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Background: A growing body of scientific evidence suggests that face masks can slow the spread of COVID-19 and save lives, but mask usage remains low across many parts of the world, and strategies to increase mask usage remain untested and unclear.
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In the prevailing COVID-19 pandemic, accurate diagnosis plays a vital role in preventing the mass transmission of the SARS-CoV-2 virus. Especially patients with pneumonia need correct diagnosis for proper treatment of their respiratory distress. However, the current standard diagnosis method, RT-PCR testing has a significant false negative and false positive rate. As alternatives, diagnosis methods based on artificial intelligence can be applied for faster and more accurate diagnosis. Currently, various machine learning and deep learning techniques are being researched on to develop better COVID-19 diagnosis system. However, these approaches do not consider the uncertainty in data. Deep learning approaches use backpropagation. It is an unexplainable black box approach and is prone to problems like catastrophic forgetting. This article applies a belief rule-based expert system (BRBES) for diagnosis of COVID-19 on hematological data and CT scan data of lung tissue infection of adult pneumonia patients. The system is optimized with nature-inspired optimization algorithm—BRBES-based adaptive differential evolution (BRBaDE). This model has been evaluated on a real-world dataset of COVID-19 patients published in a previous work. Also, performance of the BRBaDE has been compared with BRBES optimized with genetic algorithm and MATLAB’s fmincon function where BRBaDE outperformed genetic algorithm and fmincon and showed best accuracy of 73.91%. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
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[Figure: see text].
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The unusual situation that arose due to the COVID-19 pandemic and the 65-day fishing ban (national policy to boost depleted fish stocks) affected the lower-income fishing communities in coastal Bangladesh. Shocks and stresses were posed, and community people adopted strategies to adapt to the changes. In the process of adaptation, social-ecological systems resilience at different levels plays a crucial role. Though resilience is acknowledged as multilevel feature, studies on the interaction between the levels while understanding communities’ responses to shock and stress are limited. Thus, in this study, we explored the shocks and stresses the fishing community faced and their views on the resilience feature at different levels (i.e., individual, household, and community level) in coastal Bangladesh during the COVID-19 pandemic and 65-day fishing ban period. The study found that the most resilience promoting features (e.g., diversified livelihood, friendship, and network of supports) were adopted at the individual and household levels. However, positive and negative interactions were explored between resilience features at all levels. Low community-level resilience was not translated into a lack of household-level resilience, and strong individual-level resilience did not mean high household-level resilience. It was noted that the increased resilience of a particular individual or household could negatively affect community resilience. Resilience features showed inconsistent interactions within or among the three levels’ resilience features. The study also revealed that multilevel resilience features stressed the importance of combining persistence (i.e., keeping fishing as the main livelihood) and adaptation process (e.g., livelihood diversification). The study showcases the importance of considering multilevel resilience that offers insight into crucial resilience factors which would not be evident if only one level were studied. The overall finding of this study will contribute to framing governance strategies to ensure sustainable coastal management even in the time of any abrupt or expected changes, such as the COVID-19 pandemic and the fishing ban policy. © Copyright © 2021 Sultana, Irfanullah, Selim, Raihan, Bhowmik and Ahmed.
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Coherent national strategies, backed by regional cooperation efforts, offer a way forward for economic recovery in South Asia, which is rapidly becoming the next COVID-19 global hotspot. Challenges and policies relating to macroeconomics, health, economic sectors, stimulus measures, and reforms, which are all crucial for the region’s recovery are discussed. © 2020 Economic and Political Weekly. All rights reserved.