POND SIZE AFFECTS ABUNDANCE AND DIVERSITY OF AVIAN SPECIES

Wetlands provide great important ecosystem services and serve as refugia for biodiversity. Birds are bio-indicators of environmental health and utilize the wetland ecosystems. Wetlands and birds face many threats from anthropogenic activities in the forms of degradation and habitat loss. This research aimed at assessing the effects of pond size on avian abundance and diversity in a wetland in Jos south Local Government Area of Plateau state, ten (10) ponds were sampled using point count method. Each pond had two (2) points which were visited twice daily (morning and afternoon) each. A total of three thousand, four hundred and forty-eight (3448) individual birds consisting of 97 species belonging to fifty- one (51) families were recorded. Intra-African migrants such as Didric cuckoo (Chrysococcyx caprius) and yellow-billed kite (Milvus aegyptius) were recorded. Species diversity and abundance were tested against the size of the pond, depth of the pond and vegetation cover on and around the pond to determine the factors that best depicts the diversity and abundance of avian species at the Rennajj fish farm. Pond size was a significant predictor of bird abundance (P< 0.01) and had a slight positive effect on the diversity of avian species which was not statistically significant at (P>0.05). Depth of the pond had no significant effect on both bird abundance and species diversity (p>0.05). Vegetation parameters such as shrubs and saplings had positive effect while vegetation on water and number of trees had negative relationship at (p<0.001) on the abundance of birds, vegetation on the water had a negative relationship at (p<0.001) with the diversity of bird species. Wetland ecosystems should be protected from excessive human activities as they host wealth of biodiversity

Facial Emotion Recognition with Sparse Coding Descriptor

With the Corona Virus Disease 2019 (COVID-19) global pandemic ravaging the world, all sectors of life were affected including education. This led to many schools taking distance learning through the use of computer as a safer option. Facial emotion means a lot to teacher’s assessment of his performance and relation to his students. Researchers has been working on improving the face monitoring and human machine interface. In this paper we presented different types of face recognition methods which include: Principal component analysis (PCA); Speeded Up Robust Features (SURF); Local binary pattern (LBP); Gray-Level Co-occurrence Matrix (GLCM) and also the group sparse coding (GSC) and come up with the fusion of LBP, PCA, SURF GLCM with GSC. Linear Kernel Support Vector Machine (LSVM) Classifier out-performed Polynomial, RBF and Sigmoid kernels SVM in the emotion classification. Results obtained from experiments indicated that, the new fusion method is capable of differentiating different types of face emotions with higher accuracy compare with the state-of-the-art methods currently available

Cost-effectiveness of COVID rapid diagnostic tests for patients with severe/critical illness in low- and middle-income countries: A modeling study

ARUap:idPdleiaasgencoosntfiicrmtethsatsta(lRlhDeaTdsi)nfgolervceolsroarnearveiprruessednisteedacsoerr(eCcOtlyV: ID) are used in low- and middle- income countries (LMICs) to inform treatment decisions. However, to date, it is unclear when this use is cost-effective. Existing analyses are limited to a narrow set of countries and uses. The aim of this study is to assess the cost-effectiveness of COVID RDTs to inform the treatment of patients with severe illness in LMICs, considering real world practice. We assessed the cost-effectiveness of COVID testing across LMICs using a decision tree model, differentiating results by country income level, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) prevalence, and testing scenario (none, RDTs, polymerase chain reaction tests—PCRs and combinations). LMIC experts defined realistic care pathways and treatment options. Using a healthcare provider perspective and net monetary benefit approach, we assessed both intended (COVID symptom alleviation) and unintended (treatment side effects) health and economic impacts for each testing scenario. We included the side effects of corticosteroids, which are often the only available treatment for COVID. Because side effects depend both on the treatment and the patient’s underlying illness (COVID or COVID-like illnesses, such as influenza), we considered the prevalence of COVID-like illnesses in our analyses. We found that SARS-CoV-2 testing of patients with severe COVID-like illness can be cost-effective in all LMICs, though only in some circumstances. High influenza prevalence among suspected COVID cases improves cost-effectiveness, since incorrectly provided corticosteroids may worsen influenza outcomes. In low- and some lower-middle-income countries, only patients with a high index of suspicion for COVID should be tested with RDTs, while other patients should be presumed to not have COVID. In some lower-middleincome and upper-middle-income countries, suspected severe COVID cases should almost always be tested. Further, in these settings, negative test results in patients with a high initial index of suspicion should be confirmed through PCR and, during influenza outbreaks, positive results in patients with a low initial index of suspicion should also be confirmed with a PCR. The use of interleukin-6 receptor blockers, when supported by testing, may also be cost-effective in higher-income LMICs. The cost at which they would be cost-effective in low-income countries ($162 to$406 per treatment course) is below current prices. The primary limitation of our analysis is substantial uncertainty around some of the parameters in our model due to limited data, most notably on current COVID mortality with standard of care, and insufficient evidence on the impact of corticosteroids on patients with severe influenza.Fogarty International CenterRevisión por pare

"We usually see a lot of delay in terms of coming for or seeking care": an expert consultation on COVID testing and care pathways in seven low- and middle-income countries.

BACKGROUND: Rapid diagnostic testing may support improved treatment of COVID patients. Understanding COVID testing and care pathways is important for assessing the impact and cost-effectiveness of testing in the real world, yet there is limited information on these pathways in low-and-middle income countries (LMICs). We therefore undertook an expert consultation to better understand testing policies and practices, clinical screening, the profile of patients seeking testing or care, linkage to care after testing, treatment, lessons learnt and expected changes in 2023. METHODS: We organized a qualitative consultation with ten experts from seven LMICs (India, Indonesia, Malawi, Nigeria, Peru, South Africa, and Zimbabwe) identified through purposive sampling. We conducted structured interviews during six regional consultations, and undertook a thematic analysis of responses. RESULTS: Participants reported that, after initial efforts to scale-up testing, the policy priority given to COVID testing has declined. Comorbidities putting patients at heightened risk (e.g., diabetes) mainly relied on self-identification. The decision to test following clinical screening was highly context-/location-specific, often dictated by local epidemiology and test availability. When rapid diagnostic tests were available, public sector healthcare providers tended to rely on them for diagnosis (alongside PCR for Asian/Latin American participants), while private sector providers predominantly used polymerase chain reaction (PCR) tests. Positive test results were generally taken at 'face value' by clinicians, although negative tests with a high index of suspicion may be confirmed with PCR. However, even with a positive result, patients were not always linked to care in a timely manner because of reluctance to receiving care or delays in returning to care centres upon clinical deterioration. Countries often lacked multiple components of the range of therapeutics advised in WHO guidelines: notably so for oral antivirals designed for high-risk mild patients. Severely ill patients mostly received corticosteroids and, in higher-resourced settings, tocilizumab. CONCLUSIONS: Testing does not always prompt enhanced care, due to reluctance on the part of patients and limited therapeutic availability within clinical settings. Any analysis of the impact or cost-effectiveness of testing policies post pandemic needs to either consider investment in optimal treatment pathways or constrain estimates of benefits based on actual practice

SnoRNAs and miRNAs networks underlying COVID-19 disease severity

There is a lack of predictive markers for early and rapid identification of disease progression in COVID-19 patients. Our study aims at identifying microRNAs (miRNAs)/small nucleolar RNAs (snoRNAs) as potential biomarkers of COVID-19 severity. Using differential expression analysis of microarray data (n = 29), we identified hsa-miR-1246, ACA40, hsa-miR-4532, hsa-miR-145-5p, and ACA18 as the top five differentially expressed transcripts in severe versus asymptomatic, and ACA40, hsa-miR-3609, ENSG00000212378 (SNORD78), hsa-miR-1231, hsa-miR-885-3p as the most significant five in severe versus mild cases. Moreover, we found that white blood cell (WBC) count, absolute neutrophil count (ANC), neutrophil (%), lymphocyte (%), red blood cell (RBC) count, hemoglobin, hematocrit, D-Dimer, and albumin are significantly correlated with the identified differentially expressed miRNAs and snoRNAs. We report a unique miRNA and snoRNA profile that is associated with a higher risk of severity in a cohort of SARS-CoV-2 infected patients. Altogether, we present a differential expression analysis of COVID-19-associated microRNA (miRNA)/small nucleolar RNA (snoRNA) signature, highlighting their importance in SARS-CoV-2 infection

Complement C5a and clinical markers as predictors of COVID-19 disease severity and mortality in a multi-ethnic population

Coronavirus disease-2019 (COVID-19) was declared as a pandemic by WHO in March 2020. SARS-CoV-2 causes a wide range of illness from asymptomatic to life-threatening. There is an essential need to identify biomarkers to predict disease severity and mortality during the earlier stages of the disease, aiding treatment and allocation of resources to improve survival. The aim of this study was to identify at the time of SARS-COV-2 infection patients at high risk of developing severe disease associated with low survival using blood parameters, including inflammation and coagulation mediators, vital signs, and pre-existing comorbidities. This cohort included 89 multi-ethnic COVID-19 patients recruited between July 14th and October 20th 2020 in Doha, Qatar. According to clinical severity, patients were grouped into severe (n=33), mild (n=33) and asymptomatic (n=23). Common routine tests such as complete blood count (CBC), glucose, electrolytes, liver and kidney function parameters and markers of inflammation, thrombosis and endothelial dysfunction including complement component split product C5a, Interleukin-6, ferritin and C-reactive protein were measured at the time COVID-19 infection was confirmed. Correlation tests suggest that C5a is a predictive marker of disease severity and mortality, in addition to 40 biological and physiological parameters that were found statistically significant between survivors and non-survivors. Survival analysis showed that high C5a levels, hypoalbuminemia, lymphopenia, elevated procalcitonin, neutrophilic leukocytosis, acute anemia along with increased acute kidney and hepatocellular injury markers were associated with a higher risk of death in COVID-19 patients. Altogether, we created a prognostic classification model, the CAL model (C5a, Albumin, and Lymphocyte count) to predict severity with significant accuracy. Stratification of patients using the CAL model could help in the identification of patients likely to develop severe symptoms in advance so that treatments can be targeted accordingly

SPARC 2017 retrospect & prospects : Salford postgraduate annual research conference book of abstracts

Welcome to the Book of Abstracts for the 2017 SPARC conference. This year we not only celebrate the work of our PGRs but also the 50th anniversary of Salford as a University, which makes this year’s conference extra special. Once again we have received a tremendous contribution from our postgraduate research community; with over 130 presenters, the conference truly showcases a vibrant PGR community at Salford. These abstracts provide a taster of the research strengths of their works, and provide delegates with a reference point for networking and initiating critical debate. With such wide-ranging topics being showcased, we encourage you to exploit this great opportunity to engage with researchers working in different subject areas to your own. To meet global challenges, high impact research inevitably requires interdisciplinary collaboration. This is recognised by all major research funders. Therefore engaging with the work of others and forging collaborations across subject areas is an essential skill for the next generation of researchers

Antimicrobial resistance among migrants in Europe: a systematic review and meta-analysis

BACKGROUND: Rates of antimicrobial resistance (AMR) are rising globally and there is concern that increased migration is contributing to the burden of antibiotic resistance in Europe. However, the effect of migration on the burden of AMR in Europe has not yet been comprehensively examined. Therefore, we did a systematic review and meta-analysis to identify and synthesise data for AMR carriage or infection in migrants to Europe to examine differences in patterns of AMR across migrant groups and in different settings. METHODS: For this systematic review and meta-analysis, we searched MEDLINE, Embase, PubMed, and Scopus with no language restrictions from Jan 1, 2000, to Jan 18, 2017, for primary data from observational studies reporting antibacterial resistance in common bacterial pathogens among migrants to 21 European Union-15 and European Economic Area countries. To be eligible for inclusion, studies had to report data on carriage or infection with laboratory-confirmed antibiotic-resistant organisms in migrant populations. We extracted data from eligible studies and assessed quality using piloted, standardised forms. We did not examine drug resistance in tuberculosis and excluded articles solely reporting on this parameter. We also excluded articles in which migrant status was determined by ethnicity, country of birth of participants' parents, or was not defined, and articles in which data were not disaggregated by migrant status. Outcomes were carriage of or infection with antibiotic-resistant organisms. We used random-effects models to calculate the pooled prevalence of each outcome. The study protocol is registered with PROSPERO, number CRD42016043681. FINDINGS: We identified 2274 articles, of which 23 observational studies reporting on antibiotic resistance in 2319 migrants were included. The pooled prevalence of any AMR carriage or AMR infection in migrants was 25·4% (95% CI 19·1-31·8; I2 =98%), including meticillin-resistant Staphylococcus aureus (7·8%, 4·8-10·7; I2 =92%) and antibiotic-resistant Gram-negative bacteria (27·2%, 17·6-36·8; I2 =94%). The pooled prevalence of any AMR carriage or infection was higher in refugees and asylum seekers (33·0%, 18·3-47·6; I2 =98%) than in other migrant groups (6·6%, 1·8-11·3; I2 =92%). The pooled prevalence of antibiotic-resistant organisms was slightly higher in high-migrant community settings (33·1%, 11·1-55·1; I2 =96%) than in migrants in hospitals (24·3%, 16·1-32·6; I2 =98%). We did not find evidence of high rates of transmission of AMR from migrant to host populations. INTERPRETATION: Migrants are exposed to conditions favouring the emergence of drug resistance during transit and in host countries in Europe. Increased antibiotic resistance among refugees and asylum seekers and in high-migrant community settings (such as refugee camps and detention facilities) highlights the need for improved living conditions, access to health care, and initiatives to facilitate detection of and appropriate high-quality treatment for antibiotic-resistant infections during transit and in host countries. Protocols for the prevention and control of infection and for antibiotic surveillance need to be integrated in all aspects of health care, which should be accessible for all migrant groups, and should target determinants of AMR before, during, and after migration. FUNDING: UK National Institute for Health Research Imperial Biomedical Research Centre, Imperial College Healthcare Charity, the Wellcome Trust, and UK National Institute for Health Research Health Protection Research Unit in Healthcare-associated Infections and Antimictobial Resistance at Imperial College London

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries