Abu Reza Md. Towfiqul Islam

Bio: Abu Reza Md. Towfiqul Islam is an academic researcher from Begum Rokeya University. The author has contributed to research in topics: Environmental science & Medicine. The author has an hindex of 22, co-authored 123 publications receiving 1633 citations. Previous affiliations of Abu Reza Md. Towfiqul Islam include Nanjing University of Information Science and Technology & Universiti Teknologi Malaysia.

Flood susceptibility modelling using advanced ensemble machine learning models

Abstract: Floods are one of nature's most destructive disasters because of the immense damage to land, buildings, and human fatalities. It is difficult to forecast the areas that are vulnerable to flash flooding due to the dynamic and complex nature of the flash floods. Therefore, earlier identification of flash flood susceptible sites can be performed using advanced machine learning models for managing flood disasters. In this study, we applied and assessed two new hybrid ensemble models, namely Dagging and Random Subspace (RS) coupled with Artificial Neural Network (ANN), Random Forest (RF), and Support Vector Machine (SVM) which are the other three state-of-the-art machine learning models for modelling flood susceptibility maps at the Teesta River basin, the northern region of Bangladesh. The application of these models includes twelve flood influencing factors with 413 current and former flooding points, which were transferred in a GIS environment. The information gain ratio, the multicollinearity diagnostics tests were employed to determine the association between the occurrences and flood influential factors. For the validation and the comparison of these models, for the ability to predict the statistical appraisal measures such as Freidman, Wilcoxon signed-rank, and t-paired tests and Receiver Operating Characteristic Curve (ROC) were employed. The value of the Area Under the Curve (AUC) of ROC was above 0.80 for all models. For flood susceptibility modelling, the Dagging model performs superior, followed by RF, the ANN, the SVM, and the RS, then the several benchmark models. The approach and solution-oriented outcomes outlined in this paper will assist state and local authorities as well as policy makers in reducing flood-related threats and will also assist in the implementation of effective mitigation strategies to mitigate future damage.

Psychosocial and Socio-Economic Crisis in Bangladesh Due to COVID-19 Pandemic: A Perception-Based Assessment

Abstract: Background: The spread of the COVID-19 pandemic, the partial lockdown, the disease intensity, weak governance in the healthcare system, insufficient medical facilities, unawareness, and the sharing of misinformation in the mass media has led to people experiencing fear and anxiety. The present study intended to conduct a perception-based analysis to get an idea of people's psychosocial and socio-economic crisis, and the possible environmental crisis, amidst the COVID-19 pandemic in Bangladesh. Methods: A perception-based questionnaire was put online for Bangladeshi citizens of 18 years and/or older. The sample size was 1,066 respondents. Datasets were analyzed through a set of statistical techniques including principal component and hierarchical cluster analysis. Results: There was a positive significant association between fear of the COVID-19 outbreak with the struggling healthcare system (p < 0.05) of the country. Also, there was a negative association between the fragile health system of Bangladesh and the government's ability to deal with the pandemic (p < 0.05), revealing the poor governance in the healthcare system. A positive association of shutdown and social distancing with the fear of losing one's own or a family members' life, influenced by a lack of healthcare treatment (p < 0.05), reveals that, due to the decision of shutting down normal activities, people may be experiencing mental and economic stress. However, a positive association of the socio-economic impact of the shutdown with poor people's suffering, the price hike of basic essentials, the hindering of formal education (p < 0.05), and the possibility of a severe socio-economic and health crisis will be aggravated. Moreover, there is a possibility of a climate change-induced disaster and infectious diseases like dengue during/after the COVID-19 situation, which will create severe food insecurity (p < 0.01) and a further healthcare crisis. Conclusions: The partial lockdown in Bangladesh due to the COVID-19 pandemic increased community transmission and worsened the healthcare crisis, economic burden, and loss of GDP despite the resuming of industrial operations. In society, it has created psychosocial and socio-economic insecurity among people due to the loss of lives and livelihoods. The government should take proper inclusive steps for risk assessment, communications, and financial stimulus toward the public to alleviate their fear and anxiety, and to take proper action to boost mental health and well-being.

Analyzing trend and forecasting of rainfall changes in India using non-parametrical and machine learning approaches.

Abstract: This study analyzes and forecasts the long-term Spatio-temporal changes in rainfall using the data from 1901 to 2015 across India at meteorological divisional level. The Pettitt test was employed to detect the abrupt change point in time frame, while the Mann-Kendall (MK) test and Sen's Innovative trend analysis were performed to analyze the rainfall trend. The Artificial Neural Network-Multilayer Perceptron (ANN-MLP) was employed to forecast the upcoming 15 years rainfall across India. We mapped the rainfall trend pattern for whole country by using the geo-statistical technique like Kriging in ArcGIS environment. Results show that the most of the meteorological divisions exhibited significant negative trend of rainfall in annual and seasonal scales, except seven divisions during. Out of 17 divisions, 11 divisions recorded noteworthy rainfall declining trend for the monsoon season at 0.05% significance level, while the insignificant negative trend of rainfall was detected for the winter and pre-monsoon seasons. Furthermore, the significant negative trend (-8.5) was recorded for overall annual rainfall. Based on the findings of change detection, the most probable year of change detection was occurred primarily after 1960 for most of the meteorological stations. The increasing rainfall trend had observed during the period 1901-1950, while a significant decline rainfall was detected after 1951. The rainfall forecast for upcoming 15 years for all the meteorological divisions' also exhibit a significant decline in the rainfall. The results derived from ECMWF ERA5 reanalysis data exhibit that increasing/decreasing precipitation convective rate, elevated low cloud cover and inadequate vertically integrated moisture divergence might have influenced on change of rainfall in India. Findings of the study have some implications in water resources management considering the limited availability of water resources and increase in the future water demand.

Strategic assessment of COVID-19 pandemic in Bangladesh: comparative lockdown scenario analysis, public perception, and management for sustainability.

Abstract: Community transmission of COVID-19 is happening in Bangladesh—the country which did not have a noteworthy health policy and legislative structures to combat a pandemic like COVID-19. Early strategic planning and groundwork for evolving and established challenges are crucial to assemble resources and react in an appropriate timely manner. This article, therefore, focuses on the public perception of comparative lockdown scenario analysis and how they may affect the sustainable development goals (SDGs) and the strategic management regime of COVID-19 pandemic in Bangladesh socio-economically as well as the implications of the withdrawal of partial lockdown plan. Scenario-based public perceptions were collected via a purposive sampling survey method through a questionnaire. Datasets were analysed through a set of statistical techniques including classical test theory, principal component analysis, hierarchical cluster analysis, Pearson’s correlation matrix and linear regression analysis. There were good associations among the lockdown scenarios and response strategies to be formulated. Scenario 1 describes how the death and infection rate will increase if the Bangladesh Government withdraws the existing partial lockdown. Scenario 2 outlines that limited people’s movement will enable low-level community transmission of COVID-19 with the infection and death rate will increase slowly (r = 0.540, p < 0.01). Moreover, there will be less supply of necessities of daily use with a price hike (r = 0.680, p < 0.01). In scenario 3, full lockdown will reduce community transmission and death from COVID-19 (r = 0.545, p < 0.01). However, along with the other problems gender discrimination and gender-based violence will increase rapidly (r = 0.661, p < 0.01). Due to full lockdown, the formal and informal business, economy, and education sector will be hampered severely (R = 0.695). Subsequently, there was a strong association between the loss of livelihood and the unemployment rate which will increase due to business shutdown (p < 0.01). This will lead to the severe sufferings of poor and vulnerable communities in both urban and rural areas (p < 0.01). All these will further aggravate the humanitarian needs of the most vulnerable groups in the country in the coming months to be followed which will undoubtedly affect the Bangladesh targets to achieve the SDGs of 2030 and other development plans that need to be adjusted. From our analysis, it was apparent that maintaining partial lockdown with business and economic activities with social distancing and public health guidelines is the best strategy to maintain. However, as the government withdrew the partial lockdown, inclusive and transparent risk communication towards the public should be followed. Recovery and strengthening of the health sector, economy, industry, agriculture, and food security should be focused on under the “new normal standard of life” following health guidelines and social distancing. Proper response plans and strategic management are necessary for the sustainability of the nation.

Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

Abstract: Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.

Climate Change 2007: Impacts, Adaptation and Vulnerability.

Abstract: Impatti, adattamento e vulnerabilita Le cause e le responsabilita dei cambiamenti climatici sono state trattate sul numero di ottobre della rivista Cda. Approfondiamo l’argomento presentando il documento: “Cambiamenti climatici 2007: impatti, adattamento e vulnerabilita” votato ad aprile 2007 dal secondo gruppo di lavoro del Comitato Intergovernativo sui Cambiamenti Climatici (Intergovernmental Panel on Climate Change). Si tratta del secondo di tre documenti che compongono il quarto rapporto sui cambiamenti climatici.

Climate change 2014 - Mitigation of climate change

Abstract: The talk with present the key results of the IPCC Working Group III 5th assessment report. Concluding four years of intense scientific collaboration by hundreds of authors from around the world, the report responds to the request of the world's governments for a comprehensive, objective and policy neutral assessment of the current scientific knowledge on mitigating climate change. The report has been extensively reviewed by experts and governments to ensure quality and comprehensiveness.

Anthropogenic aerosols and the weakening of the South Asian summer monsoon

Abstract: Changes in monsoon rainfall are caused by human-produced aerosols slowing the tropical atmospheric circulation. Observations show that South Asia underwent a widespread summertime drying during the second half of the 20th century, but it is unclear whether this trend was due to natural variations or human activities. We used a series of climate model experiments to investigate the South Asian monsoon response to natural and anthropogenic forcings. We find that the observed precipitation decrease can be attributed mainly to human-influenced aerosol emissions. The drying is a robust outcome of a slowdown of the tropical meridional overturning circulation, which compensates for the aerosol-induced energy imbalance between the Northern and Southern Hemispheres. These results provide compelling evidence of the prominent role of aerosols in shaping regional climate change over South Asia.