021 IEEE.
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Between 2014 and 2019, the US lost more than 2.1 billion USD to phishing attacks, according to the FBI's Internet Crime Complaint Center, and COVID-19 scam complaints totaled more than 1,200. Phishing attacks reflect these awful effects. Phishing websites (PWs) detection appear in the literature. Previous methods included maintaining a centralized blacklist that is manually updated, but newly created pseudonyms cannot be detected. Several recent studies utilized supervised machine learning (SML) algorithms and schemes to manipulate the PWs detection problem. URL extraction-based algorithms and schemes. These studies demonstrate that some classification algorithms are more effective on different data sets. However, for the phishing site detection problem, no widely known classifier has been developed. This study is aimed at identifying the features and schemes of SML that work best in the face of PWs across all publicly available phishing data sets. The Scikit Learn library has eight widely used classification algorithms configured for assessment on the public phishing datasets. Eight was tested. Later, classification algorithms were used to measure accuracy on three different datasets for statistically significant differences, along with the Welch t-test. Assemblies and neural networks outclass classical algorithms in this study. On three publicly accessible phishing datasets, eight traditional SML algorithms were evaluated, and the results were calculated in terms of classification accuracy and classifier ranking as shown in tables 4 and 8. Eventually, on severely unbalanced datasets, classifiers that obtained higher than 99.0 percent classification accuracy. Finally, the results show that this could also be adapted and outperforms conventional techniques with good precision.
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AFRICAN DEVELOPMENT : It is widely feared that the shock of the COVID-19 pandemic will lead to a significant worsening of the food security situation in low and middle-income countries. One reason for this is the disruption of food marketing systems and subsequent changes in farm and consumer prices. Based on primary data in Ethiopia collected just before the start and a few months into the pandemic, we assess changes in farm and consumer prices of four major vegetables and the contribution of different segments of the rural-urban value chain in urban retail price formation. We find large, but heterogeneous, price changes for different vegetables with relatively larger changes seen at the farm level, compared to the consumer level, leading to winners and losers among local vegetable farmers due to pandemic-related trade disruptions. We further note that despite substantial hurdles in domestic trade reported by most value chain agents, increases in marketing-and especially transportation-costs have not been the major contributor to overall changes in retail prices. Marketing margins even declined for half of the vegetables studied. The relatively small changes in marketing margins overall indicate the resilience of these domestic value chains during the pandemic in Ethiopia
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INTRODUCTION: Kaduna State is among the three States with the highest number of confirmed COVID-19 cases. The objective of this study was to assess the knowledge, risk perception and practices of staff towards prevention and control of COVID-19 infection in schools to provide policy makers, education and health managers required information to manage the epidemic as the schools prepare to re-open. METHODS: This was a school-based survey conducted using purposive sampling of 55 schools located in nine LGAs with the highest number of reported COVID-19 cases as at October 2020. Five schools with the highest students'/pupils' enrollment in each of the LGA were selected and all staff were interviewed. Information on knowledge, risk perception and practices of prevention was collected. Descriptive statistics were generated using Stata v14 software. RESULTS: A total of 1065 staff in 55 schools completed the interview. Major sources of information are television (73%), radio (61%), and social media (57%);and 76% indicated that a virus is the causative agent of COVID-19. Overall, 70%, 19%, 7%, 9.3% and 0% respectively had adequate knowledge of cause, preventive measures, respiratory hygiene, modes of transmission and symptoms of COVID-19;however only 14% ever attended a workshop on COVID-19. Eighty-two percent and 89% respectively believed in the efficacy of face masks and handwashing as means of prevention;39% thought that they are likely to contract COVID-19. Ninety-nine percent and 90% have ever used face mask and hand sanitizer to prevent COVID-19;96% and 85% respectively have use these methods in previous 24hours. Between 42% and 73% of schools needed additional commodities/requirements/supplies to comply fully with COVID-19 prevention protocols. CONCLUSION: While knowledge of COVID-19 is suboptimal, perception is positive and practice is high. Thus, teachers need to be well informed and encouraged to sustain current levels of preventive measures. Government needs to provide schools with adequate preventive commodities to ensure compliance.
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The researchers combine in-person survey data collected in February 2018 with phone survey data collected in June and September 2021 to study how dairy value chains in Ethiopia have coped with the COVID-19 pandemic. Focusing on the major dairy value chain connecting farmers in North and West Shewa as well as peri-urban and urban producers in and around Addis Ababa to consumers in Addis Ababa, the researchers applied a cascading survey approach in which the researchers collected data at all levels of the value chain: dairy farmers, rural wholesalers, and urban retailers. In June and September 2021, the researchers see little evidence that the pandemic is exerting a negative effect on the dairy value chain actors. Nine percent of the dairy farmers exited the business between February 2018 and June 2021, but these exits were not caused by the pandemic. Milk yields have increased considerably between 2018 and 2021, particularly among cross-bred cow types. Meanwhile, sales patterns and sales destinations among farmers have remained similar since 2018. In 2021, farmers are processing more and the decision to process or not seems to be formed by the changes in the relative prices of liquid milk and processed dairy products. The researchers see suggestive evidence of a decline in credit availability and access to extension services. Same is true for the availability of daily workers, though not many farmers hire external help. Among farmers, by far the main concern relate to surging feed prices that increased since the onset of the pandemic and June 2021 by 80 to 100 percent. As a result, farmers report purchasing less feed and this is reducing milk yields, and thus farmer incomes. Rural traders also seem unaffected by the pandemic. The turnover among liquid milk traders is high with 36 percent of the milk wholesalers interviewed in February 2018 reported to have stopped trading dairy products by September 2021. However, only few reported that the pandemic was a factor in their decision to quit the business. The turnover among butter traders was smaller with 4 out of 30 traders quitting between February 2018 and September 2021. The researchers see no dramatic changes in procurement and sales destinations between 2018 and 2021. Traders report that the competition in their sector has increased since February 2020. Meanwhile, the availability of labor at the midstream segment of the value chain has remained the same over time. The main concern among at this segment of the value chain relates to limited supply of milk and butter from rural areas. The impact of the pandemic seems also minimal at the retail level. About 29 percent of the retail traders had quit the business since February 2018, mostly because their business was no longer profitable. Eight out of the 49 retailers that exited the sector attributed their exit, at least partly, to the pandemic. Comparison of the data collected in 2018 and 2021 reveals that the traded quantities have increased in the dairy retail sector. However, when asked to compare to the situation just before the pandemic was declared, most traders report selling less and having fewer clients now. The researchers see little change in labor use at the retail level across the survey years. Shortage of dairy coming into Addis Ababa was highlighted as the main concern among retail traders. In line with the high general inflation in Ethiopia over the past years, prices of liquid milk have increased considerably in the last three years. However, when expressed in USD terms, prices of milk have remained surprisingly stable (0.92 USD/liter in 2018 and 0.91 USD/liter in 2021). Comparing the farmgate and retail prices reveal that farm share (i.e., the share of the final retail price that is received by the farmer) increased slightly between 2018 and 2021. Finally, the researchers see no evidence that increases in post-harvest losses. The physical quantities wasted seem very low, which is in line with the more careful analysis conducted by Minten, Tamru, and Reardon (2020). If anything, these losses at the
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The researchers combine in-person survey data collected in February 2020 (i.e., just before the pandemic was declared) with phone survey data collected in March 2021 (i.e., one year into the pandemic) and August 2021 (i.e., approximately 18 months into the pandemic) to study how vegetable value chains in Ethiopia have coped with the COVID-19 pandemic. Focusing on the major vegetable value chain connecting farmers in East Shewa zone to consumers in Addis Ababa, the researchers applied a cascading survey approach in which the researchers collected data at all levels of the value chain: vegetable farmers, urban wholesalers, and retailers. In March 2021 and August 2021, the COVID-19 pandemic is having only a limited impact on this major vegetable value chain. Farmers' access to credit, labor or extension services have not markedly changed since the pre-pandemic period in February 2020. The main concern among farmers relates to the soaring prices of key inputs with prices of key fertilizers having increased by more than 40 percent between February 2020 and March 2021. Among the many pandemic related policy adjustments was the relocation of the wholesale vegetable market from a crowded area in the city center to the outskirts of Addis Ababa. Most wholesale traders viewed that while the pandemic itself has had a limited impact on their business activity, the re-location of the wholesale market had a considerably larger negative impact. Most wholesaler traders reported that they are trading less vegetables and have fewer clients to sell in March 2021 compared to the situation in February 2020. Almost all of these wholesaler traders identified the re-location of the vegetable wholesale market to the outskirts of Addis Ababa as the primary reason for the declined sales and clientele, and thus, as a major concern for their trading activities. The urban retailers seem to have been relatively more affected by the pandemic than farmers and wholesalers, although many reported to have also been negatively affected by the relocation of the wholesale market. Out of the 210 retailers interviewed in February 2020, 32 had quit their business by August 2021. Out of these 32 traders that quit, only 4 responded that the pandemic was the main factor for quitting, 9 responded at it was a factor while the remaining 19 responded that the pandemic played no role in their decision to quit. In March 2021, nearly two-thirds of the retailers reported that there is less choice with respect to transporters from wholesale markets compared to the situation in February 2020. Nearly 80 percent of retailers who reported a decrease in choice of transporters, said that the change was due to the re-location of the wholesale market, while 19 percent said it was due to the COVID-19 pandemic. The researchers document considerable volatility in prices and marketing margins using four rounds of vegetable price data collected at all levels of the value chain. For instance, onion prices soared during the first months of the pandemic when imports from Sudan came to halt. Encouraged by these price increases, many farmers began allocating more land to onions. This, together with important markets being closed because of instability and conflict in some parts of the country, led to a considerable oversupply of onions in Addis Ababa which in turn resulted a sizable drop in farm gate and final consumer prices between May 2020 and February 2021. Combined with soaring input costs, these plummeting onion prices must have led to considerable losses among farmers. This price volatility was identified by many farmers, wholesalers, and retailers as the most pressing concern to their farming or trading activities. Finally, the researchers attempted to estimate post-harvest losses along the vegetable value chain. Using the data from the March-2021 survey round, the largest losses are estimated for tomato (11.5 percent), head cabbage (11.8 percent) and Ethiopia kale (10.5 percent) and lowest for green pepper (7.2 percent) and onion (2.6 percent). Interestingly, the main origin of