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E-learning is relatively an emerging learning system that has been placed over the conventional campus based learning worldwide due to the COVID-19 pandemic. The aim of this study is to assess e-learning readiness among the university students of a developing country like Bangladesh and to identify the independent predictors of e-learning readiness. Based on the extensive literature review the study plan has been designed. The estimated sample size of the study is 1067. Data will be collected online via “Google Form” with the principles of snowball sampling through available social media platforms in Bangladesh. The E-learning readiness questionnaire will be used for E-learning readiness, and the PELSS for perceived stress will be used to measure the outcome. Demographic factors will be the age, gender, divisional residence, preference of students and their parents, devices used, and having any eye problems Descriptive statistics will be performed. A bivariate and multivariable linear regression model will be applied. A logistic regression model will be used. The data will be analyzed via statistical software Statistical Package for the Social Sciences (SPSS, version 22.0) and STATA-16. During the prolong stages of COVID-19 pandemic e-learning implication strategies are needed to be assessed systematically with the level of readiness and its’ impact among students for the continuation of a sound learning system. To our best knowledge, this is the very first study attempting to measure the level of stress induced upon the university students by the distance learning system. This study will provide an insight to the current situation of the online learning in Bangladesh and will lead to further researches, helping in future policy making for effective implementation of distance learning.

The COVID-19 pandemic has compelled all educational institutions from the conventional campus-based education system to e-learning worldwide. However, adapting to this new platform, e-learning readiness may cause perceived stress among students. This study aimed to examine the association between e-learning readiness and perceived e-learning stress and the relationship between sociodemographic and e-learning related factors. A cross-sectional study was employed, where 1145 e-learning enrolled university students were surveyed. The result indicated that nearly 91% of students reported moderate (76.07%) to the higher level (14.85%) of perceived e-learning stress, whereas more than half of them (58.17%) were at the sub-optimum level of readiness. Furthermore, it was found that students with the sub-optimum level of readiness compared to optimum had a significantly higher chance of reporting moderate and high level of perceived e-learning stress. Besides, parents’ highest education, residence, students’ preference in (e-learning or learning format), and having any eye problems were associated with perceived e-learning stress. A sudden introduction of e-learning during the COVID-19 catastrophe has brought about challenges, including the students' readiness, that might exacerbate the perceived stress level in different ways. This study reported that most of the students were at sub-optimal levels of readiness and suffered from moderate to high levels of perceived e-learning stress. The findings should integrate into the education monitoring system to enhance students' coping strategies, incite readiness, straighten, and nourish existing policies.Key messagesThe moderate and higher level of e-learning stress was 76% and 15%, respectively.Here, 58% of students were at the sub-optimum level of e-learning readiness.Students’ sub-optimum level of e-learning readiness was significantly associated with the perceived moderate and high level of e-learning stress. The moderate and higher level of e-learning stress was 76% and 15%, respectively. Here, 58% of students were at the sub-optimum level of e-learning readiness. Students’ sub-optimum level of e-learning readiness was significantly associated with the perceived moderate and high level of e-learning stress.

The illness cost borne by households, known as out-of-pocket expenditure, was 74% of the total health expenditure in Bangladesh in 2017. Calculating economic burden of diarrhea of low-income urban community is important to identify potential cost savings strategies and prioritize policy decision to improve the quality of life of this population. This study aimed to estimate cost of illness and monthly percent expenditure borne by households due diarrhea in a low-income urban settlement of Dhaka, Bangladesh. We conducted this study in East Arichpur area of Tongi township in Dhaka, Bangladesh from September 17, 2015 to July 26, 2016. We used the World Health Organization (WHO) definition of three or more loose stool in 24 hours to enroll patients and enrolled 106 severe patients and 158 non-severe patients from Tongi General Hospital, local pharmacy and study community. The team enrolled patients between the first to third day of the illness (≤ 72 hours) and continued daily follow-up by phone until recovery. We considered direct and indirect costs to calculate cost-per-episode. We applied the published incidence rate to estimate the annual cost of diarrhea. The estimated average cost of illness for patient with severe diarrhea was US$ 27.39 [95% CI: 24.55, 30.23] (2,147 BDT), 17% of the average monthly income of the households. The average cost of illness for patient with non-severe diarrhea was US$ 6.36 [95% CI: 5.19, 7.55] (499 BDT), 4% of the average monthly income of households. A single diarrheal episode substantially affects financial condition of low-income urban community residents: a severe episode can cost almost equivalent to 4.35 days (17%) and a non-severe episode can cost almost equivalent to 1 day (4%) of household’s income. Preventing diarrhea preserves health and supports financial livelihoods.