Luthful Alahi Kawsar

Multimorbidity is a complex and highly prevalent health condition characterised by the coexistence of two or more chronic diseases within an individual. It is a growing public health issue worldwide, predominantly in low‐resource countries like Bangladesh. Therefore, this study aimed to determine the prevalence and associated factors of multimorbidity among the adult population in Bangladesh. A cross‐sectional study was carried out among 504 respondents who were 18 years or older. The generalised linear mixed model was used to identify the risk factors. Among the respondents, 65.3% (95% confidence interval [CI]: 61.0 to 69.3) had multimorbidity. The most common chronic conditions were allergic disorder (34%, 95% CI: 30 to 39), gastritis (31%, 95% CI: 27 to 35), low back pain (28.4%, 95% CI: 24.6 to 32.5), oral diseases (27%, 95% CI: 23 to 29) and arthritis (21%, 95% CI: 18 to 25). Middle‐aged adults (adjusted odds ratio [AOR] = 7.97; 95% CI: 3.35 to 18.92) and older adults (AOR = 8.44; 95% CI: 1.90 to 36.64) had significantly higher odds of multimorbidity than young adults. Employed respondents had an 86% (AOR = 0.14; 95% CI: 0.07 to 0.36) lower odds of multimorbidity than non‐working individuals. Higher sleeping duration (6 to 8 h: AOR = 0.44; 95% CI: 0.25 to 0.80; 8 to 10 h: AOR = 0.26; 95% CI: 0.11 to 0.60), regular vegetable consumption (AOR = 0.42; 95% CI: 0.22 to 0.80) and adequate water intake (AOR = 0.48; 95% CI: 0.29 to 0.79) were protective factors against multimorbidity, whereas obesity increased the odds (AOR = 3.32; 95% CI: 1.06 to 10.43). These findings emphasise the need to promote healthy lifestyle habits, such as maintaining a balanced diet, staying hydrated and engaging in regular physical exercise, to reduce the burden of multimorbidity in low‐resource settings.

Acute respiratory infection (ARI) and diarrhoea are two major causes of child morbidity and mortality in Bangladesh. National and regional level prevalence of ARI and diarrhoea are calculated from nationwide surveys; however, prevalence at micro-level administrative units (say, district and sub-district) is not possible due to lack of sufficient data at those levels. In such a case, small area estimation (SAE) methods can be applied by combining survey data with census data. Using an SAE method for the dichotomous response variable, this study aims to estimate the proportions of under-5 children experienced with ARI and diarrhoea separately as well as either ARI or diarrhoea within a period of two-week preceding the survey. The ARI and diarrhoea data extracted from Bangladesh Demographic and Health Survey 2011 are used to develop a random effect logistic model for each of the indicators, and then the prevalence is estimated adapting the World Bank SAE approach for the dichotomous response variable using a 5% sample of the Census 2011. The estimated prevalence of each indicator significantly varied by district and sub-district (1.4–11.3% for diarrhoea, 2.2–11.8% for ARI and 4.3–16.5% for ARI/diarrhoea at sub-district level). In many sub-districts, the proportions are found double of the national level. District and sub-district levels spatial distributions of the indicators might help the policymakers to identify the vulnerable disaggregated and remote hotspots. Particularly, aid industries can provide effective interventions at the highly vulnerable spots to overcome the gaps between micro and macro level administrative units.

A real-world topological network consists of multiple entrances along its source nodes. Routing appropriate percentages of pedestrians from these entrances to the particular available routes with relevant arrival rates will improve the network’s performance. This paper presents a framework for finding the optimal arrival rates of pedestrians from all available entrances and routes to downstream nodes maximising the network’s throughput. The calculation of the arrival rates and movement directions is based on M/G/C/C analytical and simulation models and the network flow model and considers the real distances of the entrances along the source nodes. The framework was tested on the Tuanku Syed Putra Hall, Universiti Sains Malaysia, Malaysia. Extensive analyses of the performances of its available nodes especially on the achievable optimal throughputs were documented and discussed. Quantitative results show that the hall’s throughput is optimised when pedestrians’ arrival rates to all the available entrances and their movement directions are controlled within certain ranges.

Acute respiratory infection (ARI) and diarrhoea are two major causes of child morbidity and mortality in Bangladesh. National and regional level prevalence of ARI and diarrhoea are calculated from nationwide surveys; however, prevalence at micro-level administrative units (say, district and sub-district) is not possible due to lack of sufficient data. In such case, small area estimation (SAE) methods can be applied by combining a survey data with a census data. Using a SAE method for dichotomous response variable, this study aims to estimate the proportions of under-5 children experienced with ARI and diarrhoea separately as well as either ARI or diarrhoea within a period of two-week preceding the survey. The ARI and diarrhoea information extracted from Bangladesh Demographic and Health Survey 2011 are used to develop a random effect logistic model for each of the indicators, and then the prevalence is estimated adapting the World Bank SAE approach for the dichotomous response variable using the 5% data of the Census 2011. The estimated prevalence of each indicator significantly varied by district and sub-district (1.4-11.3% for diarrhoea, 2.2-11.8% for ARI and 4.3-16.5% for ARI/diarrhoea at sub-district level). In a number of districts and sub-district, the proportions are found double the national level. District and sub-district levels spatial distributions of the indicators might help the policy makers to identify the vulnerable disaggregated and remote hotspots. Particularly, aid industries can provide effective interventions at the highly vulnerable spots to overcome the gaps between micro and macro level administrative units.

Using the conservation of mass concept, a novel controlled flow methodology based on a linear programing problem is developed for computing the optimal flow rates for a multi-exit evacuation network. In an emergency situation, the controlled flow design is able to track the values of the walkway density, the number of occupants in nodes and thus assures that the flow from adjacent sources to the source walkways is at their maximum level. Using the DTSP hall room of Universiti Sains Malaysia as a multi-exit network, a simulation of the flow shows that the source walkways are blocked when there is an uncontrolled flow. Hence, very few occupants can make their way into the intermediate walkways and exits. For the controlled flow, the values of occupant density in the source and intermediate walkways gradually approach the critical density, ensuring a maximum flow. The developed methodology is useful for the architects and disaster management authorities who are concerned with the evacuation of building facilities and can be used as a paradigm for future studies.

The speed-density relationship performs as a basis to realize the behavior of a complex system such as vehicular or pedestrian traffic flow. Based on the speed-density relationship, the relationships between other pedestrian characteristics such as speed-flow, flow-density and speed-pedestrian module could be derived. Compared to vehicular flow, very little research has been done to develop a general model to describe pedestrian speed-density relationship. The widely used exponential speed-density models, the Underwood model and the Drake model show that the maximum flow is obtained at jam density, which is illogical because at jam density the movement is very limited and the speed will be at its minimum level. In this study, we propose an improved deterministic speed-density model for pedestrian flow which is an important contribution in the field of pedestrian studies. The proposed model shows that the maximum flow occurs at a density which is less than the jam density and thus, overcoming the limitations of the existing models. The validity of the model is empirically verified by primary and secondary datasets. The results showed that the proposed model can describe the speed-density relationship for all the datasets that were collected for different scenarios such as indoor and outdoor facilities. This model can be used as a general speed-density relationship.

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