Evaluation of online bank efficiency in Bangladesh: A Data Envelopment Analysis (DEA) approach

This study aims to examine the relative efficiency of Bangladesh online banks during 2001–2007 by utilizing Data Envelopment Analysis (DEA).Based on the several online sampled banks, the findings reveal that the most efficient banks were AL-Arafah Islami Bank Limited, Shahajalal Islami Bank Limited, Eastern Bank Limited, and the less efficient banks over the study period were Janata Bank Limited, Utara Bank Limited, United Commercial Bank Limited, Pubali Bank Limited, and AB Bank Limited.Among the three groups Group-1 (n=20), Group-2 (n=18), Group-3 (n=15) we observed that the individual efficiency level of banks are increasing group by group.The efficiency level of Group-2 was slightly increased from the efficiency level of Group-1.The source of efficiency of the sampled banks was found to be lower for technical efficiency and scale efficiency rather than pure technical efficiency.Moreover, the scale inefficiency was found lower in G-3 compare to G-1 and G-2.This indicated that the scale inefficiency was observed decreasing group by group and these were attributable to technical efficiency rather than pure technical inefficiency

Asthma in paediatric intensive care in England residents:observational study

Despite high prevalence of asthma in children in the UK, there were no prior report on asthma admissions in paediatric intensive care units (PICU). We investigated the epidemiology and healthcare resource utilisation in children with asthma presenting to PICUs in England. PICANet, a UK national PICU database, was queried for asthma as the primary reason for admission, of children resident in England from April 2006 until March 2013. There were 2195 admissions to PICU for a median stay of 1.4 days. 59% were males and 51% aged 0–4 years. The fourth and fifth most deprived quintiles represented 61% (1329) admissions and 73% (11) of the 15 deaths. Deaths were most frequent in 10–14 years age (n = 11, 73%), with no deaths in less than 5 years age. 38% of admissions (828/2193) received invasive ventilation, which was more frequent with increasing deprivation (13% (108/828) in least deprived to 31% (260/828) in most deprived) and with decreasing age (0–4-year-olds: 49%, 409/828). This first multi-centre PICU study in England found that children from more deprived neighbourhoods represented the majority of asthma admissions, invasive ventilation and deaths in PICU. Children experiencing socioeconomic deprivation could benefit from enhanced asthma support in the community

An Assessment of the Importance of Admission Test for Enrollments in Public Universities of Bangladesh

Public universities in Bangladesh arrange admission test to judge the students’ merit before the enrollment. Academic results of previous examinations (SSC and HSC) are also considered in the admission procedure. There are some disputes regarding the importance of admission test besides the previous academic records. The universities emphasize on the admission test while the government authorities ponder it as a burden for the students. This study has made an attempt to examine the importance of admission test in selection procedure utilizing a particular year admission test database of Shahjalal University of Science and Technology (SUST). Univariate and bivariate analyses along with regression models were used to analyze the data. The results indicate that students with higher score in both SSC and HSC examinations had higher possibility to be eligible for enrollment. However, a vital proportion of applicants with maximum GPA 5.00 in both examinations did not qualify in merit and waiting position. The results also show association and moderate positive correlation of admission test score with SSC and HSC results. Finally, regression analysis indicates that though the contributions of the SSC and HSC results on admission test scores are significant, the variation in admission test scores is not much explained by the previous records. Such findings recommend arranging admission test, besides academic qualification, to select the eligible applicants for enrollment in public universities

Modifiable risk factors for asthma exacerbations during the COVID-19 pandemic: a population-based repeated cross-sectional study using the Research and Surveillance Centre primary care database

Background There were substantial reductions in asthma exacerbations during the COVID-19 pandemic for reasons that remain poorly understood. We investigated changes in modifiable risk factors which might help explain the reductions in asthma exacerbations. Methods Multilevel generalised linear mixed models were fitted to examine changes in modifiable risk factors for asthma exacerbations during 2020–2022, compared to pre-pandemic year (2019), using observational, routine data from general practices in the Oxford-Royal College of General Practitioners Research and Surveillance Centre. Asthma exacerbations were defined as any of GP recorded: asthma exacerbations, prescriptions of prednisolone, accident and emergency department attendance or hospitalisation for asthma. Modifiable risk factors of interest were ownership of asthma self-management plan, asthma annual review, inhaled-corticosteroid (ICS) prescriptions, influenza vaccinations and respiratory-tract-infections (RTI). Findings Compared with 2019 (n = 550,995), in 2020 (n = 565,956) and 2022 (n = 562,167) (p < 0.05): asthma exacerbations declined from 67.1% to 51.9% and 61.1%, the proportion of people who had: asthma exacerbations reduced from 20.4% to 15.1% and 18.5%, asthma self-management plans increased from 28.6% to 37.7% and 55.9%; ICS prescriptions increased from 69.9% to 72.0% and 71.1%; influenza vaccinations increased from 14.2% to 25.4% and 55.3%; current smoking declined from 15.0% to 14.5% and 14.7%; lower-RTI declined from 10.5% to 5.3% and 8.1%; upper-RTI reduced from 10.7% to 5.8% and 7.6%. There was cluster effect of GP practices on asthma exacerbations (p = 0.001). People with asthma were more likely (p < 0.05) to have exacerbations if they had LRTI (seven times(x)), had URTI and ILI (both twice), were current smokers (1.4x), PPV vaccinated (1.3x), seasonal flu vaccinated (1.01x), took ICS (1.3x), had asthma reviews (1.09x). People with asthma were less likely to have exacerbations if they had self-management plan (7%), and were partially (4%) than fully COVID-19 vaccinated. Interpretation We have identified changes in modifiable risk factors for asthma exacerbation that need to be maintained in the post-pandemic era

Modelling global, regional and national prevalence of asthma: projections from 2018 to 2040

INTRODUCTION: Asthma is a common chronic condition that results in considerable morbidity, healthcare utilisation and economic burden, both nationally and globally. While there has been encouraging progress made in reducing asthma mortality in some countries, there is still work to do in several countries where limited progress has been made. To inform policy deliberations for sustainable and effective global and national asthma control programmes, it is crucial to have a robust evidence base for future trends of the global, regional, and national prevalence of asthma. However, there is a lack of such important information in the published literature. The aims of this PhD were to: (i) systematically identify, describe and critique existing models for estimating and/or projecting the global, regional and national prevalence and disease burden of asthma; (ii) develop a critical appraisal checklist for assessing the quality of models for estimating and projecting prevalence and burden of asthma; and (iii) generate projections of global, regional and national prevalence of asthma from 2018 to 2040. METHODS: This PhD was conducted in three consecutive phases. In Phase-I, I undertook a systematic review of models for estimating and projecting global, regional, and national prevalence and disease burden of asthma. I searched Medline, Embase, World Health Organization Library and Information Services (WHOLIS) and Web of Science databases from 1980 to 2017 for modelling studies on prevalence and burden of asthma. Data were descriptively and narratively synthesised. The identified models were appraised critically in relation to their strengths, limitations and reproducibility. In Phase-II, I developed a critical appraisal checklist for assessing the quality of models for estimating and projecting prevalence and burden of asthma by reviewing the existing critical appraisal checklists, risk of bias tools, reporting guidelines and other guidelines for good practice in modelling studies and consulting with a panel of experts in the field of asthma and disease modelling. Then, I applied this critical appraisal checklist to the models identified through the systematic review. Based on the findings, I determined the best quality models for projecting the prevalence and disease burden of asthma. In the final phase (Phase-III) of this PhD, I conducted a modelling study to generate projections of global, regional and national prevalence of asthma from 2018 to 2040. Drawing on the learning from Phase-II, I developed dynamic models by using regression models with Auto Regressive Integrated Moving Average (ARIMA) errors to generate the projections of the prevalence of asthma. Input data for this modelling study were extracted from the Global Burden of Disease (GBD) Study 2017 (GBD 2017) because GBD was the only comprehensive source of estimates of asthma prevalence. RESULTS: In Phase-I, I identified 108 eligible studies. These studies employed a total of 51 unique models. Logistic and linear regression models were mostly used in national estimates and projections. Bayesian meta-regression models such as DisMod-MR and Cause Of Death Ensemble models (CODEm) were most commonly used in international estimates. Most models for prevalence and burden of asthma suffered from several methodological limitations – in particular, suboptimal reporting, poor quality and lack of reproducibility. The critical appraisal checklist that I developed in Phase-II included the following quality criteria for models: (i) statement of objectives and scope, (ii) model structure, (iii) model assumptions, (iv) underlying theory, (v) model appropriateness, (vi) description of input data, (vii) data representativeness, (viii) outcome measure, (ix) model fitting and parameter estimation, (x) quantification of uncertainty, (xi) goodness of fit, (xii) model performance, (xiii) model presentation, (xiv) user manual, and (xv) replication and usability. Application of this critical appraisal checklist to the models that I identified through the systematic review undertaken in Phase-I determined regression models with ARIMA error as the best quality models for projecting prevalence and burden of asthma. The modelling study in Phase-III projected that there would be an expected 337.9 (95% CI: 336.8-339.0) million people with clinician-diagnosed current asthma in the world in 2040. The global prevalence of clinician-diagnosed current asthma was forecasted to be 3.7% in 2040, which is a 0.03% decrease from 2017. However, the global asthma cases were projected to increase by 65.0 million (24.0%) during this period due to population growth. The global prevalence of clinician-diagnosed current asthma in women (185.4 million; 95% CI: 184.6-186.2) was projected to be higher than those in men (152.5 million; 95% CI: 151.7-153.3) in 2040. The regional prevalence of clinician-diagnosed current asthma for the year 2040 was forecasted to be highest in Polynesia (11.5%; 95% CI: 9.3 to 13.7); followed by Australasia (10.5%; 95% CI: 10.2-10.8), Micronesia (9.0%; 95% CI: 6.8-11.2) and Northern Europe (7.6%; 95% CI: 7.4-7.8); and lowest in Southern Africa region (1.6%; 95% CI: 1.5-1.7). Among 22 Sustainable Development Goals (SDG) regions, the prevalence of clinician-diagnosed current asthma was forecasted to decrease in around two-thirds of regions (n=15; 68.2%) from 2017 to 2040. There was substantial variation in the national projections of the number of people with clinician-diagnosed current asthma ranging from 4,800.0 (95% CI: 640.0-8,960.0) in Andorra to 36.1 (95% CI: 35.7-36.4) million in India in 2040. The highest national prevalence of clinician-diagnosed current asthma for the year 2040 was forecasted to be in Tonga (14.1%; 95% CI: 8.1-20.2); followed by Vanuatu (12.5%; 95% CI: 9.5-15.5) and Australia (11.2%; 95% CI: 10.9-11.6); and the lowest in South Africa (1.4%; 95% CI: 1.3-1.5). The trends in the number of people with clinician-diagnosed current asthma from 2017 to 2040 were projected to increase in 113 countries (62.1%). CONCLUSIONS: Various models have been used to estimate and project the prevalence and burden of asthma, but almost all suffer from methodological limitations - in particular, suboptimal reporting and lack of reproducibility. There is a need for reporting sufficient details of models and making data and code available to ensure their reproducibility. The critical appraisal checklist that I developed contains essential quality criteria that a good model should possess, ranging from model structure to reproducibility. It will enable model users to assess the quality of a particular model of interest. Moreover, this checklist will be able to serve as the foundations for a future quality appraisal tool for the systematic reviews of modelling studies on prevalence and burden of diseases. The modelling phase projected that global asthma prevalence will decrease over the coming two decades. However, the global number of asthma cases is projected to increase due to population growth. Moreover, prevalence of asthma is projected to increase in two-thirds of countries. To my knowledge, this is the first study to generate comprehensive and reproducible projections of the global, regional and national prevalence of asthma. These projections of asthma prevalence can be useful inputs for governments, national and international funders, and inter-governmental organisations to make informed decision on future asthma policy worldwide