Spontaneously Resolving Pneumoperitoneum and Pneumomediastinum: A Report of Two Cases.

We present here an interesting case report of two patients with spontaneous pneumomediastinum and iatrogenic pneumoperitoneum. The patients were assessed and queried following a chest X-ray abnormality and query based on the history of recent urological procedures on a background of awaiting gastro-oesophageal surgery at a tertiary centre respectively. Although these patients were successfully managed with the best supportive approach and periodic imaging review, it remains important to be aware that fatalities have been reported in the literature. We hope this case report will help those involved in the care of the patient to be aware of these conditions as differentials when history points towards episodes of coughing or recent surgical input.

Enhancing agricultural automation through weather invariant soil parameter prediction using machine learning.

Soil parameters are crucial aspects in increasing agricultural production. Even though Bangladesh is heavily dependent on agriculture, little research has been done regarding its automation. And a vital aspect of agricultural automation is predicting soil parameters. Generally, sensors relating to soil parameters are quite expensive and are often done in a controlled environment such as a greenhouse. However, a large scale implementation of such expensive sensors is not very feasible. This work tries to find an inexpensive solution towards predicting soil parameters such as soil moisture and temperature, both of which are crucial to the growth of crops. We focus on finding a robust relation between the above mentioned soil parameters with the nearby weather parameters such as humidity and temperature, irrespective of the weather. We apply different machine learning models like multilayer perceptron (MLP), random forest, etc. to predict the soil parameters, given the humidity and temperature of the surrounding environment. For all the experiments we have used a custom made dataset, which contains around 9000 datapoints of soil moisture & temperature, ambient humidity & temperature. The data has been collected in an uncontrolled agriculture bed via inexpensive sensors. Our results show that XGBoost regressor achieves the best results with an R2 score of 0.93 and 0.99 for soil moisture and soil temperature data respectively. This suggests very high correlation between the weather parameters and soil parameters. The model also portrayed a very low root mean squared error and mean absolute error of 0.037 & 0.015 for soil moisture and 0.001 & 0.0008 for soil temperature. Our results show that it is indeed possible to find the soil parameters from the corresponding weather, which will have great impact on mass agricultural automation. The dataset has been made publicly available at https://github.com/Nadimulhaque0403/Soil_parameter_prediction_dataset.

Boosting edgeR (Robust) by dealing with missing observations and gene-specific outliers in RNA-Seq profiles and its application to explore biomarker genes for diagnosis and therapies of ovarian cancer.

The edgeR (Robust) is a popular approach for identifying differentially expressed genes (DEGs) from RNA-Seq profiles. However, it shows weak performance against gene-specific outliers and is unable to handle missing observations. To address these issues, we proposed a pre-processing approach of RNA-Seq count data by combining the iLOO-based outlier detection and random forest-based missing imputation approach for boosting the performance of edgeR (Robust). Both simulation and real RNA-Seq count data analysis results showed that the proposed edgeR (Robust) outperformed than the conventional edgeR (Robust). To investigate the effectiveness of identified DEGs for diagnosis, and therapies of ovarian cancer (OC), we selected top-ranked 12 DEGs (IL6, XCL1, CXCL8, C1QC, C1QB, SNAI2, TYROBP, COL1A2, SNAP25, NTS, CXCL2, and AGT) and suggested hub-DEGs guided top-ranked 10 candidate drug-molecules for the treatment against OC. Hence, our proposed procedure might be an effective computational tool for exploring potential DEGs from RNA-Seq profiles for diagnosis and therapies of any disease.

Controlling the counterintuitive optical repulsive thrust of nano dimers with counter propagating type waves and background medium.

This work focuses on the utilization of counter-propagating plane waves for optical manipulation, which provides a unique approach to control the behavior of Rayleigh and Dipolar nanoparticles immersed in a homogeneous or heterogeneous medium. Our study presents an interesting finding of a repulsive force between plasmonic-chiral heterodimers where the particles move away from each other in both near and far field regions. Interestingly, this repulsive thrust supports the wave like nature of light for the case of homogeneous background but particle type nature of light for heterogenous background. At first, we have investigated the theory underlying the optical trapping of the chiral particle and the impact of this phenomenon on the overall repulsive behavior of the heterodimers placed in air (homogeneous) background. After that, our proposed set-up has further been investigated putting in air-water interface (heterogenous background) and by varying light angle only a little bit. Our observation for this interface case is suggesting the transfer of Minkowski momentum of photon to each optically pulled Rayleigh or dipolar particle of the dimer set, which ultimately causes a broad-band giant repulsive thrust of the dimers. However, in absence of the other particle in the cluster, a single half-immersed particle does not experience the pulling force for the broad-band spectrum. The 'common' reason of the observed repulsive thrust of the dimers for both the aforementioned cases has been attributed to "modified" longitudinal Optical Binding Force (OBF). Technically, this work may open a new way to control the repulsion and attraction between the nanoparticles both in near and far field regions by utilizing the background and the counter-propagating waves. We also believe that this work manifests a possible simple set-up, which will support to observe a background dependent wave 'or' particle nature of light experimentally.

Synergistic Effect of Allium-like Ni9 S8 & Cu7 S4 Electrodeposited on Nickel Foam for Enhanced Water Splitting Activity.

This study explores a water-splitting activity using a biphasic electrodeposited electrode on nickel foam (NF). The *Ni9 S8 /Cu7 S4 /NF electrode with citric acid reduction exhibits superior OER (oxygen evolution reaction) and HER (hydrogen evolution reaction) performance with reduced overpotential and a steeper Tafel slope. The *Ni9 S8 /Cu7 S4 /NF electrode displays the ultra-low overpotential value of 212 mV for OER and 109 mV for HER at the current density of 10 mA cm-2 . The Tafel slope of 25.4 mV dec-1 for OER and 108 mV dec-1 for HER was found from that electrode. The maximum electrochemical surface area (ECSA), lowest series resistance and lowest charge transfer resistance are found in citric acid reduced electrode, showing increased electrical conductivity and quick charge transfer kinetics. Remarkably, the *Ni9 S8 /Cu7 S4 /NF electrode demonstrated excellent stability for 80 hours in pure water splitting and 20 hours in seawater splitting. The synergistic effect of using bimetallic (Cu&Ni) sulfide and enhanced electrical conductivity of the electrode are caused by reduction of metal sulfide into metallic species resulting in improved water splitting performance.

Metal organic framework derived NiO x nanoparticles for application as a hole transport layer in perovskite solar cells.

NiO x as a hole transport layer (HTL) has gained a lot of research interest in perovskite solar cells (PSCs), owing to its high optical transmittance, high power conversion efficiency, wide band-gap and ease of fabrication. In this work, four different nickel based-metal organic frameworks (MOFs) using 1,3,5-benzenetricarboxylic acid (BTC), terephthalic acid (TPA), 2-aminoterephthalic acid (ATPA), and 2,5-dihydroxyterephthalic acid (DHTPA) ligands respectively, have been employed as precursors to synthesize NiO x NPs. The employment of different ligands was found to result in NiO x NPs with different structural, optical and morphological properties. The impact of calcination temperatures of the MOFs was also studied and according to field emission scanning electron microscopy (FESEM), all MOF-derived NiO x NPs exhibited lower particle size at lower calcination temperature. Upon optimization, Ni-TPA MOF derived NiO x NPs calcined at 600 °C were identified to be the best for hole transport layer application. To explore the photovoltaic performance, these NiO x NPs have been fabricated as a thin film and its structural, optical and electrical characteristics were analyzed. According to the findings, the band energy gap (E g) of the fabricated thin film has been found to be 3.25 eV and the carrier concentration, hole mobility and resistivity were also measured to be 6.8 × 1014 cm-3; 4.7 × 1014 Ω cm and 2.0 cm2 V-1 s-1, respectively. Finally, a numerical simulation was conducted using SCAPS-1D incorporating the optical and electrical parameters from the thin film analysis. FTO/TiO2/CsPbBr3/NiO x /C has been utilized as the device configuration which recorded an efficiency of 13.9% with V oc of 1.89 V, J sc of 11.07 mA cm-2, and FF of 66.6%.

Temporal and spatial relationships of CrAssphage and enteric viral and bacterial pathogens in wastewater in North Carolina.

Enteric disease remains one of the most common concerns for public health, particularly when it results from human exposure to surface and recreational waters contaminated with wastewater. Characterizing the temporal and spatial variation of enteric pathogens prevalent in wastewater is critical to develop approaches to mitigate their distribution in the environment. In this study, we aim to characterize pathogen variability and test the applicability of the human-associated wastewater indicator crAssphage as an indicator of enteric viral and bacterial pathogens. We conducted weekly samplings for 14 months from four wastewater treatment plants in North Carolina, USA. Untreated wastewater samples were processed using hollow fiber ultrafiltration, followed by secondary concentration methods. Adenovirus, norovirus, enterovirus, Salmonella, Shiga toxin 2 (stx2), Campylobacter, and crAssphage were measured by quantitative polymerase chain reaction (qPCR) and reverse transcriptase (rt)-qPCR. Our results revealed significant correlations between crAssphage and human adenovirus, enterovirus, norovirus, Salmonella, and Campylobacter (p<0.01). Pathogens and crAssphage concentrations in untreated wastewater showed distinct seasonal patterns, with peak concentrations of crAssphage and viral pathogens in fall and winter, while bacterial pathogens showed peaked concentrations in either winter (Campylobacter), fall (Salmonella), or summer (stx2). This study enhances the understanding of crAssphage as an alternative molecular indicator for both bacterial and viral pathogens. The findings of this study can also inform microbial modeling efforts for the prediction of the impact of wastewater pathogens on surface waters due to increased flooding events and wastewater overflows associated with climate change.

Synthesis and biophysical properties of tetravalent PEG-conjugated antisense oligonucleotide.

This study was aimed at developing a novel platform for tetravalent conjugation of 4-arm polyethylene glycol (PEG) with an antisense oligonucleotide (ASO). The ASO technology has several limitations, such as low cellular uptake, poor nuclease stability, and short half-life. PEG-conjugated ASOs may result in an improvement in the pharmacokinetic behavior of the drug. Moreover, PEGylation can reduce enzymatic degradation and renal excretion of the conjugates, thereby, increasing its blood stability and retention time. In this study, we successfully synthesized PEG-ASO conjugate consisting of 4-arm-PEG and four molecules of ASO (4-arm-PEG-tetra ASO). Its hybridization ability with complementary RNA, enzymatic stability, and in vitro gene silencing ability were evaluated. No significant difference in hybridization ability was observed between 4-arm-PEG-tetra ASO and the parent ASO. In addition, gene silencing activity of the 4-arm-PEG-tetra ASO was observed in vitro. However, the in vitro activity of the 4-arm-PEG-tetra ASO was slightly reduced as that of the parent ASO. Moreover, the 4-arm-PEG-tetra ASO showed appreciable stability in cellular extract, suggesting that it hybridizes with mRNA in its intact form, without being cleaved in the cell, and exhibits ASO activity.

Developing a Low-Cost IoT-Based Remote Cardiovascular Patient Monitoring System in Cameroon.

(1) Background: Cameroonians are exposed to poor health services, more so citizens with cardiovascular-related diseases. The global high cost of acquiring healthcare-related technologies has prompted the government and individuals to promote the need for local research and the development of the health system. (2) Objectives: The main goal of this study is to design and develop a low-cost cardiovascular patient monitoring system (RPM) with wireless capabilities that could be used in any region of Cameroon, accessible, and very inexpensive, that are able to capture important factors, well reflecting the patient's condition and provide alerting mechanisms. (3) Method: Using the lean UX process from the Gothelf and Seiden framework, the implemented IoT-based application measures the patients' systolic, diastolic, and heart rates using various sensors, that are automated to record directly to the application database for analysis. The validity of the heuristic evaluation was examined in an ethnographic study of paramedics using a prototype of the system in their work environment. (4) Results: We obtained a system that was pre-tested on demo patients and later deployed and tested on seven real human test subjects. The users' task performances partially verified the heuristic evaluation results. (5) Conclusions: The data acquired by the sensors have a high level of accuracy and effectively help specialists to properly monitor their patients at a low cost. The proposed system maintains a user-friendliness as no expertise is required for its effective utilization.

Methotrexate therapy followed by laparotomy to manage a viable first-trimester cesarean scar ectopic pregnancy in a low-resource setting: A case report.

Cesarean scar ectopic pregnancy (CSEP) is rare, occurring in 1:1800 to 1:2625 pregnancies. It is classified into two types: endogenous, which grows inside the uterine cavity; and exogenous, which grows outward, toward the bladder. Both types are associated with increased maternal morbidity and mortality. The case report describes a 25-year-old woman with a viable first-trimester CSEP treated with both methotrexate and operative resection. Management was in a low-resource setting.

Side Effects of COVID-19 Vaccines and Perceptions about COVID-19 and Its Vaccines in Bangladesh

IntroductionOne of the primary reasons for hesitancy in taking COVID-19 vaccines is the fear of side effects. This study primarily aims to inspect the potential side effects of the COVID-19 vaccines circulated in Bangladesh. MethodsThe study was a cross-sectional anonymous online survey conducted across Bangladesh. Data were collected from December 2 to December 26, 2021. The study included consenting (informed) Bangladeshi individuals aged 12 and above who had received at least one dose of the COVID-19 vaccines. Analyses were carried out through exploratory analysis, Chi-square test, and logistic regression. ResultsA total of 1,180 (males-63.89%, age 50 years or over-65.4%, rural-52.86%) vaccinated people participated in the study. Less than half of the participants (39.48%) reported at least one side effect after receiving their COVID-19 vaccine. Injection-site pain, fever, headache, redness/swelling at the injection site, and lethargy were the most commonly reported adverse effects, all of which were mild and lasted 1-3 days. Side effects were most prevalent (about 80%) among individuals who received Pfizer-BioNTech and Moderna vaccines and were least common among those who received Sinopharm and Sinovac vaccines (21%-28%). When compared to the Sinopharm vaccines, the OxfordAstraZeneca, Pfizer-BioNTech, and Moderna vaccines were 4.51 (95% CI: 2.53-8.04) times, 5.37 (95% CI: 2.57-11.22) times, and 4.28 (95% CI: 2.28-8.05) times likelier to produce side effects. Furthermore, males, those over 50 years old, urban dwellers, smokers, and those with underlying health issues had a considerably increased risk of developing side effects. A lack of confidence in vaccines efficacy and a substantial level of hesitancy in allowing children (age five years or over) and older people (70 years or over) to receive COVID-19 vaccines were also observed. ConclusionSide effects of COVID-19 vaccines are minimal, demonstrating their safety. Further studies are required to establish the efficacy of the vaccines. What is already known?Significant COVID-19 vaccine hesitancy has been observed globally, mainly due to vaccine safety and efficacy concerns. Until now, most of the data on COVID-19 vaccine safety and efficacy have been published in manufacturer-funded trials that adhere to regulatory criteria and are monitored by third parties. A lack of independent studies on vaccine safety may have a detrimental effect on vaccine acceptance, which should be intensified to combat the deadly virus. What are the new findings?After receiving the COVID-19 vaccines, less than half of the subjects experienced at least one side effect. The side effects were mild and regular and lasted 1-3 days only. Side effects were most prevalent among individuals who received Pfizer-BioNTech and Moderna vaccines and were least common among those who received Sinopharm and Sinovac vaccines. A lack of confidence in vaccines efficacy and a substantial level of hesitancy in allowing children (age five years or over) and older people (70 years or over) to receive COVID-19 vaccines were also observed. What do the new findings imply?Side effects of COVID-19 vaccines are minimal and regular, demonstrating their safety. Efforts should be made to disseminate such findings among marginalized people worldwide who showed greater vaccine hesitancy.

Tracking the temporal variation of COVID-19 surges through wastewater-based epidemiology during the peak of the pandemic: A six-month long study in Charlotte, North Carolina.

The global spread of SARS-CoV-2 has continued to be a serious concern after WHO declared the virus to be the causative agent of the coronavirus disease 2019 (COVID-19) a global pandemic. Monitoring of wastewater is a useful tool for assessing community prevalence given that fecal shedding of SARS-CoV-2 occurs in high concentrations by infected individuals, regardless of whether they are asymptomatic or symptomatic. Using tools that are part of wastewater-based epidemiology (WBE) approach, combined with molecular analyses, wastewater monitoring becomes a key piece of information used to assess trends and quantify the scale and dynamics of COVID-19 infection in a specific community, municipality, or area of service. This study investigates a six-month long SARS-CoV-2 RNA quantification in influent wastewater from four municipal wastewater treatment plants (WWTP) serving the Charlotte region of North Carolina (NC) using both RT-qPCR and RT-ddPCR platforms. Influent wastewater was analyzed for the nucleocapsid (N) genes N1 and N2. Both RT-qPCR and RT-ddPCR performed well for detection and quantification of SARS-CoV-2 using the N1 target, while for the N2 target RT-ddPCR was more sensitive. SARS-CoV-2 concentration ranged from 103 to 105 copies/L for all four plants. Both RT-qPCR and RT-ddPCR showed a significant positive correlation between SARS-CoV-2 concentrations and the 7-day rolling average of clinically reported COVID-19 cases when lagging 5 to 12 days (ρ = 0.52-0.92, p < 0.001-0.02). A major finding of this study is that RT-qPCR and RT-ddPCR generated SARS-CoV-2 data that was positively correlated (ρ = 0.569, p < 0.0001) and can be successfully used to monitor SARS-CoV-2 signals across the WWTP of different sizes and metropolitan service functions without significant anomalies.

Zoonotic diseases appeared to be a major hurdle to successful deer farming in Bangladesh.

BACKGROUND AND AIM: Due to the diversified lifestyle and fancy ecology associated with Chitra deer (Axis axis), deer farming has become popular in Bangladesh. Diseases may be the common constrain of successful deer farming. This study aims to investigate the pathological, bacteriological, and nucleic acid based technologies to identify specific causes of morbidity and mortality of captive deer. MATERIALS AND METHODS: Two deer farms and a park deer (designated as farm A, B, and C) entailing 87, 54, and 20 deer, respectively, showed illness and death constitute the study materials. A total of 42 deer died during this investigation. Following death, routine post-mortem examination, histopathology, impression smear staining, isolation, and identification of bacteria were carried out. Polymerase chain reaction (PCR) and reverse transcription PCR were carried out to safeguard the etiology. RESULTS: Clinically, farm A and B showed the acute phase of illness and park deer showed chronic illness. Case fatality rates were 90%, 92%, and 100% in farms A, B, and C deer, respectively. Pasteurella multocida and Streptococcus pneumoniae were identified from the visceral organs of farm A deer. Farm B deer was infected with Clostridium perfringens type A. Park deer was infected with Mycobacterium tuberculosis and hydatid cyst. CONCLUSION: The infectivity in farm A deer was due to stress as induced by punishing weather. The infectivity in farm B deer was due to feeding a higher volume of protein in the diet. The park C deer may optate infection from companion man and animals living around. The diseases of captive deer identified mainly were zoonotic. It needs extensive veterinary services and specialized technologies to identify these diseases, monitor the infectivity and eliminate the public health important diseases at early onset.

A non-inferiority trial comparing two recombinant vaccines (Hepa-B vs. Engerix-B) for hepatitis B among adults in Dhaka, Bangladesh.

Worldwide Hepatitis B is known as one of the imperative causes of mortality and morbidity as well as occupational health hazard among health workers. Bangladesh is intermediate endemic country for Hepatitis B infection for which the government has introduced hepatitis B vaccination into the Expanded Programme on Immunization (EPI) nationwide since 2009 for new born children. However, the people who were born before 2009, was dependent on imported hepatitis B vaccine as there was no locally manufactured hepatitis B vaccine in Bangladesh. Hence, we conducted a randomized observer blinded non-inferiority clinical trial to assess the immunogenicity and safety of the locally manufactured Hepa-B vaccine in comparison with World Health Organization prequalified Engerix-B vaccine. Total 158 eligible adult participants were enrolled in this study with mean age of 30 and 29 years old in Hepa-B and Engerix-B groups, respectively. Both the vaccines were administered intramuscularly at 0, 1 and 6 months schedule. Baseline and post vaccination anti-HBs titers were measure at different time points. Seroconversion rate post three doses of Hepa-B vaccine was 98.67% similar to the comparator Engerix-B vaccine which was 100%. The geometric mean test ratios of both vaccines at all analysis time points were found > 0.5 predefined non-inferiority margin. Soreness at the injection site was the most common symptom for both the vaccines which resolved without any complication. No serious adverse event was reported throughout the study period. These results suggest that locally manufactured hepatitis B vaccine 'Hepa-B' vaccine is non-inferior to the well-known licensed 'Engerix-B' vaccine. ClinicalTrials.gov NCT03627507.

Tracking the temporal variation of COVID-19 surges through wastewater-based epidemiology during the peak of the pandemic: a six-month long study in Charlotte, North Carolina

The global spread of SARS-CoV-2 has continued to be a serious concern after WHO declared the virus the causative agent of the coronavirus disease 2019 (COVID-19) a global pandemic. Monitoring of wastewater is a useful tool for assessing community prevalence given that fecal shedding of SARS-CoV-2 occurs in high concentrations by infected individuals, regardless of whether they are asymptomatic or symptomatic. Using tools that are part of the wastewater-based epidemiology (WBE) approach, combined with molecular analyses, wastewater monitoring becomes a key piece of information used to assess trends and quantify the scale and dynamics of COVID-19 infection in a specific community, municipality, or area of service. This study investigates a six-month long SARS-CoV-2 RNA quantification in influent wastewater from four municipal wastewater treatment plants (WWTP) serving the Charlotte region of North Carolina (NC) using both RT-qPCR and RT-ddPCR platforms. Influent wastewater was analyzed for the nucleocapsid (N) genes N1 and N2. Both RT-qPCR and RT-ddPCR performed well for detection and quantification of SARS-CoV-2 using the N1 target, while for the N2 target RT-ddPCR was more sensitive. SARS-CoV-2 concentration ranged from 103 to105 copies/L for all four plants. Both RT-qPCR and RT-ddPCR showed a significant moderate to a strong positive correlation between SARS-CoV-2 concentrations and the 7-day rolling average of clinically reported COVID-19 cases using a lag that ranged from 7 to 12 days. A major finding of this study is that despite small differences, both RT-qPCR and RT-ddPCR performed well for tracking the SARS-CoV-2 virus across WWTP of a range of sizes and metropolitan service functions.

Performance evaluation of virus concentration methods for implementing SARS-CoV-2 wastewater based epidemiology emphasizing quick data turnaround.

Wastewater based epidemiology (WBE) has drawn significant attention as an early warning tool to detect and predict the trajectory of COVID-19 cases in a community, in conjunction with public health data. This means of monitoring for outbreaks has been used at municipal wastewater treatment centers to analyze COVID-19 trends in entire communities, as well as by universities and other community living environments to monitor COVID-19 spread in buildings. Sample concentration is crucial, especially when viral abundance in raw wastewater is below the threshold of detection by RT-qPCR analysis. We evaluated the performance of a rapid ultrafiltration-based virus concentration method using InnovaPrep Concentrating Pipette (CP) Select and compared this to the established electronegative membrane filtration (EMF) method. We evaluated sensitivity of SARS-CoV-2 quantification, surrogate virus recovery rate, and sample processing time. Results suggest that the CP Select concentrator is more efficient at concentrating SARS-CoV-2 from wastewater compared to the EMF method. About 25% of samples that tested negative when concentrated with the EMF method produced a positive signal with the CP Select protocol. Increased recovery of the surrogate virus control using the CP Select confirms this observation. We optimized the CP Select protocol by adding AVL lysis buffer and sonication, to increase the recovery of virus. Sonication increased Bovine Coronavirus (BCoV) recovery by 19%, which seems to compensate for viral loss during centrifugation. Filtration time decreases by approximately 30% when using the CP Select protocol, making this an optimal choice for building surveillance applications where quick turnaround time is necessary.

Performance evaluation of virus concentration methods for implementing SARS-CoV-2 Wastewater-based epidemiology emphasizing quick data turnaround.

Wastewater based epidemiology (WBE) has drawn significant attention as an early warning tool to detect and predict the trajectory of COVID-19 cases in a community, in conjunction with public health data. This means of monitoring for outbreaks has been used at municipal wastewater treatment centers to analyze COVID-19 trends in entire communities, as well as by universities and other community living environments to monitor COVID-19 spread in buildings. Sample concentration is crucial, especially when viral abundance in raw wastewater is below the threshold of detection by RT-qPCR analysis. We evaluated the performance of a rapid ultrafiltration-based virus concentration method using InnovaPrep Concentrating Pipette (CP) Select and compared this to the established electronegative membrane filtration (EMF) method. We evaluated sensitivity of SARS-CoV-2 quantification, surrogate virus recovery rate, and sample processing time. Results suggest that the CP Select concentrator is more efficient at concentrating SARS-CoV-2 from wastewater compared to the EMF method. About 25% of samples that tested negative when concentrated with the EMF method produced a positive signal with the CP Select protocol. Increased recovery of the surrogate virus control using the CP Select confirms this observation. We optimized the CP Select protocol by adding AVL lysis buffer and sonication, to increase the recovery of virus. Sonication increased Bovine Coronavirus (BCoV) recovery by 19%, which seems to compensate for viral loss during centrifugation. Filtration time decreases by approximately 30% when using the CP Select protocol, making this an optimal choice for building surveillance applications where quick turnaround time is necessary.

Implementing building-level SARS-CoV-2 wastewater surveillance on a university campus.

The COVID-19 pandemic has been a source of ongoing challenges and presents an increased risk of illness in group environments, including jails, long-term care facilities, schools, and residential college campuses. Early reports that the SARS-CoV-2 virus was detectable in wastewater in advance of confirmed cases sparked widespread interest in wastewater-based epidemiology (WBE) as a tool for mitigation of COVID-19 outbreaks. One hypothesis was that wastewater surveillance might provide a cost-effective alternative to other more expensive approaches such as pooled and random testing of groups. In this paper, we report the outcomes of a wastewater surveillance pilot program at the University of North Carolina at Charlotte, a large urban university with a substantial population of students living in on-campus dormitories. Surveillance was conducted at the building level on a thrice-weekly schedule throughout the university's fall residential semester. In multiple cases, wastewater surveillance enabled the identification of asymptomatic COVID-19 cases that were not detected by other components of the campus monitoring program, which also included in-house contact tracing, symptomatic testing, scheduled testing of student athletes, and daily symptom reporting. In the context of all cluster events reported to the University community during the fall semester, wastewater-based testing events resulted in the identification of smaller clusters than were reported in other types of cluster events. Wastewater surveillance was able to detect single asymptomatic individuals in dorms with resident populations of 150-200. While the strategy described was developed for COVID-19, it is likely to be applicable to mitigation of future pandemics in universities and other group-living environments.

Exploring the Behavioral Determinants of COVID-19 Vaccine Acceptance among an Urban Population in Bangladesh: Implications for Behavior Change Interventions

BackgroundWhile vaccines ensure individual protection against COVID-19 infection, delay in receipt or refusal of vaccines will have both individual and community impacts. The behavioral factors of vaccine hesitancy or refusal are a crucial dimension that need understanding to implicate appropriate interventions. The aim of this study was to assess the behavioral determinants of COVID-19 vaccine acceptance and to provide recommendations to increase the uptake of COVID-19 vaccines in Bangladesh. MethodsWe employed a Barrier Analysis (BA) approach to examine twelve potential behavioral determinants (drawn from the Health Belief Model and Theory of Reasoned Action [TRA]) of intended vaccine acceptance. We conducted 45 interviews with those who intended to take the vaccine (Acceptors) and another 45 interviews with those who did not have that intention (Non-acceptors). We performed data analysis to find statistically significant differences and to identify which beliefs were most highly associated with acceptance and non-acceptance with COVID-19 vaccines. ResultsCOVID-19 vaccine Acceptors in Dhaka were different from Non-acceptors in terms of many of their beliefs and responses. The behavioral determinants associated with the behavior included perceived social norms, perceived safety of COVID-19 vaccines and trust in them, perceived risk/susceptibility, perceived self-efficacy, perceived positive and negative consequences, perceived action efficacy, perceived severity of COVID-19, access, and perceived divine will. In line with the Health Belief Model, beliefs about the disease itself were highly correlated with vaccine acceptance, although not the only determinant. Other responses of Acceptors provide clues such as providing vaccination through government health facilities, schools, and kiosks, and having vaccinators maintain proper COVID-19 health and safety protocols as to ways to make it easier to boost acceptance. ConclusionAn effective behavior change strategy for COVID-19 vaccines uptake will need to address multiple beliefs and behavioral determinants, reducing barriers and leveraging enablers identified in this study. The national plans on COVID-19 vaccination should adopt culturally and community label acceptable and appropriate evidence-based behavior change interventions strategies to promote high vaccination coverage and acceptance in all societal structures across the country.

Implementing Building-Level SARS-CoV-2 Wastewater Surveillance on a University Campus

The COVID-19 pandemic has been a source of ongoing challenges and presents an increased risk of illness in group environments, including jails, long term care facilities, schools, and, of course, residential college campuses. Early reports that the SARS-CoV-2 virus was detectable in wastewater in advance of confirmed cases sparked widespread interest in wastewater based epidemiology (WBE) as a tool for mitigation of COVID-19 outbreaks. One hypothesis was that wastewater surveillance might provide a cost-effective alternative to other more expensive approaches such as pooled and random testing of groups. In this paper, we report the outcomes of a wastewater surveillance pilot program at the University of North Carolina at Charlotte, a large urban university with a substantial population of students living in on-campus dormitories. Surveillance was conducted at the building level on a thrice-weekly schedule throughout the universitys fall residential semester. In multiple cases, wastewater surveillance enabled identification of asymptomatic COVID-19 cases that were not detected by other components of the campus monitoring program, which also included in-house contact tracing, symptomatic testing, scheduled testing of student athletes, and daily symptom reporting. In the context of all cluster events reported to the University community during the fall semester, wastewater-based testing events resulted in identification of smaller clusters than were reported in other types of cluster events. Wastewater surveillance was able to detect single asymptomatic individuals in dorms with total resident populations of 150-200. While the strategy described was developed for COVID-19, it is likely to be applicable to mitigation of future pandemics in universities and other group-living environments.