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Abstract Background Veterans have unique military risk factors and exposures during deployment that may augment their risk of post-acute sequelae of SARS-CoV-2 (PASC). The purpose of this study is to identify potential risk factors for PASC among Veterans in the national Airborne Hazards and Open Burn Pit Registry (AHOBPR). Methods This prospective observational study consisted of a semi-structured interview conducted via phone or videoconference from November 2021 to December 2022 among a stratified random sample of deployed Veterans nested within the national AHOBPR with laboratory-confirmed SARS-CoV-2 infection. PASC was defined as persistent new-onset symptoms lasting more than 2 months after initial SARS-CoV-2 infection. Deployment history, airborne hazards exposure and symptoms were obtained from the AHOBPR self-assessment questionnaire completed prior to SARS-CoV-2 infection (past). Post-infection symptoms and health behaviors obtained at study interview (present) were used to test the hypothesis that deployment experience and exposure increases the risk for PASC. Results From a sample of 212 Veterans, 149 (70%) met criteria for PASC with a mean age of 47 ± 8.7 years; 73 (49%) were women and 76 (51%) were men, and 129 (82.6%) continued to experience persistent symptoms of SARS-CoV-2 (596.8 ± 160.4 days since initial infection). Neither exposure to airborne hazards (OR 0.97, CI 0.92–1.03) or to burn pits (OR 1.00, CI 0.99-1.00) augmented risk for PASC. Conclusions PASC is highly common among Veterans enrolled in the AHOBPR, but we did not observe any unique military risk factors (e.g., airborne hazards exposure) that augmented the risk of PASC. Our findings may provide guidance to clinicians in the VHA network to administer appropriate care for Veterans experiencing PASC.

Background: Child malnutrition risk factors are globally recognized, but the specific impact of the COVID-19 pandemic on the prevalence of child malnutrition, considering socioeconomic burdens and changes in family lifestyles, remains underexplored. This study aims to identify the significance of COVID-19-related factors in relation to the prevalence of child malnutrition in Selangor, Malaysia. Methods: Purposive sampling was employed in this pilot study to select the households with under-5 children and, a structured questionnaire was developed to gather data. Chi-squared tests, logistic regression modelling and World Health Organisation AnthroPlus software-based visualization were used for analyses. Results: The present study’s findings indicate that demographic and social factors, including 'Citizenship,' 'Type of House,' 'Number of Earning Members,' 'Father's Highest Educational Level,' and 'Number of Children in a Family,' have a statistically significant association with Wasting. Additionally, the mother's 'Highest Educational Level' is found to be linked to underweight prevalence. Within COVID-19 factors, ''COVID-19 Impact on Employment/Business'' demonstrated significance for both stunting and wasting. Multivariate analysis revealed disparities in childhood malnutrition by gender, age, and factors such as ''COVID-19 impact on children's physical activity'' and ''COVID-19 impact on children's decrease in health over the last two weeks.'' Conclusions: This study identified COVID-19 factors alongside sociodemographic variables with statistically significant relationships impacting childhood malnutrition in Selangor, Malaysia. The results underscored the substantial influence of the COVID-19 pandemic on child malnutrition prevalence. Decision-makers at family and community levels can benefit by considering these factors in their actions. However, the study's limitation lay in its dataset, urging larger-scale analyses to explore further sub-categories of the examined variables.

The rapid dissemination of misinformation on the internet complicates the decision-making process for individuals seeking reliable information, particularly parents researching child development topics. This misinformation can lead to adverse consequences, such as inappropriate treatment of children based on myths. While previous research has utilized text-mining techniques to predict child abuse cases, there has been a gap in the analysis of child development myths and facts. This study addresses this gap by applying text mining techniques and classification models to distinguish between myths and facts about child development, leveraging newly gathered data from publicly available websites. The research methodology involved several stages. First, text mining techniques were employed to pre-process the data, ensuring enhanced accuracy. Subsequently, the structured data was analysed using six robust Machine Learning (ML) classifiers and one Deep Learning (DL) model, with two feature extraction techniques applied to assess their performance across three different training-testing splits. To ensure the reliability of the results, cross-validation was performed using both k-fold and leave-one-out methods. Among the classification models tested, Logistic Regression (LR) demonstrated the highest accuracy, achieving a 90 % accuracy with the Bag-of-Words (BoW) feature extraction technique. LR stands out for its exceptional speed and efficiency, maintaining low testing time per statement (0.97 μs). These findings suggest that LR, when combined with BoW, is effective in accurately classifying child development information, thus providing a valuable tool for combating misinformation and assisting parents in making informed decisions.

Biopolymers are natural polymers produced by living organisms’ cells, and have promising multidisciplinary applications [...]

Sylhet division is the major tea-producing region of Bangladesh. This study was conducted to explore the potential of rainwater harvesting by a designed model to fulfill the water requirement of the Lackatoorah tea garden during the dry season. Data were collected from both primary and secondary sources, and remote sensing data were analyzed using ArcGIS 10.7 to assess soil texture and slope. Four potential sites of (1.5 m ×1m) area were identified to estimate the volume of runoff water in the study. Four tanks with a capacity of 4000 liters were placed to store water as a reservoir for four sites. This study reveals that the study area received maximum average rainfall during June (742.7 mm - 839.2 mm) and July (667.7 mm - 787.2 mm) and the months from October-March received minimum rainfall (

Monitoring of groundwater (GW) resources in coastal areas is vital for human needs, agriculture, ecosystems, securing water supply, biodiversity, and environmental sustainability. Although the utilization of water quality index (WQI) models has proven effective in monitoring GW resources, it has faced substantial criticism due to its inconsistent outcomes, prompting the need for more reliable assessment methods. Therefore, this study addressed this concern by employing the data-driven root mean squared (RMS) models to evaluate groundwater quality (GWQ) in the coastal Bhola district near the Bay of Bengal, Bangladesh. To enhance the reliability of the RMS-WQI model, the research incorporated the extreme gradient boosting (XGBoost) machine learning (ML) algorithm. For the assessment of GWQ, the study utilized eleven crucial indicators, including turbidity (TURB), electric conductivity (EC), pH, total dissolved solids (TDS), nitrate (NO3−), ammonium (NH4+), sodium (Na), potassium (K), magnesium (Mg), calcium (Ca), and iron (Fe). In terms of the GW indicators, concentration of K, Ca and Mg exceeded the guideline limit in the collected GW samples. The computed RMS-WQI scores ranged from 54.3 to 72.1, with an average of 65.2, categorizing all sampling sites' GWQ as “fair.” In terms of model reliability, XGBoost demonstrated exceptional sensitivity (R2 = 0.97) in predicting GWQ accurately. Furthermore, the RMS-WQI model exhibited minimal uncertainty (

Abstract Objective: To examine the height-for-age z-score (HAZ) of 0–35 months’ children along with stunting prevalence to identify trends, changes and available nutrition-sensitive and specific determinants that could help explain the long-term variation in child linear growth using successive Bangladesh Demographic and Health Surveys (BDHS) data from 1996 to 2018. Design: The BDHS pooled data are used for determining the key outcome variables HAZ, stunting and severe stunting. Trends, kernel-weighted local polynomial smoothing illustrations, pooled multivariable linear probability model (LPM), ordinary least squares method (OLS) and regression decomposition were used. Participants: Mothers having 0–35 months’ children, the most critical age range for growth faltering. Results: The mean HAZ increased by 0·91(±1·53) with 0·041 annual average change, while the percentages of stunting (–26·63 ± 0·54) and severe stunting (–21·12 ± 0·48) showed a reduction with 1·21 and 0·96 average annual changes, respectively. The average HAZ improvement (0·42 ± 1·56) in urban areas was less than the rural areas (1·16 ± 1·44). Similar patterns followed for stunting and severe stunting. The prenatal doctor visits (3064·65 %), birth in a medical facility (1054·32 %), breastfeeding initiation (153·18 %) and asset index (144·73 %) demonstrated a huge change. The findings of OLS, LPM and regression decomposition identified asset index, birth order, paternal and maternal education, bottle-fed, prenatal doctor visit, birth in a medical facility, vaccination, maternal BMI and ever-breastfed as influencing factors to predict the long-term changes of stunting and severe stunting. Conclusion: The nutrition-sensitive and specific factors identified through regression decomposition describing long-term variation in child linear growth should be focused further to attain the sustainable development goals.

Abstract Background Dietary diversity is a key determinant of infant and young child eating patterns for a variety of food groups taken by children between the ages of 6–23 months. The study aimed to examine the association between prenatal and postnatal obstetric care factors of mother and child’s dietary diversity, and specific food practices in Bangladesh. Methods This study analyzed the data of 2497 children between the age of 6–23 extracted from the latest countrywide Bangladesh Demographic Health Survey 2017–2018 and explored relationships between prenatal and postnatal obstetric care received by mother and dietary diversity score (DDS), minimum dietary diversity (MDD), and introduction of solid, semi-solid, and soft foods (ISSSF) of their children. Results Findings revealed that ≥ 4 antenatal care (ANC) visits care visits increased the DDS (adjusted $$\beta$$ β : 0.32, 95% CI [0.21, 0.43]), increased the likelihood of MDD (AOR 1.54, 95% CI [1.23, 1.93]), and ISSSF (AOR 1.24, 95% CI [1.08, 1.48]), consuming eggs (AOR 1.47, 95% CI [1.23, 1.76]), and vitamin A vegetables and fruits (AOR 1.38, 95% CI [1.15, 1.66]). Moreover, DDS (adjusted β: 0.05, 95% CI [0.00, 0.11]) and MDD (AOR 1.66, 95% CI [1.31, 2.11]) are linked to childbirth in a medical facility. The C-section delivery influences the DDS (adjusted $$\beta$$ β : 0.05, 95% CI [0.00, 0.10]), MDD (AOR 1.39, 95% CI [1.10, 1.75]), and ISSSF (AOR 1.22, 95% CI [1.02, 1.48]). Besides, postnatal visits within 48 h of delivery linked to MDD (AOR 0.66, 95% CI [0.49, 0.89]) and ISSSF (AOR 0.76, 95% CI [0.59, 0.97]), and physicians or professionals providing postnatal checkups were significantly associated with DDS (adjusted $$\beta$$ β : 0.09, 95% CI [0.02, 0.16]), MDD (AOR 1.69, 95% CI [1.26, 2.26]), and ISSSF (AOR 1.30, 95% CI [1.04, 1.62]). Conclusion Knowledge of child nutritional feeding should emphasize during prenatal and postnatal obstetric care of mother, particularly during antenatal and postnatal visits, C-section delivery, and birth in a healthcare facility to eradicate malnutrition and establish healthy child feeding practices.

Marine collagen and chitin derived from marine organisms are gaining significant attention for their diverse applications across various fields [...]

COVID-19 is a significant public health problem around the globe, including in Australia. Despite this, Australia's Ministry of Health has expanded COVID-19 control measures widely, logistical trials exist, and the disease burden still needs more clarity. One of the best methods to comprehend the dynamics of disease transmission is by mathematical modeling of COVID-19, which also makes it possible to quantify factors in many places, including Australia. In order to understand the dynamics of COVID-19 in Australia, we examine a mathematical modeling framework for the virus in this study. Australian COVID-19 actual incidence data from January to December 2021 was used to calibrate the model. We also performed a sensitivity analysis of the model parameters and found that the COVID-19 transmission rate was the primary factor in determining the basic reproduction number (R0). Gradually influential intervention policies were established, with accurate effect and coverage regulated with the help of COVID-19 experts in Australia. We simulated data for the period from April 2022 to August 2023. To ascertain which of these outcomes is most effective in lowering the COVID-19 burden, we here assessed the COVID-19 burden (as shown by the number of incident cases and mortality) under a range of intervention scenarios. Regarding the policy of single intervention, the fastest and most efficient way to lower the incidence of COVID-19 is via increasing the first-dose immunization rate, while an improved treatment rate for the afflicted population is also helps to lower mortality in Australia. Furthermore, our results imply that integrating more therapies at the same time increases their efficacy, particularly for mortality, which significantly reduced with a moderate effort, while lowering the number of COVID-19 instances necessitates a major and ongoing commitment.

Abstract Purpose Child morbidity prevents Bangladesh from reaching the target for the Sustainable Development Goals (target 3.2) despite the country’s success in reducing child mortality rates. As a result, it's crucial to consider a child's health-related issues. Therefore, this study aims to explore the prevalence and factors associated with under-five child morbidity in Bangladesh. Methods The Bangladesh Demographic and Health Survey, 2017–2018, a secondary cross-sectional survey data, was used in this study, which collected information using a two-stage systematic sampling design. After association test, Bayesian estimation of binary logistic regression model was used to identify the significant risk factors of morbidity among under-five children, and a trace plot was used to try to figure out the convergence of simulation. Results According to the prevalence analysis of this study, it can be noted that more than one-thirds of under-five children in Bangladesh suffered from at least one of the child health-related problems, and of these, the highest prevalence of child morbidity was found in the Barisal division of Bangladesh (~ 42%). According to the Bayesian logistic regression results, higher child age and maternal education are associated with a potential decrease in the risk of child morbidity in Bangladesh. Again, male children had a 7% higher risk of morbidity than female children. Another finding was that underweight children suffered 31% more fever/diarrhea/ acute respiratory infection (ARI) related problems than others. Conclusions According to this study’s findings, child morbidity is still a significant issue in Bangladesh. Therefore, progress on risk factors, such as maternal education, child nutrition, etc., should be the focus of policymakers' intervention.

Abstract Background The associated factors and patterns of giving birth in home settings of rural areas have been extensively studied in Bangladeshi literature. However, urban areas still need to be explored, particularly with recent data. Therefore, the authors aimed to investigate the influential determinants of delivery at home in urban areas of Bangladesh. Materials and methods In this study, 1699 urban-dwelling women who had given birth within the previous 60 months of the survey and lived in urban areas were used. The secondary data were extracted from the latest Bangladesh Demographic and Health Survey 2017–2018. Descriptive statistics and logistic regression were applied along with the association among selected variables were examined by the Chi-square test. Results Findings depict that 36.49% of women who lived in urban areas of Bangladesh delivered at home, whereas, 63.51% delivered at different govt. and private health care facilities. Women who lived in Chittagong [adjusted odds ratio (AOR) = 2.11, 95% CI 1.24–3.60], Barisal [AOR = 2.05, 95% CI 1.16–3.64] and Sylhet [AOR = 1.92, 95% CI 1.08–3.43] divisions have more likelihood to deliver at home (36.85%). Urban women following Christian religion [AOR = 10.71, 95% CI 1.32–86.68] have higher odds of delivering child at home (0.47%). Urban women having three or more children before her latest delivery (22.37%) and who are employed (29.37%) have more likelihood to deliver at home. However, women aged between 25 and 34 years (43.50%), who have higher education (25.90%), play the role of household head (9.06%), have parity of more than two births (2.24%), and read daily newspapers (68.69%) had a lower chance of delivery at home. Furthermore, women from wealthier families (89.12%) and more antenatal care (ANC) visits (94.93%) were less likely to have a delivery at home. Conclusion Despite significant progress in women and reproductive health in Bangladesh, the proportion of delivery in the home in urban areas is alarming and should be emphasized more. The authors believe the identified factors will help design interventions and policy development on this issue.

Movement sonification has emerged as a promising approach for rehabilitation and motion control. Despite significant advancements in sensor technologies, challenges remain in developing cost-effective, user-friendly, and reliable systems for gait detection and sonification. This study introduces a novel wearable personalised sonification and biofeedback device to enhance movement awareness for individuals with irregular gait and posture. Through the integration of inertial measurement units (IMUs), MATLAB, and sophisticated audio feedback mechanisms, the device offers real-time, intuitive cues to facilitate gait correction and improve functional mobility. Utilising a single wearable sensor attached to the L4 vertebrae, the system captures kinematic parameters to generate auditory feedback through discrete and continuous tones corresponding to heel strike events and sagittal plane rotations. A preliminary test that involved 20 participants under various audio feedback conditions was conducted to assess the system’s accuracy, reliability, and user synchronisation. The results indicate a promising improvement in movement awareness facilitated by auditory cues. This suggests a potential for enhancing gait and balance, particularly beneficial for individuals with compromised gait or those undergoing a rehabilitation process. This paper details the development process, experimental setup, and initial findings, discussing the integration challenges and future research directions. It also presents a novel approach to providing real-time feedback to participants about their balance, potentially enabling them to make immediate adjustments to their posture and movement. Future research should evaluate this method in varied real-world settings and populations, including the elderly and individuals with Parkinson’s disease.

Abstract COVID-19 remains a significant public health problem in New South Wales, Australia. Although the NSW government is employing various control policies, more specific and compelling interventions are needed to control the spread of COVID-19. This paper presents a modified SEIR-X model based on a nonlinear ordinary differential equations system that considers the transmission routes from asymptomatic (Exposed) and symptomatic (Mild and Critical) individuals. The model is fitted to the corresponding cumulative number of cases in metropolitan and rural health districts of NSW reported by the Health Department and parameterised using the least-squares method. The basic reproduction number $$({\mathrm{R}}_{0})$$ ( R 0 ) , which measures the possible spread of COVID-19 in a population, is computed using the next generation operator method. Sensitivity analysis of the model parameters reveals that the transmission rate had an enormous influence on $${\mathrm{R}}_{0}$$ R 0 , which may be an option for controlling this disease. Two time-dependent control strategies, namely preventive (it refers to effort at inhibiting the virus transmission and prevention of case development from Exposed, Mild, Critical, Non-hospitalised and Hospitalised population) and management (it refers to enhance the management of Non-hospitalised and Hospitalised individuals who are infected by COVID-19) measures, are considered to mitigate this disease’s dynamics using Pontryagin’s maximum principle. The most sensible control strategy is determined through the cost-effectiveness analysis for the metropolitan and rural health districts of NSW. Our findings suggest that of the single intervention strategies, enhanced preventive strategy is more cost-effective than management control strategy, as it promptly reduces COVID-19 cases in NSW. In addition, combining preventive and management interventions simultaneously is found to be the most cost-effective. Alternative policies can be implemented to control COVID-19 depending on the policymakers’ decisions. Numerical simulations of the overall system are performed to demonstrate the theoretical outcomes.

The emergence of generative artificial intelligence (AI), as demonstrated by models like ChatGPT, has garnered significant attention in recent times owing to its capacity to transform multiple domains of society, including higher education. Within academia, individuals such as students, educators, and scholars have already employed Large Language Models (LLMs) such as ChatGPT for a diverse range of academic and non-academic endeavors. However, there is still debate regarding the use of ChatGPT in higher education. The acceptability and validity of its impact on higher education have been a recent burning issue. The primary aim of this review paper is to elucidate the utilization of ChatGPT within the context of higher education, considering its possible opportunities and challenges. The data utilized in this study has been generated by examining published papers, websites, and blogs. Using an "introductory literature review," we have analyzed, synthesized, and explained the data that was generated. The findings revealed inadequate technological access, overreliance on AI, the presence of inaccuracies within subject-based knowledge, and the inability of educators to adapt teaching strategies are the core challenges of ChatGPT in higher education. However, besides these challenges, ChatGPT also brings opportunities like the advancement of learning efficiency, the concept of personalized learning, support for educators, and opportunities for skill enhancement.

The objective of the present study is to elucidate the evolution of thoughts on urine inspection from antiquity to the present day. The classical Unani literature like Liber Regius, Canon of Medicine, Liber continens, Treasure of Khwarazamshah, etc. and the ancient literature of other traditional medicines like Ayurveda were prime sources of data. Additional sources were translations and summaries of the said classical books and scholarly articles written on the topic of urine. For recent advancements in uroscopy, browsing PubMed, Google Scholar, data science, and other trusted websites was carried out. Plentiful resources were frequently looked up and aided in the selection of topics for discussion in this review. With this intent, bibliographic research on the various classical literature was thoroughly sought out. In this regard, the classical literature of various traditional medicines was of immense help. Moreover, browsing trusted websites was carried out by searching for complementary and alternative medicine for uroscopy and urinalysis. Uroscopy has a long, colourful, and interesting history. The earliest evidence of urine inspection can be found in Babylonian, Sumerian, and Ayurvedic writings. Correspondingly, uroscopy has been practised for over 6,000 years. However, with the invention of the microscope, urinalysis became a valuable diagnostic tool in clinical practices. So essentially, urine represents a mirror image of the body’s states, such as health and disease. Besides, Urinalysis has been evolving from antiquity to the present day, from time to time.

Aging is closely associated with collagen degradation, impacting the structure and strength of the muscles, joints, bones, and skin. The continuous aging of the skin is a natural process that is influenced by extrinsic factors such as UV exposure, dietary patterns, smoking habits, and cosmetic supplements. Supplements that contain collagen can act as remedies that help restore vitality and youth to the skin, helping combat aging. Notably, collagen supplements enriched with essential amino acids such as proline and glycine, along with marine fish collagen, have become popular for their safety and effectiveness in mitigating the aging process. To compile the relevant literature on the anti-aging applications of marine collagen, a search and analysis of peer-reviewed papers was conducted using PubMed, Cochrane Library, Web of Science, and Embase, covering publications from 1991 to 2024. From in vitro to in vivo experiments, the reviewed studies elucidate the anti-aging benefits of marine collagen, emphasizing its role in combating skin aging by minimizing oxidative stress, photodamage, and the appearance of wrinkles. Various bioactive marine peptides exhibit diverse anti-aging properties, including free radical scavenging, apoptosis inhibition, lifespan extension in various organisms, and protective effects in aging humans. Furthermore, the topical application of hyaluronic acid is discussed as a mechanism to increase collagen production and skin moisture, contributing to the anti-aging effects of collagen supplementation. The integration of bio-tissue engineering in marine collagen applications is also explored, highlighting its proven utility in skin healing and bone regeneration applications. However, limitations to the scope of its application exist. Thus, by delving into these nuanced considerations, this review contributes to a comprehensive understanding of the potential and challenges associated with marine collagen in the realm of anti-aging applications.

A principal concept in developing antibacterial agents with selective toxicity is blocking metabolic pathways that are critical for bacterial growth but that mammalian cells lack. Serine O-acetyltransferase (CysE) is an enzyme in many bacteria that catalyzes the first step in l-cysteine biosynthesis by transferring an acetyl group from acetyl coenzyme A (acetyl-CoA) to l-serine to form O-acetylserine. Because mammalian cells lack this l-cysteine biosynthesis pathway, developing an inhibitor of CysE has been thought to be a way to establish a new class of antibacterial agents. Here, we demonstrated that alkyl gallates such as octyl gallate (OGA) could act as potent CysE inhibitors in vitro and in bacteria. Mass spectrometry analyses indicated that OGA treatment markedly reduced intrabacterial levels of l-cysteine and its metabolites including glutathione and glutathione persulfide in Escherichia coli to a level similar to that found in E. coli lacking the cysE gene. Consistent with the reduction of those antioxidant molecules in bacteria, E. coli became vulnerable to hydrogen peroxide-mediated bacterial killing in the presence of OGA. More important, OGA treatment intensified susceptibilities of metallo-β-lactamase-expressing Gram-negative bacteria (E. coli and Klebsiella pneumoniae) to carbapenem. Structural analyses showed that alkyl gallate bound to the binding site for acetyl-CoA that limits access of acetyl-CoA to the active site. Our data thus suggest that CysE inhibitors may be used to treat infectious diseases caused by drug-resistant Gram-negative bacteria not only via direct antibacterial activity but also by enhancing therapeutic potentials of existing antibiotics.

Groundwater resources around the world required periodic monitoring in order to ensure the safe and sustainable utilization for humans by keeping the good status of water quality. However, this could be a daunting task for developing countries due to the insufficient data in spatiotemporal resolution. Therefore, this research work aimed to assess groundwater quality in terms of drinking and irrigation purposes at the adjacent part of the Rooppur Nuclear Power Plant (RNPP) in Bangladesh. For the purposes of achieving the aim of this study, nine groundwater samples were collected seasonally (dry and wet season) and seventeen hydro-geochemical indicators were analyzed, including Temperature (Temp.), pH, electrical conductivity (EC), total dissolved solids (TDS), total alkalinity (TA), total hardness (TH), total organic carbon (TOC), bicarbonate (HCO3−), chloride (Cl−), phosphate (PO43−), sulfate (SO42−), nitrite (NO2−), nitrate (NO3−), sodium (Na+), potassium (K+), calcium (Ca2+) and magnesium (Mg2+). The present study utilized the Canadian Council of Ministers of the Environment water quality index (CCME-WQI) model to assess water quality for drinking purposes. In addition, nine indices including EC, TDS, TH, sodium adsorption ratio (SAR), percent sodium (Na%), permeability index (PI), Kelley's ratio (KR), magnesium hazard ratio (MHR), soluble sodium percentage (SSP), and Residual sodium carbonate (RSC) were used in this research for assessing the water quality for irrigation purposes. The computed mean CCME-WQI score found higher during the dry season (ranges 48 to 74) than the wet season (ranges 40 to 65). Moreover, CCME-WQI model ranked groundwater quality between the “poor” and “marginal” categories during the wet season implying unsuitable water for human consumption. Like CCME-WQI model, majority of the irrigation index also demonstrated suitable water for crop cultivation during dry season. The findings of this research indicate that it requires additional care to improve the monitoring programme for protecting groundwater quality in the RNPP area. Insightful information from this study might be useful as baseline for national strategic planners in order to protect groundwater resources during the any emergencies associated with RNPP.

Nowadays, with the proliferation of different news sources, fake news detection is becoming a crucial topic to research. Millions of articles are published daily in the press, on social media, and in electronic media, and many of them may be fake. It is common for scammers to spread fake news to mislead people for malicious purposes. For researchers to be able to evaluate fake news, it is necessary to understand its diversity, how to study it, how to detect it, and its limitations. A descriptive literature review has been conducted in this paper to identify more appropriate methodologies for analysing fake news. The review found two broad classifications in the fake news research methodologies: fake news study perspectives and fake news detection techniques. Based on our literature review, we suggest four perspectives to study fake news and two major approaches to detecting it. Fake news can be studied in terms of knowledge, style, propagation and source. In order to detect fake news, there are two major approaches: manually and automatically. There are two types of manual fact-checks: expert-based and crowd-sourced. Automatic techniques are based mainly on data science methods, specifically deep learning and machine learning. A machine learning-based method was found to be more appealing when we evaluated all the automatic methods. Further research will focus on investigating the efficacy of using Bayesian methods for detecting fake news statistically because it is a flexible approach that allows for rapid updating of models in response to new data and has been successfully applied to a wide range of problems across different domains.

In recent years, organic agriculture has gained more popularity, yet its approach to food production and its potential impact on consumers’ health and various environmental aspects remain to be fully discovered. The goal of organic farming practices is to maintain soil health, sustain ecological systems, maintain fairness in its relationship with the environment and protect the environment in its entirety. Various health benefits have been associated with higher consumption of organic foods. This review identified some of these health benefits, including a reduction in obesity and body mass index (BMI), improvements in blood nutrient composition as well as reductions in maternal obesity and pregnancy-associated preeclampsia risks. Furthermore, organic food consumption can reduce the development of non-Hodgkin lymphoma (NHL) and colorectal cancers. Upon reviewing the existing literature regarding the nutritional value of organic foods, it was found that organic food contained higher levels of iron, magnesium and vitamin C. However, the evidence available to draw definitive causations remains limited due to study biases, short study durations and confounding variables; thus, it cannot be concluded that the organic diet provides any related health benefits. In this review, we provided essential insights and statistical analysis from the evidence available and consider study limitations to evaluate the potential of organic food consumption in positively impacting human health.

Abstract Introduction This study investigated differences between rural Australian First Nations and non-First Nations survey respondents’ perceptions of COVID-19-related risks and analysed other variables that could predict an exacerbation of anxiety related to COVID-19 harms. Methods A cross-sectional online and paper survey of rural residents from the western regions of NSW, Australia, was conducted. Descriptive and multivariate statistical analyses were used to assess links between First Nations status and demographic measures including postcode, age, gender, education, rural or town/village location, proximity to medical services and living situation. The analysis included five items related to perceptions about COVID-19: perceived likelihood of contracting COVID-19 in the next 12 months, perceived harmfulness of the virus, how often people felt afraid, perception about respondents’ ability to do something about the virus and perceived economic impacts of the pandemic. Results There were significant differences between First Nations (n=60) and non-First Nations (n= 639) respondents across all sociodemographic categories. The results reflect a significantly higher level of anxiety among the First Nations Australians in the sample: they felt afraid more often, felt it was highly likely they would catch the virus and if they did catch the virus perceived that it would be very harmful. Living with children under eighteen years of age and in small rural towns were key factors linked to feeling afraid of COVID-19 and First Nations status. Conclusion Health risk communication in pandemic response should include an equitable focus on rural areas, recognising that First Nations Australians are a significant proportion of the rural population with different risk factors and concerns than those of non-First Nations Australians. This principle of First Nations-led design is critical to all health policy and planning. The Australian Government should include rural areas in planning pandemic responses, recognising that First Nations populations are a significant proportion of the rural population creating syndemic conditions.

Background and aimsThe key interest of this research is to identify the causes of the ongoing increasing trends in caesarean section or C-section (CS) deliveries in both urban and rural areas of Bangladesh.MethodsThis study analyzed all Bangladesh Demographic and Health Survey (BDHS) datasets through Chi-square and z tests and the multivariable logistic regression model.ResultsCS deliveries were found to be more prevalent in urban than in rural areas of Bangladesh. Mothers above 19 years, above 16 years at first birth, overweight mothers, those with higher educational levels, those who received more than one antenatal care (ANC) visit, fathers having secondary/higher education degrees and employed as workers or in business, and mothers living in wealthy households in the cities of Dhaka, Khulna, Mymensingh, Rajshahi, and Rangpur divisions had a significantly higher likelihood of CS deliveries in urban areas. Contrastingly, mothers with ages between 20 and 39 years, above 20 years at first birth, normal weight/overweight mothers, those with primary to higher level of education, those in the business profession, fathers who also received primary to higher education, mothers who received more than one ANC visit, and those living in wealthy households in Dhaka, Khulna, Mymensingh, Rajshahi, and Rangpur divisions were more likely to have CS deliveries in rural areas. The 45–49 age group mothers had a five times higher likelihood of CS deliveries [odds ratio (OR): 5.39] in urban areas than in rural areas. Wealthy mothers were more likely to be CS-delivered in urban (OR: 4.84) than in rural areas (OR: 3.67).ConclusionThe findings reveal a gradual upward alarming trend in CS deliveries with an unequal contribution of significant determinants in urban and rural areas of Bangladesh. Therefore, integrated community-level awareness programs are an urgent need in accordance with the findings on the risks of CS and the benefits of vaginal deliveries in this country.

Abstract Background Although efforts have been made by the international community to improve childhood health, risk factors linked with the healthiness of preschool-age children in low and middle-income countries (LMICs) are very diverse. Therefore, this paper examines the prevalence and determinants of fever, acute respiratory infection and diarrhea of preschool children in Bangladesh. Methods A sample of 8,421 children from the latest country representative BDHS-2017–18 survey was analyzed by utilizing both the bivariate and multivariate techniques. Results The results revealed that about 4.7, 33.1, and 35.8% of the children aged under 5 years had suffered from diarrhea, fever and ARI respectively during the 2 weeks preceding the date of the survey. Demographic, socio-economic, and community and health characteristics likely to play an important role in suffering under-five children from diarrhea, fever, and ARI in Bangladesh. The child’s age of 13–24 months, delivery by cesarean section, unsafe drinking water, unhygienic toilet facility, low level of family wealth index and parental education, a higher number of living children in the household, rural residency and regional difference were all found to be most crucial determinants of the occurrences of fever, ARI and diarrhea. Conclusion Interventions should focus on improving these significant demographic, socioeconomic, and community and health risk factors. A special attention is necessary to the people who live in rural areas and geospatially disadvantaged regions.

Abstract The challenge of accurately short-term forecasting demand is due to model selection and the nature of data trends. In this study, the prediction model was determined based on data patterns (trend data without seasonality) and the accuracy of prediction measurement. The cumulative number of COVID-19 affected people in some ASEAN countries had been collected from the Worldometers database. Three models [Holt’s method, Wright’s modified Holt’s method, and unreplicated linear functional relationship model (ULFR)] had been utilized to identify an efficient model for short-time prediction. Moreover, different smoothing parameters had been tested to find the best combination of the smoothing parameter. Nevertheless, using the day-to-day reported cumulative case data and 3-days and 7-days in advance forecasts of cumulative data. As there was no missing data, Holt’s method and Wright’s modified Holt’s method showed the same result. The text-only result corresponds to the consequences of the models discussed here, where the smoothing parameters (SP) were roughly estimated as a function of forecasting the number of affected people due to COVID-19. Additionally, the different combinations of SP showed diverse, accurate prediction results depending on data volume. Only 1-day forecasting illustrated the most efficient prediction days (1 day, 3 days, 7 days), which was validated by the Nash–Sutcliffe efficiency (NSE) model. The study also validated that ULFR was an efficient forecasting model for the efficient model identifying. Moreover, as a substitute for the traditional R-squared, the study applied NSE and R-squared (ULFR) for model selection. Finally, the result depicted that the prediction ability of ULFR was superior to Holt’s when it is compared to the actual data.

In the insurance and pension industries, as well as in designing social security systems, forecasted mortality rates are of major interest. The current research provides statistical methods based on functional time series analysis to improve mortality rate prediction for the Canadian population. The proposed functional time series-based model was applied to the three-mortality series: total, male and female age-specific Canadian mortality rate over the year 1991 to 2019. Descriptive measures were used to estimate the overall temporal patterns and the functional principal component regression model (fPCA) was used to predict the next ten years mortality rate for each series. Functional autoregressive model (fAR (1)) was used to measure the impact of one year age differences on mortality series. For total series, the mortality rates for children have dropped over the whole data period, while the difference between young adults and those over 40 has only been falling since about 2003 and has leveled off in the last decade of the data. A moderate to strong impact of age differences on Canadian age-specific mortality series was observed over the years. Wider application of fPCA to provide more accurate estimates in public health, demography, and age-related policy studies should be considered.

Abstract Background Intimate partner violence (IPV) is a global public health concern, with women in low- and middle-income countries (LMICs) bearing a disproportionately high burden. This study investigates the prevalence and factors correlated with attitudes regarding wife-beating among Bangladeshi women in urban–rural contexts. Methods A sample of 13,033 urban women and 51,344 rural women data from the Bangladesh Multiple Indicator Cluster Survey (MICS) 2019 were analyzed using the Chi-square test and ordinal logistic regression model. Results The findings reveal that arguing with her husband is the widespread reason for wife-beating in Bangladesh (urban: 17.3%, rural: 21.9%), followed by neglecting the children (urban: 12.7%, rural: 15.8%). About 8% of urban women and 10% of rural women favoured the opinion that refusing to involve sexual intercourse is a legitimate justification for wife-beating. In comparison, around 5% feel that a husband has a right to beat his wife due to burning food. The respondents’ age, education, marital status, number of children, socioeconomic level, any health or physical difficulty, having problems becoming pregnant, and the husband’s age are all significant factors in justifying wife-beating. Conclusions Bangladesh has a massive challenge in eliminating IPV. Women from lower socioeconomic classes, low levels of education, other challenges, and residents of rural areas are particularly more vulnerable than their urban counterparts. Therefore, it is vital to develop a proper action plan that considers women’s education and occupation to raise awareness of the various implications of wife-beating in women, particularly in Bangladesh’s rural areas.

In recent years measles has been one of the most critical public health problem in Bangladesh. Although the Ministry of Health in Bangladesh employs a broad extension of measles control policies, logistical challenges exist, and there is significant doubt regarding the disease burden. Mathematical modelling of measles is considered one of the most effective ways to understand infection transmission and estimate parameters in different countries, such as Bangladesh. In this study, a mathematical modelling framework is presented to explore the dynamics of measles in Bangladesh. We calibrated the model using cumulative measles incidence data from 2000 to 2019. Also, we performed a sensitivity analysis of the model parameters and found that the contact rate had the most significant influence on the basic reproduction number R0. Four hypothetical intervention scenarios were developed and simulated for the period from 2020 to 2035. The results show that the scenario which combines enhanced treatment for exposed and infected population, first and second doses of vaccine is the most effective at rapidly reducing the total number of measles incidence and mortality in Bangladesh. Our findings also suggest that strategies that focus on a single interventions do not dramatically affect the decline in measles incidence cases; instead, those that combine two or more interventions simultaneously are the most effective in decreasing the burden of measles incidence and mortality. In addition, we also evaluated the cost-effectiveness of varying combinations of three basic control strategies including distancing, vaccination and treatment, all within the optimal control framework. Our finding suggested that combines distancing, vaccination and treatment control strategy is the most cost-effective for reducing the burden of measles in Bangladesh. Other strategies can be comprised to measles depending on the availability of funds and policymakers' choices.

Enterobacter cloacae is a Gram-negative rod with multidrug-resistant potential due to chromosomally-induced AmpC β-lactamase. We evaluated characteristics, antibiotic utilization, and outcomes associated with battlefield-related E. cloacae infections (2009-2014). Single initial and serial E. cloacae isolates (≥24 hours from initial isolate from any site) associated with a clinical infection were examined. Susceptibility profiles of initial isolates in the serial isolation group were contrasted against last isolate recovered. Characteristics of 112 patients with E. cloacae infections (63 [56%] with single initial isolation; 49 [44%] with serial isolation) were compared to 509 patients with bacterial infections not attributed to E. cloacae. E. cloacae patients sustained more blast trauma (78%) compared to non-E. cloacae infections patients (75%; p

Since November 2019, most countries across the globe have suffered from the disastrous consequences of the Covid-19 pandemic which redefined every aspect of human life. Given the inevitable spread and transmission of the virus, it is critical to acknowledge the factors that catalyse transmission of the disease. This research investigates the relation of the external demographic parameters such as total population, population density and weighted population density on the spread of Covid-19 in Malaysia. Pearson correlation and simple linear regression were utilized to identify the relation between the population-related variables and the spread of Covid-19 in Malaysia using data from 15th March 2020 to 31st March 2021. As a result, a strong positive significant correlation between the total population and Covid-19 cases was found. However, a weak positive relationship was found between the density variable (population density and weighted population density) and the spread of Covid-19. Our findings suggest that the transmission of Covid-19 during lockdown (Movement Control Order, MCO) in Malaysia was more readily explained by the demographic variable population size, than population density or weighted population density. Thus, this study could be helpful in intervention planning and managing future virus outbreaks in Malaysia.

BackgroundUnderweight is one of the important anthropometric components of malnutrition among under-five children and is a major public health concern in Bangladesh because it contributes to mortality as well as morbidity. In designing suitable health programs and policies with the goal of attaining UN SDG Goals, it is necessary to identify the critical risk factors of under-five malnutrition. It is evident that the quantile regression produces robust estimates in the presence of outliers. However, in the context of Bangladesh, no study has been conducted considering the sequential quantile regression on this topic. Therefore, the authors aimed to find the determinants of underweight among under-5 children in Bangladesh considering the latest country representative dataset.Methods and materialsThe paper considers a weighted sample of size 7762 children are used and data were extracted from the latest Bangladesh Demographic and Health Survey (BDHS) 2017-18 data. Multivariable simultaneous quantile regression models were used to fulfill the objectives of this study.ResultsFindings depict that undernutrition affects the majority of children in the population as compared to the reference population. The WAZ-score of the child increases by 0.202 points at the 10th quantile of the conditional distribution, and by 0.565 points at the 90th quantile as we move from children of underweight to overweight women. Moreover, the WAZ scores of children from the richest families in the 10th, 50th, and 75th quantiles, respectively, are increased by 0.171, 0.016, and 0.084 points.ConclusionQuantile regression revealed the results of several socioeconomic and demographic factors acting differently across the WAZ distribution. Therefore, policymakers may consider the identified risk factors to lessen malnutrition among under-5 children in Bangladesh.

BackgroundThe child nutritional status of a country is a potential indicator of socioeconomic development. Child malnutrition is still the leading cause of severe health and welfare problems across Bangladesh. The most prevalent form of child malnutrition, stunting, is a serious public health issue in many low and middle-income countries. This study aimed to investigate the heterogeneous effect of some child, maternal, household, and health-related predictors, along with the quantiles of the conditional distribution of Z-score for height-for-age (HAZ) of under five children in Bangladesh.Methods and materialsIn this study, a sample of 8,321 children under five years of age was studied from BDHS-2017-18. The chi-square test was mainly used to identify the significant predictors of the HAZ score and sequential quantile regression was used to estimate the heterogeneous effect of the significant predictors at different quantiles of the conditional HAZ distribution.ResultsThe findings revealed that female children were significantly shorter than their male counterparts except at the 75th quantile. It was also discovered that children aged 7-47 months were disadvantaged, but children aged 48-59 months were advantaged in terms of height over children aged 6 months or younger. Moreover, children with a higher birth order had significantly lower HAZ scores than 1st birth order children. In addition, home delivery, the duration of breastfeeding, and the BCG vaccine and vitamin A received status were found to have varied significant negative associations with the HAZ score. As well, seven or fewer antenatal care visits was negatively associated with the HAZ score, but more than seven antenatal care visits was positively associated with the HAZ score. Additionally, children who lived in urban areas and whose mothers were over 18 years and either normal weight or overweight had a significant height advantage. Furthermore, parental secondary or higher education had a significant positive but varied effect across the conditional HAZ distribution, except for the mother's education, at the 50th quantile. Children from wealthier families were also around 0.30 standard deviations (SD) taller than those from the poorest families. Religion also had a significant relationship with the conditional HAZ distribution in favor of non-Muslim children.ConclusionsTo enhance children's nutritional levels, intervention measures should be designed considering the estimated heterogeneous effect of the risk factors. This would accelerate the progress towards achieving the targets of Sustainable Development Goals (SDGs) related to child and maternal health in Bangladesh by 2030.

Objectives: The ongoing COVID-19 pandemic, caused by a novel coronavirus SARS-CoV-2, has created a severe threat to global human health. We are extremely lucky because within the first year of the COVID-19 pandemic, scientists developed a number of vaccines against COVID-19. In this paper, the authors discuss the difficulties and challenges faced in different low-and middle-income countries due to the ongoing pandemic. Study design and methods: This research is primarily based on secondary data and existing literature reviews. The authors use maps and graphical representations to show information about vaccination coverage. Results: The lacking vaccination coverage and insufficient supply of oxygen tanks in hospitals of low- and middle-income countries (LMICs) raise the likelihood of death of the critical COVID-19 patients. Developed countries vaccinate their citizens more quickly than LMICs. In comparison to wealthy countries, LMICs usually lack the resources and capacity to obtain the required vaccination doses. Conclusion: It is frequently observed that hospitals in low- and middle-income nations with a dearth of oxygen tanks result in increased suffering and mortality. To avoid a worldwide disaster, LMICs urgently require COVID-19 vaccinations since viruses have no borders, and no one is safe until every one is protected in our interconnected world. Therefore, more national and international collaborative supports are urgently necessary for LMICs in this regard.

Abstract The long‐term impact of this pandemic will continue in almost all sectors of a country such as health, economic situations, education, mental health, and violence. Therefore, the authors intended to discuss the prolonged effect of COVID‐19 on the health along with wellbeing, education, and economy of Bangladesh through a mixed approach. To assess the possible scenario in health sector of Bangladesh, we conducted a short survey through online with a structured questionnaire. The impact of the pandemic is highlighted by graphical presentations and discussed the issues in light of the existing literature. It is realized that health care services and resources are always essential for predominant health conditions and fatal diseases patients. Mental health has also been impacted a lot during this pandemic. Moreover, students of only those schools located in urban areas are attended some online classes but due to the internet interruption and scarcity of devices students from rural areas cannot attend the classes and it will widen the gap between pupils from urban areas and those who live in remote rural areas. Additionally, many students terminate school. The country's youth unemployment is projected to intensify as a result of the economic effects, which would promote antisocial behavior and cause social discontent among young people. Also, the flow of remittances greatly declined in the last couple of months and a many people were jobless abroad, and the majority of them were sent back home. The demographic dividend's intended results are expected to be negatively impacted by COVID‐19's overall effect as well as sustainable development goals (SDGs) in Bangladesh. Therefore, many social services systems need strategic backup resources at community, national, and global levels if any basic system may collapse due to COVID‐19 and socio‐economic as well as geopolitical negligence in handling post‐pandemic challenges.

Abstract Background Vaccination has important consequences for childhood development, mortality, and inequalities in health and well-being. This research explores the trend of vaccinations coverage from 1993 to 2014 and determines the significant factors for vaccinations coverage in Bangladesh, considering geospatial, socioeconomic, and demographic characteristics. Methods This study uses a secondary dataset extracted from the Bangladesh Demographic and Health Survey (BDHS) from 1992 to 93 to 2014. The association between selected independent variables and vaccination coverage of children was examined through the Chi-square test. In addition, unadjusted and adjusted logistic regression approaches were applied to determine the effects of covariates on vaccination status by using the BDHS-2014 dataset. Results The results reveal that the trend of the vaccination coverage rate has gradually been increased over the study period. The coverage rate of BCG is observed maximum while the lowest for Measles vaccination among all types of vaccinations. The findings revealed that the significantly lower coverage of all vaccination had been observed in the Sylhet region. Children of higher educated mothers (OR 10.21; CI: 4.10–25.37) and father (OR 8.71; CI: 4.03–18.80), born at health facilities (OR 4.53; CI: 2.4–8.55) and whose mother has media exposure (OR 3.20; CI: 2.22–4.60) have more chance of receiving BCG vaccine. For DPT vaccination coverage, there is a significant difference from children whose mothers have primary (OR 1.7; CI: 1.35–2.15), secondary (OR 3.5; CI: 2.75–4.45), and higher (OR 9.6; CI: 5.28–17.42) educational qualification compared to children of illiterate mothers. Findings demonstrated that children born in wealthier households have a higher likelihood of being immunized against DPT, Polio, and Measles vaccination than children born in the poorest households. Conclusions The findings reveal that to enhance and make sustainable the overall country’s vaccination coverage, we should pay more attention to the mother’s education, socioeconomic condition, children’s age, birth order number, having media exposure, place of residence, and religion. The authors think that this finding would be helpful to accelerate the achievement target of Sustainable Development Goals (SDGs) for children’s health in Bangladesh.

Abstract Background Vitamin A supplementation reduces child morbidity, mortality, and blindness of people, especially in developing countries like Bangladesh. This study explores significant determinants of vitamin A deficiency among preschool children in rural and urban areas of Bangladesh. Methods The data set was extracted from a nationally representative survey based on a cross-sectional study, the BDHS-2017-18. The base survey was conducted using a two-stage stratified sample of households. A sample of 8364 (urban 2911, rural 5453) children under-5 years old was analyzed using bivariate and multivariate statistical techniques. Results Results have demonstrated that 73.9 and 73.2% of children have had a vitamin A supplementation from urban and rural areas, respectively. Logistic regression analysis showed that parents’ education plays a vital role in consuming vitamin A supplements in urban and rural areas. Children whose mothers have secondary (OR: 1.17, CI: 0.76–1.81) and higher (OR: 1.21, CI: 0.72–2.04) education were more likely to consume vitamin A supplementation than children whose mothers were illiterate in urban areas. However, in rural areas, children whose mothers have secondary education were about 24% and higher education with 60% more likely to consume vitamin A supplementation than children whose mothers were illiterate. Child’s age, regional variation and wealth index also contributing factors for vitamin A deficiency in Bangladesh. Conclusions These findings indicated that the consumption of vitamin A does not cover the target of sustainable development goals. Thus special national and community level efforts are required to ensure the coverage of the national vitamin A program is increased adequately to the most vulnerable groups of children in Bangladesh.

Abstract Although the availability of the measles vaccine, it is still epidemic in many countries globally, including Bangladesh. Eradication of measles needs to keep the basic reproduction number less than one $$(\mathrm{i}.\mathrm{e}. \, \, {\mathrm{R}}_{0}1)$$ ( i . e . R 0 > 1 ) epidemic occurs. While using the Routh-Hurwitz criteria, the equilibria are found to be locally asymptotically stable under the former condition on $${\mathrm{R}}_{0}$$ R 0 . The partial rank correlation coefficients (PRCCs), a global sensitivity analysis method is used to compute $${\mathrm{R}}_{0}$$ R 0 and measles prevalence $$\left({\mathrm{I}}^{*}\right)$$ I ∗ with respect to the estimated and fitted model parameters. We found that the transmission rate $$(\upbeta )$$ ( β ) had the most significant influence on measles prevalence. Numerical simulations were carried out to commissions our analytical outcomes. These findings show that how progression rate, transmission rate and double dose vaccination rate affect the dynamics of measles prevalence. The information that we generate from this study may help government and public health professionals in making strategies to deal with the omissions of a measles outbreak and thus control and prevent an epidemic in Bangladesh.

In recent years, the adverse effect of climate change on soil properties in the agricultural sector has become a dreadful reality worldwide. Climate change-induced abiotic stresses such as salinity, drought and temperature fluctuations are devastating crops’ physiological responses, productivity and overall yield, which is ultimately posing a serious threat to global food security and agroecosystems. The applications of chemical fertilizers and pesticides contribute towards further deterioration and rapid changes in climate. Therefore, more careful, eco-friendly and sustainable strategies are required to mitigate the impact of climate-induced damage on the agricultural sector. This paper reviews the recently reported damaging impacts of abiotic stresses on various crops, along with two emerging mitigation strategies, biochar and biostimulants, in light of recent studies focusing on combating the worsening impact of the deteriorated environment and climate change on crops’ physiological responses, yields, soil properties and environment. Here, we highlighted the impact of climate change on agriculture and soil properties along with recently emerging mitigation strategies applying biochar and biostimulants, with an aim to protecting the soil, agriculture and environment.

Abstract Background Vitamin A deficiency (VAD) is a prominent and widespread public health problem in developing countries, including Bangladesh. About 2% of all deaths among under-five children are attributable to VAD. Evidence-based information is required to understand the influential factors to increase vitamin A supplementation (VAS) coverage and reduce VAD. We investigated the potential factors affecting VAS coverage and its significant predictors among Bangladeshi children aged 6 to 59 months using the VAS clustered data extracted from the latest Bangladesh Demographic and Health Survey 2014. Methods Data were analysed using mixed logistic regression (MLR) modelling approach in the generalised linear mixed model framework. The MLR model performs better than logistic regression for analysing the clustered data because of its minimum Akaike information criterion value. The likelihood ratio test showed that the variance component was significant. Therefore, the clustering effect among children was inevitable to use. Results VAS coverage among under-five children was 63.6%, which is not optimal and below the WHO’s recommendation and the country’s target of 90%. Children aged 25 to 36 months (AOR = 2.07, 95% CI: 1.711 to 2.513), who had higher educated mothers (AOR = 1.37, p = 0.033, 95% CI: 1.026–1.820) and fathers (AOR = 1.32, p = 0.027, 95% CI: 1.032–1.683), whose mothers had media exposure (AOR = 1.22, p = 0.006, 95% CI: 1.059–1.408) and NGO membership (AOR = 1.24, p = 0.002, 95% CI: 1.089–1.422) were more likely to consume VAS. Conclusion The relevant authorities should create proactive awareness programs for highly vulnerable local communities, specifically targeted to educate the children’s mothers about the necessity and benefits of childhood nutrition.

Hippocratic treatises are early text of medicine, compiled by several scholars, collectively known as Hippocratic Corpus. For the first times in history, Hippocrates rejects the divine theory of disease and laid-down the foundation of scientific medicine. Diseases were described on natural causes. They proposed humoral theory of diseases. According to this theory, there are four humors in the body. Harmony among these humors constitutes a good health. Age, sex, season, diet and regime affect the production of humors and impart their effect on the condition of body. Various ways were adopted for categorization and classification of diseases, making medical studies easier. In these treatises, diseases were broadly categorized based on age, sex and population distribution. Nomenclature of disease was also based upon the name of diseased organ, dominating symptom, etiology and its resemblance with the thing and phenomenon in outer world. This study is focused on understanding Hippocratic classification and categorization of diseases.

Background: The accurate estimation of temporal patterns of influenza may help in utilizing hospital resources and guiding influenza surveillance. This paper proposes functional data analysis (FDA) to improve the prediction of temporal patterns of influenza. Methods: We illustrate FDA methods using the weekly Influenza-like Illness (ILI) activity level data from the U.S. We propose to use the Fourier basis function for transforming discrete weekly data to the smoothed functional ILI activities. Functional analysis of variance (FANOVA) is used to examine the regional differences in temporal patterns and the impact of state's political orientation. Results: The ILI activity has a very distinct peak at the beginning and end of the year. There are significant differences in average level of ILI activities among geographic regions. However, the temporal patterns in terms of the peak and flat time are quite consistent across regions. The geographic and temporal patterns of ILI activities also depend on the political make-up of states. The states affiliated with Republicans had higher ILI activities than those affiliated with Democrats across the whole year. The influence of political party affiliation on temporal pattern is quite different among geographic regions. Conclusions: Functional data analysis can help us to reveal the temporal variability in average ILI levels, rate of change in ILI levels, and the effect of geographical regions. Consideration should be given to wider application of FDA to generate more accurate estimates in public health and biomedical research.

Surgical site infections (SSIs) are the second most common nosocomial (hospital-acquired) infections after urinary tract infections. Despite recent advances in aseptic techniques, till now SSI has been considered as a major source of morbidity and mortality in developing countries and continued to represent about one fifth of all healthcare-associated infections. This cross-sectional study was conducted to analyze the pattern & aetiological factors of SSI among patients undergoing surgery at Sir Salimullah Medical College Mitford Hospital, Dhaka, Bangladesh involving 160 admitted patients during the study period. Of all SSIs, 73.0% were superficial and 27.0% were deep infections. Among the risk factors, Hypertension (29.4%), Diabetes Mellitus (24.4%), old age (>60 yr) [19.4%], anaemia (28.7%), and below average nutrition (13.8%) were the most common and had statistically significant relation with SSIs (p

The current study aims to explore relationship between manufacturing metrics or manufacturing performance factors and manufacturing fitness, which establishes the basis for manufacturing strategy. Previous researches on manufacturing strategies and competitive strategies to measure firm performance guided the manufacturers towards further developments. To emphasize these developments, this study continued after the development of strategic fit models by generalizing these models through linear structural relations (LISREL) analysis. Results from hypotheses tests and LISREL analysis found manufacturing metrics are directly linked to firm’s performance. This article found strong relation of availability of materials (AM) to order variation handling (OVH) & order fill rate (OF); OVH, problem handling (PH), & OF to shipment time (ST); and ST to strategic fitness (SF). Identification of affecting metrics and determination of their strength & significance to manufacturing fitness by using this article’s generalized models & firm’s performance determinants is the main significance of this article.

BackgroundWasting is perhaps one of the signs of malnutrition that has been linked to the deaths of children suffering from malnutrition. As a result, understanding its correlations and drivers is critical. Using quantile regression analysis, this research aims to contribute to the discussion on under-5 malnutrition by analyzing the predictors of wasting in Bangladesh.Methods and materialsThe dataset was extracted from the 2017-18 Bangladesh demographic and health survey (BDHS) data. The weight-for-height (WHZ) z-score based anthropometric indicator was used in the study as the target variable. The weighted sample constitutes 8,334 children of under-5 years. However, after cleaning the missing values, the analysis is based on 8,321 children. Sequential quantile regression was used for finding the contributing factors.ResultsThe findings of this study depict that the prevalence of wasting in children is about 8 percent and only approximately one percent of children are severely wasted in Bangladesh. Age, mother's BMI, and parental educational qualification, are all major factors of the WHZ score of a child. The coefficient of the female child increased from 0.1 to 0.2 quantiles before dropping to 0.75 quantile. For a child aged up to three years, the coefficients have a declining tendency up to the 0.5 quantile, then an increasing trend. Children who come from the richest households had 16.3%, 3.6%, and 15.7% higher WHZ scores respectively than children come from the poorest households suggesting that the risk of severe wasting in children under the age of five was lower in children from the wealthiest families than in children from the poorest families. The long-term malnutrition indicator (wasting) will be influenced by the presence of various childhood infections and vaccinations. Furthermore, a family's economic position is a key determinant in influencing a child's WHZ score.ConclusionsIt is concluded that socioeconomic characteristics are correlated with the wasting status of a child. Maternal characteristics also played an important role to reduce the burden of malnutrition. Thus, maternal nutritional awareness might reduce the risk of malnutrition in children. Moreover, the findings disclose that to enrich the nutritional status of children along with achieving Sustainable Development Goal (SDG)-3 by 2030, a collaborative approach should necessarily be taken by the government of Bangladesh, and non-governmental organizations (NGOs) at the community level in Bangladesh.

Introduction Child marriage is a significant social and health concern in many low- and middle-income countries (LMICs). This harmful practice violates children’s rights and continues to be widespread across developing nations like Bangladesh. This study investigated the mortality trend among Bangladeshi children and the impact of child marriage on under-5 children morbidity and mortality in Bangladesh. Methods and materials A sample of 8,321 children under-5 years old was analyzed using bivariate and multivariate statistical techniques collected from the recent 2017–18 BDHS data. Chi-square test and logistic regression (unadjusted and adjusted) were used to determine the influence of covariates on the target variable. Results Results revealed that child mortality was significantly higher among children whose mothers married at an early age than their counterparts. Although the general trend in the prevalence of different childhood mortality in Bangladesh was declining gradually from 1993 to 2018, it was still high in 2018. Also, marriage after 18 years lessens likelihood of diarrhea (adjusted OR = 0.93; 95% CI: 0.76–1.16) and cough (adjusted OR = 0.91; 95% CI: 0.78–1.17) among children. Furthermore, findings reveal that likelihood of different child mortality is higher among early married women. Conclusion Immediate intervention through rigorous enforcement of policies and different programs to raise the age at marriage and by lessening socioeconomic disparities can combat the prevalence of high morbidity and mortality of under-5 years old children. Findings from this study will be helpful to accelerate strategies for achieving the Sustainable Development Goals (SDGs) related to child and maternal health by 2030.

BackgroundBangladesh is a South Asian developing country trying to achieve the Sustainable Development Goals (SDG)-3 and the objective of the Rural Electrification Board (REB) regarding child mortality. Infectious diseases are leading causes of child mortality, and lack of exclusive breastfeeding (EBF) among infants aged 0-6 months increases child morbidity and mortality from various infectious diseases in developing countries. However, as per existing literature, no study has been conducted yet to determine the lack of EBF practice effect on child mortality in Bangladesh. With this backdrop, the authors intend to measure the likelihood of infectious diseases due to the lack of EBF of infants aged 0-6 months in Bangladesh.Materials and methodsThis study used Bangladesh Demographic and Health Survey (BDHS) data over 1996-97 to 2017-18. The mothers of infants aged 0-6 months who were willingly participated in the BDHSs were considered to include in our analysis. Initially, there were 9,133 cases in the combined dataset. After filtering, there were 5,724 cases in the final dataset. We have considered diarrhea (D), acute respiratory infection (ARI) separately as well as the presence of either D or ARI or both and named as CoDARI as outcome variables. This study used both graphical and statistical techniques (Chi-square test, Wald test, and logistic regression) to analyze the data. The odds ratio (OR) and 95% confidence interval (CI) were used to quantify the likelihood of infectious diseases due to lack of EBF practice and its elasticity, respectively.ResultsThe EBF practice got a conspicuous increasing trend, but the prevalence of infectious diseases was declined from 0 to 3 months of age of infants, whereas an inverse scenario is observed between 4-6 months. The significance of that inverse relationship was confirmed by p-value corresponding to the chi-square test and the Wald test of the adjusted regression coefficients after adjusting the associated factor's effect on infectious diseases. The adjusted ORs also concluded that the lack of EBF practice up to six months of age could enhance the risk of D, ARI, and CoDARI by 2.11 [95% CI: 1.56-2.85], 1.43 [95% CI: 1.28-1.60], and 1.48 [95% CI: 1.32-1.66] times higher, respectively.ConclusionFindings of this study emphasize the importance of EBF up to six months of age of infants against diarrhea and ARI specific morbidity and mortality. Our results also agreed to the recommendation of the World Health Organization (WHO), United Nations International Children's Emergency Fund (UNICEF), American Academy of Pediatrics (AAP), American Academy of Family Physicians (AAFP), and National Nutrition Programme of Ethiopia (NNPE) that the EBF practice for the first six months of age could be a best, cost-effective, long-lasting natural preventive way to reduce the child morbidity and mortality due to infectious diseases in developing countries. Therefore, findings would help policymakers ensuring the achievement target of REB and SDG-3 associated with the health sector in Bangladesh.

Infectious diseases kill millions of people each year, and they are the major public health problem in the world. This paper presents a modified Susceptible-Latent-Infected-Removed (SLIR) compartmental model of disease transmission with nonlinear incidence. We have obtained a threshold value of basic reproduction number (R0) and shown that only a disease-free equilibrium exists when R01. With the help of the Lyapunov-LaSalle Invariance Principle, we have shown that disease-free equilibrium and endemic equilibrium are both globally asymptotically stable. The study has also provided the model calibration to estimate parameters with month wise coronavirus (COVID-19) data, i.e. reported cases by worldometer from March 2020 to May 2021 and provides prediction until December 2021 in China. The Partial Rank Correlation Coefficient (PRCC) method was used to investigate how the model parameters’ variation impact the model outcomes. We observed that the most important parameter is transmission rate which had the most significant impact on COVID-19 cases. We also discuss the epidemiology of COVID-19 cases and several control policies and make recommendations for controlling this disease in China.