Enhanced cluster detection and noise reduction for geospatial time series data of COVID-19.

Spatial-temporal analysis of the COVID-19 cases is critical to find its transmitting behaviour and to detect the possible emerging clusters. Poisson's prospective space-time analysis has been successfully implemented for cluster detection of geospatial time series data. However, its accuracy, number of clusters, and processing time are still a major problem for detecting small-sized clusters. The aim of this research is to improve the accuracy of cluster detection of COVID-19 at the county level in the U.S.A. by detecting small-sized clusters and reducing the noisy data. The proposed system consists of the Poisson prospective space-time analysis along with Enhanced cluster detection and noise reduction algorithm (ECDeNR) to improve the number of clusters and decrease the processing time. The results of accuracy, processing time, number of clusters, and relative risk are obtained by using different COVID-19 datasets in SaTScan. The proposed system increases the average number of clusters by 7 and the average relative risk by 9.19. Also, it provides a cluster detection accuracy of 91.35% against the current accuracy of 83.32%. It also gives a processing time of 5.69 minutes against the current processing time of 7.36 minutes on average. The proposed system focuses on improving the accuracy, number of clusters, and relative risk and reducing the processing time of the cluster detection by using ECDeNR algorithm. This study solves the issues of detecting the small-sized clusters at the early stage and enhances the overall cluster detection accuracy while decreasing the processing time.

Quantities and qualities of fecal sludge: Experiences from field implementation with a Volaser in 7 countries during a pandemic

Reasonable estimates for quantities and qualities (Q&Q) of fecal sludge that accumulate in onsite sanitation containments are fundamental for the design of appropriate management and treatment solutions, from community to city-scale. There are increasing attempts to improve Q&Q estimates, but current approaches are still at a conceptual level, and are not yet standardized with confirmed statistical relationships. To reach this level, we will need consistent approaches for planning, measuring, and global collaborations. Hence, the objectives of this study were: (1) to assess and compare Q&Q of fecal sludge from seven cities and communities, and explore statistical relationships that could be used to increase accuracy of Q&Q estimations;(2) to test and launch the Volaser device for measuring in situ volumes of fecal sludge;and (3) to capture lessons learned from field implementation with collaborators in seven countries during a global pandemic when no international travel was possible. The study took place in Ghana, India, Lebanon, Kenya, Sierra Leone, Uganda, and Zambia during the COVID-19 pandemic. Q&Qs were measured in 204 containments with a Volaser, laboratory analysis, and questionnaire. Results indicate that there are differences in Total Solids (TS) and Chemical Oxygen Demand (COD) in fecal sludge based on containment type, toilet type, source, and whether there is a water connection on the premises. Based on the results of this study, together with previously published open-source data, an empirical relationship for Volatile Solids (VS) and TS of 0.49 (R2 = 0.88) was established using 1,206 data points. For COD/TS, no significant relationship was observed. Developing such empirical relationships will be useful for planning and modeling approaches. An external evaluation was conducted to evaluate overall project management, Volaser technology transfer, and effects of collaborating during the COVID-19 pandemic. Success factors for collaborating with new and existing partners without face-to-face meetings included laboratory capacity and experience with analytical methods, study objectives that were relevant for the partner and locality, and a strong quality assurance plan to ensure comparability of results. The lessons learned can be taken forward as ways to reduce carbon footprint, and contribute to resilient, inclusive development research projects. Copyright © 2023 Andriessen, Appiah-Effah, Browne, al Jahjah, Kabika, Kinobe, Korir, Nishimwe, Niwagaba, Pradeep, Prasad, Tembo, William, Ambuehl and Strande.

Phantasms in the Halls: A Future University is Possible (or) … a performative response to la paperson, Stefano Harney, Fred Moten, and Julietta Singh

Phantasms in the Halls: A Future University is Possible, is a mediated live performance presented synchronously on Zoom and in person. In this devised ensemble piece, the performers offer a performative response to recent scholarship on the settler colonial university and its significance in the time of the COVID-19 pandemic. The work weaves together theories of fugitivity, spectrality, and refusal to offer contextually situated critiques of labor practices under quarantine. The performance form works in collaboration with its critical content to offer an embodied, albeit mediated, look into what decolonizing academic labor can look like in a moment of global epistemic upheaval and collective survival. © 2022 National Communication Association.

A First-order Action Research Study to Uncover Students' Conceptual Gaps in an Online Statistics Course using Extended Matching Questions

The COVID-19 pandemic has forced institutions worldwide to accelerate their practices on digital transformation, especially in the use of Online Learning. The rapid pace of this transition has forced instructors also to adapt quickly to the online instructional design and in turn reduced opportunities of systematic action research within such a setting. In this paper, we present the action research study by an online instructor to tackle the problem of understanding conceptual gaps among learners. The instructor adapted an existing solution widely used in medical learning, called extended matching items, to design 'Extended Matching Question (EMQ)' for large scale online students (N=1525) of an introductory Statistics course. The instructor modified the structure of this assessment by allowing learners to first identify the concepts involved to solve a particular question and then use those concepts to reach the final numeric answer in the topic 'Permutations and Combinations'. Comparisons of this assessment were made with regular assessments (multiple choice or numerical answers) on the efficacy to make students apply their conceptual understanding for solving the problems. The analysis also enabled the instructor to identify the exact conceptual points where the students lag and showed strong association between identification of concepts and getting the final numeric answer correct. In addition, there was a significant increase in the average score of the test takers in the EMQ assessment compared to that of regular assessment. The study also presents pointers to universities involved in hybrid learning regarding the need for setting up research-practice partnerships within their institutions to tackle their own problems of practice. © 30th International Conference on Computers in Education Conference, ICCE 2022 - Proceedings.

Overlapping Delta and Omicron Outbreaks During the COVID-19 Pandemic: Dynamic Panel Data Estimates.

BACKGROUND: The Omicron variant of SARS-CoV-2 is more transmissible than prior variants of concern (VOCs). It has caused the largest outbreaks in the pandemic, with increases in mortality and hospitalizations. Early data on the spread of Omicron were captured in countries with relatively low case counts, so it was unclear how the arrival of Omicron would impact the trajectory of the pandemic in countries already experiencing high levels of community transmission of Delta. OBJECTIVE: The objective of this study is to quantify and explain the impact of Omicron on pandemic trajectories and how they differ between countries that were or were not in a Delta outbreak at the time Omicron occurred. METHODS: We used SARS-CoV-2 surveillance and genetic sequence data to classify countries into 2 groups: those that were in a Delta outbreak (defined by at least 10 novel daily transmissions per 100,000 population) when Omicron was first sequenced in the country and those that were not. We used trend analysis, survival curves, and dynamic panel regression models to compare outbreaks in the 2 groups over the period from November 1, 2021, to February 11, 2022. We summarized the outbreaks in terms of their peak rate of SARS-CoV-2 infections and the duration of time the outbreaks took to reach the peak rate. RESULTS: Countries that were already in an outbreak with predominantly Delta lineages when Omicron arrived took longer to reach their peak rate and saw greater than a twofold increase (2.04) in the average apex of the Omicron outbreak compared to countries that were not yet in an outbreak. CONCLUSIONS: These results suggest that high community transmission of Delta at the time of the first detection of Omicron was not protective, but rather preluded larger outbreaks in those countries. Outbreak status may reflect a generally susceptible population, due to overlapping factors, including climate, policy, and individual behavior. In the absence of strong mitigation measures, arrival of a new, more transmissible variant in these countries is therefore more likely to lead to larger outbreaks. Alternately, countries with enhanced surveillance programs and incentives may be more likely to both exist in an outbreak status and detect more cases during an outbreak, resulting in a spurious relationship. Either way, these data argue against herd immunity mitigating future outbreaks with variants that have undergone significant antigenic shifts.

The Interplay Between Policy and COVID-19 Outbreaks in South Asia: Longitudinal Trend Analysis of Surveillance Data.

BACKGROUND: COVID-19 transmission rates in South Asia initially were under control when governments implemented health policies aimed at controlling the pandemic such as quarantines, travel bans, and border, business, and school closures. Governments have since relaxed public health restrictions, which resulted in significant outbreaks, shifting the global epicenter of COVID-19 to India. Ongoing systematic public health surveillance of the COVID-19 pandemic is needed to inform disease prevention policy to re-establish control over the pandemic within South Asia. OBJECTIVE: This study aimed to inform public health leaders about the state of the COVID-19 pandemic, how South Asia displays differences within and among countries and other global regions, and where immediate action is needed to control the outbreaks. METHODS: We extracted COVID-19 data spanning 62 days from public health registries and calculated traditional and enhanced surveillance metrics. We use an empirical difference equation to measure the daily number of cases in South Asia as a function of the prior number of cases, the level of testing, and weekly shifts in variables with a dynamic panel model that was estimated using the generalized method of moments approach by implementing the Arellano-Bond estimator in R. RESULTS: Traditional surveillance metrics indicate that South Asian countries have an alarming outbreak, with India leading the region with 310,310 new daily cases in accordance with the 7-day moving average. Enhanced surveillance indicates that while Pakistan and Bangladesh still have a high daily number of new COVID-19 cases (n=4819 and n=3878, respectively), their speed of new infections declined from April 12-25, 2021, from 2.28 to 2.18 and 3.15 to 2.35 daily new infections per 100,000 population, respectively, which suggests that their outbreaks are decreasing and that these countries are headed in the right direction. In contrast, India's speed of new infections per 100,000 population increased by 52% during the same period from 14.79 to 22.49 new cases per day per 100,000 population, which constitutes an increased outbreak. CONCLUSIONS: Relaxation of public health restrictions and the spread of novel variants fueled the second wave of the COVID-19 pandemic in South Asia. Public health surveillance indicates that shifts in policy and the spread of new variants correlate with a drastic expansion in the pandemic, requiring immediate action to mitigate the spread of COVID-19. Surveillance is needed to inform leaders whether policies help control the pandemic.

Care of Patients with Haemato-Lymphoid Diseases During Covid: Challenges and Difficulties Faced by Non-Covid Patients in Accessing Health Care

Introduction: Since the national lock down was declared in March in response to the SARS COV-2 pandemic, there has been a concerted exercise to ramp up medical infrastructure and man power, with hospitals devising plans to prepare and allocate resources to organize themselves in managing the emerging cases efficiently. There was a growing concern that non COVID care and diseases could be affected. Inability to travel, limitation of financial support, lack of support services are among the many reasons that could limit non covid care. There is however a lack of information on this impact. Aims & Objectives: * To estimate the proportion of patients with benign hematological diseases whose care was affected during covid. * To estimate the proportion of patients with malignant hematological diseases whose care was affected during covid. Material(s) and Method(s): This was a cross-sectional study conducted among patients under the care of the Regional Advanced Center for Transplantation, Haemato-Lymphoid Oncology and Marrow Diseases (RACTHAM) at the Believers Church Medical College Hospital. Patients visiting the OP service were intervewed face to face. We report on our data collected in the intial phase of lockdown from April 1, 2020 through August 31, 2020. Result(s): A total of 505 patients were interviewed and 501 resposnes were recorded. The detailed characteristics are tabulated in Table 1. The majority, 375)74.8%) of patients were diagnosed with non malignat conditions. 256 (50.6%) of the resposndent were male. We noted that only 68 patients (13.5%) could not continue their care during the intial phase of the pandemic and lock down. 156 patients (30.*%) were able to continue their care elsewhere. There were 20 deaths during this period. Amongst those whose care was affected, 156 transferred care elsewehere. 27 (5.3&) patients were unalble to travel and 15 (2.9%) patients utilised telemedicine dservices to continue their care. ALl patients who required transfusion were able to access the same during this period. Conclusion(s): This study provides the first insight to the best of our knowledge on challenges to non covid care by patients with hematological diseases in our region. This study estimating the burden or proportion of patients with hematological diseases whose non covid care was affected has the potential to help in formulating national programs in times of pandemics.

Has Omicron Changed the Evolution of the Pandemic?

BACKGROUND: Variants of the SARS-CoV-2 virus carry differential risks to public health. The Omicron (B.1.1.529) variant, first identified in Botswana on November 11, 2021, has spread globally faster than any previous variant of concern. Understanding the transmissibility of Omicron is vital in the development of public health policy. OBJECTIVE: The aim of this study is to compare SARS-CoV-2 outbreaks driven by Omicron to those driven by prior variants of concern in terms of both the speed and magnitude of an outbreak. METHODS: We analyzed trends in outbreaks by variant of concern with validated surveillance metrics in several southern African countries. The region offers an ideal setting for a natural experiment given that most outbreaks thus far have been driven primarily by a single variant at a time. With a daily longitudinal data set of new infections, total vaccinations, and cumulative infections in countries in sub-Saharan Africa, we estimated how the emergence of Omicron has altered the trajectory of SARS-CoV-2 outbreaks. We used the Arellano-Bond method to estimate regression coefficients from a dynamic panel model, in which new infections are a function of infections yesterday and last week. We controlled for vaccinations and prior infections in the population. To test whether Omicron has changed the average trajectory of a SARS-CoV-2 outbreak, we included an interaction between an indicator variable for the emergence of Omicron and lagged infections. RESULTS: The observed Omicron outbreaks in this study reach the outbreak threshold within 5-10 days after first detection, whereas other variants of concern have taken at least 14 days and up to as many as 35 days. The Omicron outbreaks also reach peak rates of new cases that are roughly 1.5-2 times those of prior variants of concern. Dynamic panel regression estimates confirm Omicron has created a statistically significant shift in viral spread. CONCLUSIONS: The transmissibility of Omicron is markedly higher than prior variants of concern. At the population level, the Omicron outbreaks occurred more quickly and with larger magnitude, despite substantial increases in vaccinations and prior infections, which should have otherwise reduced susceptibility to new infections. Unless public health policies are substantially altered, Omicron outbreaks in other countries are likely to occur with little warning.

Lives and Livelihoods in Smallholder Farming Systems of Senegal: Impacts, Adaptation, and Resilience to COVID-19

The COVID-19 pandemic has had immediate and cascading impacts on global agricultural systems. In Senegal, the immediate impacts include inaccessibility of inputs due to disruption in markets and supply chains, availability of labor, and changes in crop and livestock management practices. To understand the range of impacts on the biophysical and socioeconomic dimensions of smallholder farming systems, a survey was designed to identify the risk factors, assess the impacts, and explore appropriate mitigation strategies. The survey was administered to 917 smallholder farmers in 14 regions of Senegal in collaboration with a national farmer's organization and the Senegalese Institute of Agricultural Research (ISRA). The sample was comprised of farmers (men and women) and was stratified in each region to ensure representation from all agroecological zones of the country. The survey examined variables such as access to inputs, ability to plant, impacts on yields, markets, labor, the gendered division of labor, food security, and community well-being. The survey response indicated that 77.7% of respondents experienced a reduction in access to inputs, 70.3% experienced a reduction in ability to plant crops during the planting season, 57.1% experienced a reduction in ability to rent farm machinery, and 69.2% reported a reduction in yields. Similar findings were observed for labor, market conditions, and adaptation measures to reduce the impacts on farming systems and household livelihoods. This study advances the research on characterizing risk factors, assessing the impacts, and designing mitigation strategies for strengthening smallholder farming systems resilience to future shocks.

Study Of Public Awareness About Immunity and Immunity Boosters Against Covid-19 In India

Since December 2019, the world has been under emergency due to novel coronavirus disease (Covid-19). Due to a lack of powerful preventative strategies (such as vaccinations) and pharmaceutical treatments, various preventive techniques have been implemented worldwide. Boosting the immune system is one of the most popular tools which has gained worldwide attention. However, the general public's impression is tainted by a lack of understanding of immune-boosting strategies and timetables. We carried out questionnaire-based research in India to assess people's actual knowledge of immunity and immunity-boosting techniques. The data analysis highlighted the idiographic convolutions in comprehending the various essential aspects affecting these people's immunity perception. The findings show that the general population understands the need to have a healthy immune system to combat any disease. More focus, however, is needed on false immunity-boosting claims and the careful implementation of immunity-boosting methods with professional advice. The study has the potential to address bottlenecks in reaching sustainable development objectives, notably United Nations' sustainable development goal three, which is Health and Well-being. Ensuring healthy lifestyles and encouraging well-being at all ages is critical to long-term development. The world is currently experiencing a global health catastrophe causing human distress, undermining the global economy, and upending the lives of billions of people worldwide. © The Electrochemical Society

In silico evaluation of the compounds of the ayurvedic drug, AYUSH-64, for the action against the SARS-CoV-2 main protease.

BACKGROUND: Outbreak of Corona Virus Disease in late 2019 (COVID-19) has become a pandemic global Public health emergency. Since there is no approved anti-viral drug or vaccine declared for the disease and investigating existing drugs against the COVID-19. OBJECTIVE: AYUSH-64 is an Ayurvedic formulation, developed and patented by Central Council of Research in Ayurvedic Sciences, India, has been in clinical use as anti-malarial, anti-inflammatory, anti-pyretic drug for few decades. Thus, the present study was undertaken to evaluate AYUSH-64 compounds available in this drug against Severe Acute Respiratory Syndrome-Corona Virus (SARS-CoV-2) Main Protease (Mpro; PDB ID: 6LU7) via in silico techniques. MATERIALS AND METHODS: Different molecular docking software's of Discovery studio and Auto Dock Vina were used for drugs from selected AYUSH-64 compounds against SARS-CoV-2. We also conducted 100 ns period of molecular dynamics simulations with Desmond and further MM/GBSA for the best complex of AYUSH-64 with Mpro of SARS-CoV-2. RESULTS: Among 36 compounds of four ingredients of AYUSH-64 screened, 35 observed to exhibits good binding energies than the published positive co-crystal compound of N3 pepetide. The best affinity and interactions of Akuammicine N-Oxide (from Alstonia scholaris) towards the Mpro with binding energy (AutoDock Vina) of -8.4 kcal/mol and Discovery studio of Libdock score of 147.92 kcal/mol. Further, molecular dynamics simulations with MM-GBSA were also performed for Mpro- Akuammicine N-Oxide docked complex to identify the stability, specific interaction between the enzyme and the ligand. Akuammicine N-Oxide is strongly formed h-bonds with crucial Mpro residues, Cys145, and His164. CONCLUSION: The results provide lead that, the presence of Mpro- Akuammicine N-Oxide with highest Mpro binding energy along with other 34 chemical compounds having similar activity as part of AYUSH-64 make it a suitable candidate for repurposing to management of COVID-19 by further validating through experimental, clinical studies.

Facemask Detection to Prevent COVID-19 Using YOLOv4 Deep Learning Model

The on-going global Covid-19 pandemic has impacted everyone's life. World Health organization (WHO) and Governments all over world have found that social distancing and donning a mask in public places has been instrumental in reducing the rate of COVID-19 transmission. Stepping out of homes in a face mask is a social obligation and a law mandate that is often violated by people and hence a face mask detection model that is accessible and efficient will aid in curbing the spread of disease. Detecting and identifying a face mask on an individual in real time can be a daunting and challenging task but using deep learning and computer vision, establish tech-based solutions that can help combat COVID-19 pandemic. In this paper, YOLOv4 deep learning model is designed and applied deep transfer learning approach to create a face mask detector which can be used in real time. GPU used was Google Collab to run the simulations and to draw inferences. Proposed implementation considered three types of data as input such as image dataset, video dataset and real time data for face mask detection. Performance parameters are tabulated and obtained mean average precision of 0.86, F1 score 0.77 for image dataset, 90 % accuracy for video dataset. And real time face mask detector with accuracy of 95%, it is successfully able to identify a person with and without facemask and report if they are wearing a face mask or not. © 2022 IEEE.

Prediction of Corona Virus Outbreak using Machine Learning

Predicting the corona virus can be divided into several phases, including a state-wide analysis that includes active, confirmed, cured, deaths as well as an increase in cases on a daily basis that includes each and every state of India as well as Union Territories. This also includes a thread of new corona virus cases from throughout India and forecasts the outbreak's conclusion in the next days. Machine learning algorithms like SVM, Linear Regression and Decision Tree Regression are used to analyze this data and improve this model's outcome. In this study, Jupyter notebook is used which provides an environment that is suited for machine learning principles. This technique provides for a comprehensive analysis of the virus's spread, including total and active cases, as well as forecasting future outbreaks and a weekly study epidemic. © 2021 IEEE

A Review on Wireless Telemedicine Technology Challenges and Possible Solution

The emergence of the Corona Virus (COVID-19) pandemic has resulted in a technological revolution bringing with it changes such as working from home, online shopping, online health consultation and many others were now taking place on a daily basis. One of the major impacts of COVID-19 was on public health due to travel restrictions and lockdowns restricting travel to medical clinics, stressing hospital capacity to the limit and throwing into strong relief the benefits of Telemedicine and Telehealth. This technological advancement has evolved over the past four decades with considerable success;however, challenges remain regarding data transfer, audiovisual streaming, power consumption, the impact of adverse climatic conditions on performance, area of coverage, security, privacy, and wearable sensors integration. This research aims to identify and critically analyse these issues. Prior research will be extracted from peer-reviewed journals published in scientific and medical data bases during 2017 and 2021. The resulting data will be compiled into graphic representations for further analysis. This paper makes a significant contribution to the body of knowledge in the field of wireless Telemedicine and Telehealth through detailed identification of the issues that are plaguing this field. © 2021 IEEE.

Co-infections and antimicrobial use in patients hospitalized with COVID-19

Background. In-hospital antimicrobial use among COVID-19 patients is widespread due to perceived bacterial and fungal co-infections. We aim to describe the incidence of these co-infections and antimicrobial use in patients hospitalized with COVID-19 to elucidate data for guiding effective antimicrobial use in this population. Methods. This retrospective study included all patients admitted with COVID-19 from January 1, 2020, to February 1, 2021 at any of the three teaching hospitals of the NYU Langone Health system. Variables of interest were extracted from the health system's de-identified clinical database. The nadir of hospital admissions between the first and second peaks of hospital admissions in the dataset was used to delineate the First Wave and Late Pandemic periods of observation. A cut-off of 48 hours after admission was used to differentiate Co-infections and Secondary infections respectively among isolates of clinically relevant bacterial or fungal pathogens in blood or sputum samples. Population statistics are presented as median with interquartile range (IQR) or total numbers with percentages. Results. 663 of 7,213 (9.2%) inpatients were found to have a positive bacterial or fungal culture of the respiratory tract or blood during the entire course of their initial admission at our hospitals for COVID-19. Positive respiratory cultures were found in 437 (6.1%) patients, with 94 (1.3%) being collected within 48 hours of admission. Blood culture positivity occurred in 333 patients (4.6%), with 115 (1.6%) identified within 48 hours of admission. Infection-free survival decreased with duration of hospitalization, with rate of secondary infections steadily rising after the second week of hospitalization as seen in Figure 1. 70.2% of inpatients received antimicrobials for a median duration of 6 antimicrobial days (IQR 3.0 - 12.0) per patient. A higher proportion of patients received antimicrobials in the first wave than in the late pandemic period (82.6% vs. 51.8%). Infection free survival represented as duration of admission in days on the X-axis, and proportion of admitted patients remaining infection-free in the Y-axis. The blue line represents blood cultures and the orange line represents sputum cultures. Conclusion. There was a very low incidence of co-infection with SARS-CoV-2 infection at admission. A longer duration of hospitalization was associated with an increased risk of secondary infections. Antimicrobial use far exceeded the true incidence and detection of co-infections in these patients.

Importation, circulation, and emergence of variants of SARS-CoV-2 in the South Indian state of Karnataka

Background: As the coronavirus disease 2019 (COVID-19) pandemic continues, the selection of genomic variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) associated with higher transmission, more severe disease, re-infection, and immune escape are a cause for concern. Such variants have been reported from the UK (B.1.1.7), South Africa (B.1.351) and, Brazil (P.1/B.1.1.28). We performed this study to track the importation, spread, and emergence of variants locally.

Clinical profile and outcome of coronavirus disease-2019 in kidney transplant recipients admitted to a tertiary care center: A retrospective study

Background: The mortality of kidney transplant recipients (KTR) affected with coronavirus disease-2019 (COVID-19) is reported to be higher than the general population. There is a scarcity of data on the pattern and outcome of COVID-19 in KTRs in developing country like India. Materials and Methods: It was a retrospective study conducted in a tertiary care center in North India. The detailed data on the Covid-19 affected KTR admitted to our center from March 2020 to March 2021 was obtained from computerized records. Clinical and biochemical characteristics of the survivors and nonsurvivors were studied. The factors affecting the mortality in this cohort were analyzed. Results: Of the 35 participants, 25 (71.4%) were males. The mean age was 53.06 & PLUSMN;11.84 years. Overall, mortality was 17.1% (Six out of 35). There was a significant difference in the oxygen saturation at presentation, computed tomography severity scores, level of inflammatory markers, level of serum albumin, and the absolute lymphocyte count (ALC) between the survivors and nonsurvivors (P < 0.05). On univariate regression analysis, serum C-reactive protein, ferritin, albumin, and ALC were found to be significantly predicting mortality in COVID-19 affected KTR. Conclusions: Mortality rate in COVID-19 affected KTR is higher than in the general population. Clinical, biochemical, and radiological parameters can be helpful in predicting the adverse outcome.

COVID-19 infections in pediatric hematology oncology patients in Louisiana

Purpose of Study The majority of documented SARS-CoV2 infections in children have been mild illnesses. The highest frequency of infection is documented in children between the ages of 5 -17 years;with the incidence of SARS-CoV2 being the highest in adolescents aged 12-17 years. Severe respiratory complications and a multi-system inflammatory syndrome (MIS-C) have been documented in pediatrics. There is very limited information about pediatric hematology and oncology patients in the United States, actively undergoing therapy, and how SARS-CoV2 affects them. Louisiana was an early 'hotspot' for SARS-CoV2 with its first documented infection on March 9, 2020. We present our institutional experience with SARS-CoV2 and pediatric hematology-oncology patients. Methods Used A retrospective chart review was performed on all pediatric hematology-oncology patients who were actively being treated at Children's Hospital of New Orleans between March 9, 2020, through December 15, 2020. Any patient who had a positive SARS-CoV2 test was included in the chart review. Information including demographics, signs, and symptoms at the time of testing, hospitalization, medications, diagnosis, and treatment was obtained. The institutional review board at Louisiana State University Health Sciences Center and Children's Hospital of New Orleans approved this study. Summary of Results Between March 9, 2020 and December 15, 2020, 15,404 patients were tested for SARS-CoV2 at Children's Hospital of New Orleans;628 children tested positive. Ten of those children had a pediatric hematological or oncological diagnosis. The mean age of the pediatric hematology- oncology patients was 7.9 years, and 80% were female. Ten percent of the patients identified as Hispanic. Forty percent were African American. Of the 10, four children (40%) had a diagnosis of acute lymphoblastic leukemia, and all were actively undergoing chemotherapy. One of the ten total children had undergone a bone marrow transplant. Five (50%) were hospitalized;2 (20%) with severe infections requiring PICU admission and 3 (30%) patients were treated for MIS-C with SARS-CoV2 specific therapy including Remdesivir, steroids, and Tocilizumab. One of our patients died from SARSCoV2 related complications. Conclusions Pediatric hematology-oncology patients are a heterogeneous group of patients, and little was known about how SARS-CoV2 would affect these patients. Of the 15,404 patients tested for SARS-CoV2 at CHNOLA, there were 628 that tested positive between March 9, 2020, and December 15, 2020. 1.6% of those had an oncology or hematology diagnosis. Most of our pediatric hematology oncology patients did not require hospitalization and did not require treatment. There was one patient who died of SARS-CoV2 related complications.

Impacts of the COVID-19 pandemic on vegetable production systems and livelihoods: Smallholder farmer experiences in Burkina Faso.

At the onset of COVID-19, researchers quickly recognized the need for research on the consequences of the pandemic for agricultural and food systems, both in terms of immediate impacts on access to inputs and labor, disruptions in transportation and markets, and the longer-term implications on crop productivity, income, and livelihoods. Vegetable production and supply chains are particularly vulnerable due to the perishable nature of the products and labor-intensive production practices. The purpose of this study was to understand the impacts of COVID-19 on vegetable production in Burkina Faso in terms of both the biophysical aspects such as yields and access to inputs and socioeconomic aspects such as access to labor, markets, and social services. A survey was developed to better understand smallholder farmer experiences regarding the impacts of COVID-19 on their vegetable production systems and social well-being. The survey was administered (between August and October 2020) with smallholder farmers (n = 605) in 13 administrative regions covering all agroecological zones of Burkina Faso. The survey results clearly show impacts of COVID-19 on vegetable systems, including a reduction in access to inputs, a reduction in yields, a loss of income, reduced access to local and urban markets, reduced access to transportation, and an increase in post-harvest loss. Market access, distribution, and disruptions were a major shock to the system. Results also showed an increase in women's labor in the household, and for youth, an increase in unemployment, job loss, and concerns of poverty. Finally, food security and social supports were highlighted as major issues for resilience and livelihoods. The results from this survey should be helpful to policymakers and researchers to develop policies and strategies to minimize the negative impacts of this ongoing pandemic on the agri-food systems and support smallholder farmers to overcome stress caused by COVID-19.