| 1. |
- Sultana, Arifa, et al.
(författare)
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A Retrospective Cross-Sectional Study Assessing Self-Reported Adverse Events following Immunization (AEFI) of the COVID-19 Vaccine in Bangladesh
- 2021
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Ingår i: Vaccines. - : MDPI. - 2076-393X. ; 9:10
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Tidskriftsartikel (refereegranskat)abstract
- Background: The Oxford-AstraZeneca vaccine (Covishield) was the first to be introduced in Bangladesh to fight the ongoing global COVID-19 pandemic. As this vaccine had shown some side-effects in its clinical trial, we aimed to conduct a study assessing short-term adverse events following immunization (AEFIs) in Bangladesh. Method: A cross-sectional study was conducted on social and electronic media platforms by delivering an online questionnaire among people who had taken at least one dose of the COVID-19 vaccine. The collected data were then analysed to evaluate various parameters related to the AEFIs of the respondents. Results: A total of 626 responses were collected. Of these, 623 were selected based on complete answers and used for the analysis. Most of the respondents were between 30-60 years of age, and 40.4% were female. We found that a total of 8.5% of the total respondents had been infected with the SARS-CoV-2 virus. Our survey revealed that out of 623 volunteers, 317 reported various side-effects after taking the vaccine, which is about 50.88% of the total participants. The majority of participants (37.07%, 231/623) reported swelling and pain at the injection site and fever (25.84%, 162/623); these were some of the common localized and generalized symptoms after the COVID-19 vaccine administration. Conclusion: The side-effects reported after receiving the Oxford-AstraZeneca vaccine (Covishield) are similar to those reported in clinical trials, demonstrating that the vaccines have a safe therapeutic window. Moreover, further research is needed to determine the efficacy of existing vaccines in preventing SARS-CoV-2 infections or after-infection hospitalization.
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| 2. |
- Ahmed, Anisuddin, et al.
(författare)
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Trends and inequity in improved sanitation facility utilisation in Bangladesh : Evidence from Bangladesh Demographic and Health Surveys
- 2023
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Ingår i: BMC Research Notes. - : Springer Nature. - 1756-0500. ; 16
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Tidskriftsartikel (refereegranskat)abstract
- Improved sanitation is indispensable to human health. However, lack of access to improved sanitation remains one of the most daunting public health challenges of the twenty-first century in Bangladesh. The aim of the study was to describe the trends in access to improved sanitation facilities following the inequity gap among households in different socioeconomic groups in Bangladesh. Data from the Bangladesh Demographic and Health Survey (BDHS) 2007, 2011, 2014, and 2017-18 were extracted for this study. Inequity in access to improved sanitation was calculated using rich-poor ratio and concentration index to determine the changes in inequity across the time period. In Bangladesh, the proportion of households with access to improved sanitation increased steadily from 25.4% to 45.4% between 2007 and 2014, but slightly decreased to 44.0% in 2017-18. Age, educational status, marital status of household head, household wealth index, household size, place of residence, division, and survey year were significantly associated with the utilisation of improved sanitation. There is a pro-rich situation, which means that utilisation of improved sanitation was more concentrated among the rich across all survey years (Concentration Index ranges: 0.40 to 0.27). The government and other relevant stakeholders should take initiatives considering inequity among different socioeconomic groups to ensure the use of improved sanitation facilities for all, hence achieving universal health coverage.
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| 3. |
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| 4. |
- Ahmed, Anisuddin, et al.
(författare)
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Factors influencing delivery-related complications and their consequences in hard-to-reach areas of Bangladesh
- 2024
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Ingår i: Sexual & Reproductive HealthCare. - : Elsevier. - 1877-5756 .- 1877-5764. ; 40
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Tidskriftsartikel (refereegranskat)abstract
- Background and objectives: Bangladesh's high maternal mortality ratio is exacerbated by delivery-related complications, particularly in hard-to-reach (HtR) areas with limited healthcare access. Despite this, few studies have explored delivery-related complications and factors contributing to these complications among the disadvantaged population. This study aimed to investigate the factors contributing to delivery-related complications and their consequences among the mothers residing in the HtR areas of Bangladesh. Methods: Data were collected using a cross-sectional study design from 13 HtR sub-districts of Bangladesh between September 2019 and October 2019. Data from 1,290 recently delivered mothers were analysed. Results: Around 32% (95% CI: 29.7-34.8) of the mothers reported at least one delivery-related complication. Prolonged labour pain (21%) was the highest reported complication during the delivery, followed by obstructive labour (20%), fever (14%), severe headache (14%). Mothers with higher education, a higher number of antenatal care (ANC) visits, complications during ANC, employed, and first-time mothers had higher odds of reporting delivery-related complications. More than one-half (51%) of these mothers had normal vaginal delivery. Nearly one-fifth (20%) of mothers who reported delivery-related complications were delivered by unskilled health workers at homes. On the other hand, about one-fifth (19%) of the mothers without any complications during delivery had a caesarean delivery. Nine out of ten of these caesarean deliveries were done at the private facilities. Conclusion: Delivery-related complications are significantly related to a woman's reproductive history and other background characteristics. Unnecessary caesarean delivery is prominent at private facilities.
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| 5. |
- Bhattacharya, Prosun, 1962-, et al.
(författare)
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Prevalence of SARS-CoV-2 in Communities Through Wastewater Surveillance—a Potential Approach for Estimation of Disease Burden
- 2021
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Ingår i: Current Pollution Reports. - : Springer Nature. - 2198-6592. ; 7:2, s. 160-166
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Tidskriftsartikel (refereegranskat)abstract
- The episodic outbreak of COVID-19 due to SARS-CoV-2 is severely affecting the economy, and the global count of infected patients is increasing. The actual number of patients had been underestimated due to limited facilities for testing as well as asymptomatic nature of the expression of COVID-19 on individual basis. Tragically, for emerging economies with high population density, the situation has been more complex due to insufficient testing facilities for diagnosis of the disease. However, the recent reports about persistent shedding of viral RNA of SARS-CoV-2 in the human feces have created a possibility to track the prevalence and trends of the disease in communities, known as wastewater-based epidemiology (WBE). In this article, we highlight the current limitations and future prospects for WBE to manage pandemics.
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| 6. |
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| 7. |
- Salauddin, Md., et al.
(författare)
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Molecular Detection of Multidrug Resistant Staphylococcus aureus Isolated from Bovine Mastitis Milk in Bangladesh
- 2020
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Ingår i: Veterinary Sciences. - BASEL SWITZERLAND : MDPI AG. - 2306-7381. ; 7:2
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Tidskriftsartikel (refereegranskat)abstract
- The current study was conducted to isolate and identify multidrug-resistant Staphylococcus aureus (MDR-SA) from mastitis milk samples and to determine their antimicrobial susceptibility pattern. A total of 48 bovine mastitis (BM) milk samples were collected from different parts of the Rangpur division, Bangladesh. After the collection of milk samples, mastitis was confirmed using the California mastitis test. Isolation and identification of Staphylococcus aureus were performed using conventional cultural and biochemical tests as well as using molecular methods of PCR. Nucleotide sequence analysis of the 23S rRNA gene of Staphylococcus aureus was determined. The antibiogram of the isolated bacteria was conducted using the disc diffusion method. Phylogenetic analysis of 23S rRNA was done using MEGA 7, ClustalW multiple sequence alignment, and NCBI-BLAST tools, where the sequence of the isolate showed 98% to 99% identity. Antibiogram test using 15 antimicrobial agents showed that all of the Staphylococcus aureus isolates were classified as multidrug-resistant (MDR). It was found that the isolates were resistant to tetracycline, novobiocin, methicillin, vancomycin, and cephradine, and the isolates were sensitive to ciprofloxacin, azithromycin, norfloxacin, levofloxacin, gentamicin, and amoxicillin. The detection of MDR-SA in mastitis milk is alarming and represents a great public health concern. The findings of the present study help identify Staphylococcus aureus at the molecular level using 23S rRNA gene sequencing and will help select the appropriate and effective antimicrobial agent to control BM in the northern part of Bangladesh.
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| 8. |
- Sumi, Tahmina Akter, et al.
(författare)
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Classifying Humerus Fracture Using X-Ray Images
- 2023
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Ingår i: The Fourth Industrial Revolution and Beyond - Select Proceedings of IC4IR. - : Springer Science and Business Media Deutschland GmbH. - 9789811980312 - 9789811980329 ; , s. 527-538
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Konferensbidrag (refereegranskat)abstract
- Bone is the most important part of our body which holds the whole structure of human body. The long bone situated in the upper arm of human body between the shoulder and elbow junction is known as “Humerus”. Humerus works as a structural support of the muscles and arms in the upper body which helps in the movement of the hand and elbow. Therefore, any fracture in humerus disrupts our daily lives. The manual fracture detection process where the doctors detect the fracture by analyzing X-ray images is quite time consuming and also error prone. Therefore, we have introduced an automated system to diagnose humerus fracture in an efficient way. In this study, we have focused on deep learning algorithm for fracture detection. In this purpose at first, 1266 X-ray images of humerus bone including fractured and non-fractured have been collected from a publicly available dataset called “MURA”. As a deep learning model has been used here, data augmentation has been applied to increase the dataset for reducing over-fitting problem. Finally, all the images are passed through CNN model to train the images and classify the fractured and non-fractured bone. Moreover, different pretrained model has also been applied in our dataset to find out the best accuracy. After implementation, it is observed that our model shows the best accuracy which is 80% training accuracy and 78% testing accuracy comparing with other models.
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| 9. |
- Akter, Nasrin, et al.
(författare)
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Brain Tumor Classification using Transfer Learning from MRI Images
- 2022
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Ingår i: Proceedings of International Conference on Fourth Industrial Revolution and Beyond 2021. - Singapore : Springer. ; , s. 575-587
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Bokkapitel (refereegranskat)abstract
- One of the most vital parts of medical image analysis is the classification of brain tumors. Because tumors are thought to be origins to cancer, accurate brain tumor classification can save lives. As a result, CNN (Convolutional Neural Network)-based techniques for classifying brain cancers are frequently employed. However, there is a problem: CNNs are exposed to vast amounts of training data in order to produce good performance. This is where transfer learning enters into the picture. We present a 4-class transfer learning approach for categorizing Glioma, Meningioma, and Pituitary tumors and non-tumors in this study. The three most prevalent types of brain tumors are glioma, meningioma, and pituitary tumors. Our presented method, which employs the theory of transfer learning, utilizes a pre-trained InceptionResnetV1 method for classifying brain MRI images by extracting features from them using the softmax classifier method. The proposed approach outperforms all prior techniques with a mean classification accuracy of 93.95%. For the evaluation of our method we use kaggle dataset. Precision, recall, and F-score are one of the key performance metrics employed in this study.
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| 10. |
- Haque, Rehnuma, et al.
(författare)
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Wastewater surveillance of SARS-CoV-2 in Bangladesh : Opportunities and challenges
- 2022
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Ingår i: CURRENT OPINION IN ENVIRONMENTAL SCIENCE & HEALTH. - : Elsevier BV. - 2468-5844. ; 27, s. 100334-
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Tidskriftsartikel (refereegranskat)abstract
- The ongoing pandemic of the coronavirus disease 2019 (COVID-19) is a public health crisis of global concern. The progression of the COVID-19 pandemic has been monitored in the first place by testing symptomatic individuals for SARS-CoV-2 virus in the respiratory samples. Concurrently, wastewater carries feces, urine, and sputum that potentially contains SARS-CoV-2 intact virus or partially damaged viral genetic materials excreted by infected individuals. This brings significant opportunities for understanding the infection dynamics by environmental surveillance. It has advantages for the country, especially in densely populated areas where individual clinical testing is difficult. However, there are several challenges including: 1) establishing a sampling plan and schedule that is representative of the various catchment populations 2) development and validation of standardized protocols for the laboratory analysis 3) understanding hydraulic flows and virus transport in complex wastewater drainage systems and 4) collaborative efforts from government agencies, NGOs, public health units and academia.
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