The Prevalence and Determinants of Child Hunger and Its Associations with Early Childhood Nutritional Status among Urban Poverty Households during COVID-19 Pandemic in Petaling District, Malaysia: An Exploratory Cross-Sectional Survey.

Child hunger was prevalent during the COVID-19 pandemic, but the extent, determinants, and impact on pre-school children aged 6 months to 7 years old from Malaysian urban poor households are still unknown. This exploratory cross-sectional study was performed between July 2020 and January 2021 at the Lembah Subang People Housing Project, Petaling. The households' food security status was assessed using the previously validated Radimer/Cornell questionnaire, and the children's anthropometric measurements were taken. Food diversity score was assessed using the World Health Organization Infant and Young Children Feeding (under-2 children) or Food and Agriculture Organization Women's Dietary Diversity (2-year-old-and-above children) systems. Overall, 106 households were recruited. The prevalence of child hunger is 58.4% (95% CI: 50.0, 67.4). Significant differences were found in breastfeeding and sugar-sweetened beverage consumption between under-2 and ≥2-year-old children. There were no significant differences between child hunger and other food-insecure groups in weight-for-age, height-for-age, and weight-for-height z-scores. Only a higher dietary diversity score was significantly protective against child hunger after adjusting for maternal age, paternal employment status, and the number of household children (ORadjusted: 0.637 (95% CI: 0.443, 0.916), p = 0.015)). Proactive strategies are warranted to reduce child hunger during the COVID-19 pandemic by improving childhood dietary diversity.

Probabilistic Approach to COVID-19 Data Analysis and Forecasting Future Outbreaks Using a Multi-Layer Perceptron Neural Network.

The present outbreak of COVID-19 is a worldwide calamity for healthcare infrastructures. On a daily basis, a fresh batch of perplexing datasets on the numbers of positive and negative cases, individuals admitted to hospitals, mortality, hospital beds occupied, ventilation shortages, and so on is published. Infections have risen sharply in recent weeks, corresponding with the discovery of a new variant from South Africa (B.1.1.529 also known as Omicron). The early detection of dangerous situations and forecasting techniques is important to prevent the spread of disease and restart economic activities quickly and safely. In this paper, we used weekly mobility data to analyze the current situation in countries worldwide. A methodology for the statistical analysis of the current situation as well as for forecasting future outbreaks is presented in this paper in terms of deaths caused by COVID-19. Our method is evaluated with a multi-layer perceptron neural network (MLPNN), which is a deep learning model, to develop a predictive framework. Furthermore, the Case Fatality Ratio (CFR), Cronbach's alpha, and other metrics were computed to analyze the performance of the forecasting. The MLPNN is shown to have the best outcomes in forecasting the statistics for infected patients and deaths in selected regions. This research also provides an in-depth analysis of the emerging COVID-19 variants, challenges, and issues that must be addressed in order to prevent future outbreaks.

'More together than apart': The evaluation of a virtual course to improve mental health and well-being of adults with intellectual disabilities during the COVID-19 pandemic.

BACKGROUND: To address the growing concerns over poor mental health experienced by adults with intellectual disabilities due to the COVID-19 pandemic, a national virtual mental health course was delivered and evaluated. METHODS: This mixed methods study utilized both qualitative and quantitative assessments. Participants were 27 adults with intellectual disabilities who participated in the 6-week course. Participants completed measures of self-efficacy and well-being at three time points and qualitative satisfaction measures at post and follow-up. RESULTS: Attendance was high and the course was feasible and acceptable to participants. Positive changes related to mental health self-efficacy were detected (p = .01), though mental well-being did not improve. CONCLUSION: The study provided evidence for the feasibility and value of the course for this population. Future research should examine how virtual courses could support the population in terms of pandemic recovery and how courses may work for individuals who are less independent.

Comparison of sleep quality among COVID-19 patients and non-COVID-19 population in Pakistan: A cross sectional study during the COVID-19 pandemic.

Background: Adverse effects on the health and well-being changes may also express as a decreased sleep quality in COVID-19 patients. This study aimed to assess sleep quality among confirmed COVID-19 patients and the non-COVID-19 Pakistani population. Methods: An online cross-sectional survey was conducted between April and September 2020 in Punjab province, Pakistan. Information about demographic characteristics, COVID-19 diseased status, prior knowledge about COVID-19, and sleep quality using the Pittsburgh Sleep Quality Index (PSQI) was collected. Results: A total of 597 participants were included in this study, 296 (49.6%) COVID-19 patients and 301(50.4%) non-COVID-19 population. The PQSI was used to measure seven distinct sleep components; subjective quality, latency, duration, efficiency, disturbances, medication, and daytime dysfunction. Where mean ± standard deviation (SD) were 0.96 ± 0.743, 1.47 ± 1.032, 0.97 ± 1.006, 0.61 ± 0.995, 1.13 ± 0.649, 0.23 ± 0.651, 1.02 ± 0.861 respectively in total population (N = 597). Sleep latency, sleep duration, and sleep efficiency did not show a significant difference in the T-Test. While sleep quality, sleep disturbances, sleep medication, and daytime dysfunction showed a significant difference between both populations. Conclusion: In conclusion, we highlighted the poor sleep quality in COVID-19 patients as compared to the non-COVID-19 population.

Effect of Metarhizium anisopliae on the nutritional physiology of the fall armyworm, Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae)

Background: The fall armyworm, Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae), was recorded for the first time in Pakistan in 2019, and now it has spread in several regions, i.e., Punjab and Sindh, affecting maize production. Farmers are using widely synthetic pesticides to control the pest. Further, the resistance development in insects and the non-target effect of chemicals on the environment and humans pose serious threats of using insecticides. The use of entomopathogenic fungi (EPF) is being considered an important tool in integrated pest management program. The main objective of this study was to check the impact of different conidial concentrations of Metarhizium anisopliae fungus on the nutritional physiology of S. frugiperda. Results: The dose-dependent effect of tested EPF was observed, and the highest concentration (1 × 109 conidia/ml) considerably affected nutritional parameters. Reduced relative consumption rate (21.7%), relative growth rate (19.5%), the efficiency of conversion of ingested food (24.2%), and approximate digestibility (16.3%) were observed in treated larvae compared to the untreated by using a higher concentration of EPF. Pupal weight was also found lower (77.9 mg and 84.2 mg, respectively), when larvae were treated by 1 × 109 and 1 × 108 conidia/ml concentrations of EPF. Further, 46.7% of larvae were found dead with this conidial concentration. Conclusions: This study suggests that the application of a higher concentration of M. anisopliae could be an effective option to control S. frugiperda. The EPF can enhance the integrated pest management programs and could be useful in reducing the environmental impact of synthetic insecticides. [ FROM AUTHOR] Copyright of Egyptian Journal of Biological Pest Control is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full . (Copyright applies to all s.)

Role of Serum Ferritin in Predicting Outcomes of COVID-19 Infection Among Sickle Cell Disease Patients: A Systematic Review and Meta-Analysis.

Patients with sickle cell disease (SCD) are at higher risk of getting severe COVID-19 infection. This systematic review and meta-analysis aimed to determine the role of serum ferritin in predicting ICU admission and mortality among patients with SCD following COVID-19 infection. A systematic search was conducted in PubMed, Scopus, Web of Science, Embase, WHO COVID-19 database, ProQuest, and Cochrane Library for articles published between 1st December 2019 to 31st November 2021. Methodological quality was assessed using the Joanna Briggs Institute (JBI) critical appraisal checklists. Eleven articles (7 cohorts and 4 case series) were included in this review. Pooled mean serum ferritin level on admission was 1581.62 ng/mL while pooled proportion of ICU admission and mortality were 0.10 (95% CI 0.06; 0.16, prediction interval 0.04; 0.23, p = 0.29, I 2 = 17%) and 0.07 (95% CI 0.05; 0.11, prediction interval 0.04; 0.12, p = 0.68, I 2 = 0%) respectively. Meta-regression showed that serum ferritin did not predict for both ICU admission (regression coefficient = 0.0001, p = 0.3523) and mortality (regression coefficient = 0.0001, p = 0.4029). Our analyses showed that serum ferritin may not be a useful marker to predict the outcomes of COVID-19 infection among patients with SCD. More data are required to identify a reliable tool to identify patients with SCD who are at risk of getting severe COVID-19 infection. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=287792, PROSPERO Registration: CRD42021287792.

Tocilizumab in severe COVID-19 – a randomized, double-blind, placebo-controlled trial

Background The therapeutic effectiveness of interleukin-6 (IL-6) receptor inhibitor in critically ill hospitalized patients with coronavirus disease 2019 (COVID-19) is uncertain. Methods To evaluate the efficacy and safety of the outcome as recovery or death of tocilizumab for severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) infection, we conducted a randomized, double-blinded, placebo-controlled phase 2 trial in critically ill COVID-19 adult patients. The patients were randomly assigned in a 4:1 ratio to receive standard medical treatment plus the recommended dose of either tocilizumab or the placebo drug. Randomization was stratified. The primary outcome was the recovery or death after administration of tocilizumab or a placebo drug. The secondary outcomes were clinical recovery or worsening of the patients' symptoms and inflammatory markers and discharge from the hospital. Results Out of 190 patients included in this study, 152 received tocilizumab, and 38 received a placebo. The duration of hospital stay of the interventional group was 12.9±9.2, while the placebo group had a more extended hospital stay (15.6±8.8). The survival ratio in tocilizumab group was 0.82 (95% confidence interval [CI], 10.55 to 12.24;p=0.58 by log-rank test). The survival ratio in the placebo group was 0.23 (95% confidence interval [CI], 10.86 to 16.11;p=0.32 by log-rank test). The inflammatory markers in the tocilizumab group significantly declined by day 16 compared to the placebo group. Conclusions The use of tocilizumab was associated with decreased mortality, earlier improvement of inflammatory markers, and reduced hospital stay in patients with severe COVID-19.

Potential Barriers amongst Health Care Professionals of Pakistan in managing COVID-19 patients.

OBJECTIVES: To evaluate basic knowledge of Health Care Professionals (HCPs) of Pakistan in managing COVID 19 patients. It includes information regarding infection control measures, administrative and professional support. This was followed by evaluation of psychological factor that can act as a barrier in effective management of these patients. METHODS: The survey was conducted on line using Google Form. After approval from hospital ethical committee survey link was disseminated to HCPs using social media. RESULTS: Four hundred fifteen HCPs were participated. Most of them were younger than 30 years and majority of them were postgraduate trainees. Results showed gaps in the knowledge about basic infection control measure like donning/doffing and understanding about high-risk procedures. On job training, professional and administrative support is compromising. Many of HCPs are anxious nowadays, having symptoms related to burn out with logical reasons behind. Even with all those hurdles they are committed and ready to volunteer themselves. CONCLUSION: The HCPs of Pakistan needs urgent attention for providing them Formal training regarding infection control measure. Administrative and professional support is required from institutions and scientific societies. Online teaching modules and webinar is a suitable option. The symptoms of burn out are significant and would increase with passage of time. This needs to be supported by occupational health committees.

The Impact of Intellectual Capital on Bank Profitability during COVID-19: A Comparison with China and Pakistan

This study aims to examine how the relationship between intellectual capital (IC) and bank profitability changed during COVID-19. Based on the data of 34 Chinese banks and 39 Pakistani banks, this study uses ordinary least squares (OLS) to examine this relationship during the COVID-19 era. Profitability is measured by return on assets (ROA) and return on equity (ROE), and IC is measured by the value added intellectual coefficient (VAIC) model. The findings show that, even during the COVID-19 pandemic, IC has managed to sustain its positive influence on bank profitability in China and Pakistan. Among IC components, our study reports that human capital is the only IC resource that continues to enhance ROA and ROE of Chinese and Pakistani banks during the pandemic period. Our study suggests that policymakers should pay more attention to IC resources, which has the potential to improve banks’ profitability even during crisis times.

The utility of remdesivir in SARS-CoV-2: A single tertiary care center experience from a developing country.

BACKGROUND: Remdesivir is a monophosphoramidate prodrug of an adenosine analog, and it has a broad-spectrum antiviral activity against paramyxoviruses, flaviviruses, and coronaviruses. Remdesivir is associated with decreased hospital stay and improved outcomes in coronavirus- disease 2019 (COVID-19). METHODOLOGY: Of 846 suspected COVID-19 patients admitted to the hospital, 612 SARS-CoV-2 nasopharyngeal RT-PCR positive patients were evaluated for enrollment in this prospective cohort study. 159 RT-PCR positive patients were given remdesivir. Their clinical, biochemical parameters, hospital stay, and outcomes related to morbidity and mortality were followed. RESULTS: Out of the 159 patients, 141 recovered after remdesivir use. The Chi-square test for independence examined the relation between the day of the first dose, dose of remdesivir, and clinical outcome. The standardized case fatality ratio (CFR) in the 453 hospitalized patients who did not receive remdesivir was 32.89% (N = 149) as compared to 11.32% (N = 18) in the patients who received remdesivir. These findings are in keeping with the therapeutic value of remdesivir in symptomatic SARS-CoV-2 infection of varying severity. CONCLUSION: The use of remdesivir is associated with a decrease in the severity of the SARS-CoV-2 infection. Its use is also associated with a decreased length of hospital stay and lower mortality than the patients who did not receive remdesivir.

Indo-Pak comparison and forecasting of COVID-19 epidemic: a secondary data analysis

Background: The world has historically faced and recovered from many pandemics. The most recent global pandemic that the whole world is facing is Novel Coronavirus - Covid-19. The objective of current study is to compare and forecast COVID-19 trends for Pakistan and India.

Sistem informasi desa siaga pangan menghadapi COVID-19 berbasis web service

SIDAVID19 is a food alert village information system to deal with COVID-19 a capability that must be owned by the system for recording the entry and distribution of staple goods BKPD can know food supplies and aid recipients in an integrated manner as well as village residents to obtain information to distribute village food via the internet. Information integration is a necessity for the government in realizing integrated services to the public. The SIDAVID19 service is one of the services provided to facilitate the management of the distribution of staple goods during the COVID9 emergency and access to information for the public and BKPD. This study describes the design of the SiDavid19 service which is a web service technology to connect users and providers in retrieving information needed by users.

Gambaran penggunaan masker di masa pandemi COVID-19 pada masyarakat kelurahan Cengkeh Turi kota Binjai tahun 2020

Penggunaan masker di masa pandemi COVID-19 merupakan hal yang sangat penting dikarenakan merupakan langkah pencegahan dan pengendalian COVID-19. Masker digunakan baik untuk orang terinfeksi guna mencegah penularan lebih lanjut dan masker digunakan orang yang sehat untuk melindungi diri dari orang yang terinfeksi. Sebagaimana diketahui penyebaran COVID-19 dapat terjadi terutama dari orang ke orang melalui percikan-percikan dari hidung atau mulut yang keluar saat orang yang terinfeksi COVID-19 batuk bersin atau berbicara. Tujuan penelitian ini adalah untuk mengetahui Gambaran Penggunaan Masker di Masa Pandemi COVID-19 Pada Masyarakat Kelurahan Cengkeh Turi Kota Binjai. Jenis Penelitian ini adalah penelitian deskriftif dan dengan menggunaan pendekatan cross sectional study. Sempel didalam penelitian ini sebanyak 75 responden. Analisis data didalam penelitian ini menggunakan Microsoft excel. Hasil dari penelitian ini menunjukkan bahwa dari 75 responden masyarakat kelurahan cengkeh turi kecamatan Binjai utara kota Binjai yang sudah selalu menggunakan masker saat bepergian keluar rumah dimasa pandemi COVID-19 ini sebanyak 53 (70.67%) dan 22 (29.33%) yang jarang menggunakan masker saat keluar rumah. The use of masks during the COVID-19 pandemic is very important because it is a measure to prevent and control COVID-19. Masks are used both for infected people to prevebt further transmission and masks are used by healthy people to protect themselves from infected people. As it is known that the spread of COVID-19 can occur mainly from person through droplets from the nose or mouth the come out when a person infected with COVID-19 coughs sneezes or talks. The purpose of this study is to find out. The purpose of the study is to determine An overview of the use of masks during the COVID-19 pandemic in the Cengkeh Turi village Binjai City. This type of research is a descriptive study and using a cross sectional study approach. Samples in this study were 75 respondents. Data analysis in this study used a Microsoft excel. The results of this study indicate that of the 75 respondents for the Cengkeh Turi Sub-district Binjai utara district Binjai city who have always used masks when traveling outside the hause during the COVID-19 pandemic 53 (7067%) and 22 (2933%) who rarely use masks when leaving the house.

CHALLENGES OF THE COVID-19 DURING PANDEMIC SITUATION, THE POSSIBLE SOLUTIONS USING INFORMATION TECHNOLOGY

Different technological advancements and technologies for the war against the pandemic have been created. The pandemic similarly has consequences for technology design, production and use. Better awareness of the roles that information technology system and technology investigators will play in this worldwide pandemic is urgently needed. This paper addresses new developments for reducing COVID-19 risks and relevant issues in the architecture, implementation and usage of technologies. It also offers perspectives and recommendations about how IT scientists can better combat the COVID-19 pandemic. This paper contributes to the future advancement of science and technologies to address pandemics and future pandemics adequately.

SOCIAL DISTANCE MODEL OF INNOVATIVE URBAN DESIGN: IMPLICATIONS OF POST-PANDEMIC STRATEGIC PLANNING FOR URBAN FORMS

According to expert's opinion, one can do very little to prevent the spread. [...]this pandemic has converted into international public health concern as well as economic crisis that has affected global economy of 90 trillion US dollars, which is beyond anything that previous century has witnessed. [...]governments are trying to adopt policies to avoid complete lockdowns along with minimizing the spread of this contagious virus. [...]governments have no option rather than attempting to develop a balance between health care and economic policies (Hynes et al., 2020). [...]as history constantly reminds us of the relationship between features of cities and critical diseases, it could leave marks on our cities, our societies and ourselves, we should know that things will never go to be as it was the past.

COVID-19 Infected Lung Computed Tomography Segmentation and Supervised Classification Approach

The purpose of this research is the segmentation of lungs computed tomography (CT) scan for the diagnosis of COVID-19 by using machine learning methods. Our dataset contains data from patients who are prone to the epidemic. It contains three types of lungs CT images (Normal, Pneumonia, and COVID-19) collected from two different sources;the first one is the Radiology Department of Nishtar Hospital Multan and Civil Hospital Bahawalpur, Pakistan, and the second one is a publicly free available medical imaging database known as Radiopaedia. For the preprocessing, a novel fuzzy c-mean automated region-growing segmentation approach is deployed to take an automated region of interest (ROIs) and acquire 52 hybrid statistical features for each ROIs. Also, 12 optimized statistical features are selected via the chi-square feature reduction technique. For the classification, five machine learning classifiers named as deep learning J4, multilayer perceptron, support vector machine, random forest, and naive Bayes are deployed to optimize the hybrid statistical features dataset. It is observed that the deep learning J4 has promising results (sensitivity and specificity: 0.987;accuracy: 98.67%) among all the deployed classifiers. As a complementary study, a statistical work is devoted to the use of a new statistical model to fit the main datasets of COVID-19 collected in Pakistan.

Indo-Pak Comparison Of COVID-19 By ARIMA Model: A Secondary Analysis (preprint)

Background: Historically, the world has faced and recovered from many pandemics. The most recent global pandemic facing the entire world is Covid-19. India and Pakistan can be considered to be in the same phases of development and health spending relative to their GDP and also have similar climatic conditions. The main aim of the study is to forecast cumulative cases and deaths in Pakistan and India, which will be helpful for policy makers to plan accordingly.Methods: The data set was obtained from the World Health Organization (WHO) website (https://covid19.who.int). The time period we have considered since the first corona related case and death were observed in both countries. The dataset for Pakistan covered the time period from 28th February 2020 to 28th February 2021 and for India 30th January to 28th February 2021. The Auto-Regressive integrated moving average (ARIMA) model was applied for forecasting using R-package.Results: Our results forecasted that cumulative COVID-19 cases at the end of June 2021, at the end of September 2021 and at the end of December 2021 will be 13065792, 14704450, and 16481122 respectively in India while for Pakistan, we forecasted that at the end of June 2021, at the end of September 2021 and at the end of December 2021 will be 746963.5 873557.3and 999766.5 respectively. Cumulative deaths were also forecasted for Pakistan and India. We predicted cumulative deaths as at the end of June 2021 at the end of June 2021, at the end of September 2021 and at the end of December 2021 will be 170586.5, 181153.4 and 192017.5 respectively in India while for Pakistan, we forecasted that cumulative deaths at the end of June 2021, at the end of September 2021 and at the end of December 2021 will be 17890.98, 21825.26 and 25849.4 respectively.Conclusion: Corona related cumulative cases and deaths are on the rise in both countries. The pandemic situation in India is worse than in Pakistan nevertheless both countries are at high risk. There is a sudden increasing pattern in the number of corona related cases in both countries.

Surveillance of genetic diversity and evolution in locally transmitted SARS-CoV-2 in Pakistan during the first wave of the COVID-19 pandemic (preprint)

Surveillance of genetic diversity in the SARS-CoV-2 is extremely important to detect the emergence of more infectious and deadly strains of the virus. In this study, we monitored mutational events in the SARS-CoV-2 genome through whole genome sequencing. The samples (n=48) were collected from the hot spot regions of the metropolitan city Karachi, Pakistan during the four months (May 2020 to August 2020) of first wave of the COVID-19 pandemic. The data analysis highlighted 122 mutations, including 120 single nucleotide variations (SNV), and 2 deletions. Among the 122 mutations, there were 71 singletons, and 51 recurrent mutations. A total of 16 mutations, including 5 nonsynonymous mutations, were detected in spike protein. Notably, the spike protein missense mutation D614G was observed in 31 genomes. The phylogenetic analysis revealed majority of the genomes (36) classified as B lineage, where 2 genomes were from B.6 lineage, 5 genomes from B.1 ancestral lineage and remaining from B.1 sub-lineages. It was noteworthy that three clusters of B.1 sub-lineages were observed, including B.1.36 lineage (10 genomes), B.1.160 lineage (11 genomes), and B.1.255 lineage (5 genomes), which represent independent events of SARS-CoV-2 transmission within the city. The sub-lineage B.1.36 had higher representation from the Asian countries and the UK, B.1.160 correspond to the European countries with highest representation from the UK, Denmark, and lesser representation from India, Saudi Arabia, France and Switzerland, and the third sub-lineage (B.1.255) correspond to the USA. Collectively, our study provides meaningful insight into the evolution of SARS-CoV-2 lineages in spatio-temporal local transmission during the first wave of the pandemic.