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Md. Selim Mondol

Bio: Md. Selim Mondol is an academic researcher. The author has contributed to research in topics: Population. The author has an hindex of 1, co-authored 1 publications receiving 5 citations.
Topics: Population

Papers
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Journal ArticleDOI
22 Dec 2020
TL;DR: In this paper, a social media-based cross-sectional survey was conducted to explore these variables among Bangladeshi adults to determine KAP among rural and urban residents as well as predictors of preventive practices associated with COVID-19.
Abstract: As other nations around the world, Bangladesh is facing enormous challenges with the novel coronavirus (COVID-19) epidemic. To design a prevention and control strategy for this new infectious disease, it is essential to first understand people’s knowledge, attitudes, and practices (KAP) regarding COVID-19. This study sought to determine KAP among rural and urban residents as well as predictors of preventive practices associated with COVID-19 in Bangladesh. A social media-based (Facebook) cross-sectional survey was conducted to explore these variables among Bangladeshi adults. Of 1520 respondents who completed the questionnaire, low level of good or sufficient knowledge of COVID-19 (70.8%) and practices associated with COVID-19 (73.8%) were found. Despite the low level of knowledge and practices, respondents’ attitude (78.9%) towards COVID-19 was relatively high. Results suggest that compared to urban, rural residents are at a particularly high risk of COVID-19 because they were found to have significantly lower knowledge (p = 0.001) and practice levels (p = 0.002) than were urban residents. Multivariable logistic regression analysis identified gender, education, knowledge of COVID-19 transmission, signs and symptoms, and sources of information as factors significantly associated with preventive practices against COVID-19. Further attention and effort should be directed toward increasing both knowledge and practices targeting the general population in Bangladesh, particularly the rural and less educated residents. Findings from this study provide baseline data that can be used to promote integrated awareness of and effective health education programs about COVID-19 prevention and control strategies in Bangladesh, and similar COVID-19 endemic countries.

21 citations


Cited by
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Journal ArticleDOI
27 Apr 2021-PLOS ONE
TL;DR: In this paper, a cross-sectional analysis from a household survey of 3646 adults aged 18 years or older was conducted in 8 districts of Bangladesh, from December 12, 2020, to January 7, 2021.
Abstract: BACKGROUND: Although the approved COVID-19 vaccine has been shown to be safe and effective, mass vaccination in Bangladeshi people remains a challenge. As a vaccination effort, the study provided an empirical evidence on willingness to vaccinate by sociodemographic, clinical and regional differences in Bangladeshi adults. METHODS: This cross-sectional analysis from a household survey of 3646 adults aged 18 years or older was conducted in 8 districts of Bangladesh, from December 12, 2020, to January 7, 2021. Multinomial regression examined the impact of socio-demographic, clinical and healthcare-releated factors on hesitancy and reluctance of vaccination for COVID-19. RESULTS: Of the 3646 respondents (2212 men [60.7%]; mean [sd] age, 37.4 [13.9] years), 74.6% reported their willingness to vaccinate against COVID-19 when a safe and effective vaccine is available without a fee, while 8.5% were reluctant to vaccinate. With a minimum fee, 46.5% of the respondents showed intent to vaccinate. Among the respondents, 16.8% reported adequate adherence to health safety regulations, and 35.5% reported high confidence in the country's healthcare system. The COVID-19 vaccine refusal was significantly high in elderly, rural, semi-urban, and slum communities, farmers, day-laborers, homemakers, low-educated group, and those who had low confidence in the country's healthcare system. Also, the prevalence of vaccine hesitancy was high in the elderly population, low-educated group, day-laborers, people with chronic diseases, and people with low confidence in the country's healthcare system. CONCLUSION: A high prevalence of vaccine refusal and hesitancy was observed in rural people and slum dwellers in Bangladesh. The rural community and slum dwellers had a low literacy level, low adherence to health safety regulations and low confidence in healthcare system. The ongoing app-based registration for vaccination increased hesitancy and reluctancy in low-educated group. For rural, semi-urban, and slum people, outreach centers for vaccination can be established to ensure the vaccine's nearby availability and limit associated travel costs. In rural areas, community health workers, valued community-leaders, and non-governmental organizations can be utilized to motivate and educate people for vaccination against COVID-19. Further, emphasis should be given to the elderly and diseased people with tailored health messages and assurance from healthcare professionals. The media may play a responsible role with the vaccine education program and eliminate the social stigma about the vaccination. Finally, vaccination should be continued without a fee and thus Bangladesh's COVID vaccination program can become a model for other low and middle-income countries.

129 citations

Journal ArticleDOI
TL;DR: The findings reveal the existence of a nonlinear trend and weekly seasonality in the dataset and suggest the ARIMA model performed better than the XGBoost model in predicting COVID-19 confirmed cases and deaths in Bangladesh.
Abstract: Accurate predictive time series modelling is important in public health planning and response during the emergence of a novel pandemic. Therefore, the aims of the study are three-fold: (a) to model the overall trend of COVID-19 confirmed cases and deaths in Bangladesh; (b) to generate a short-term forecast of 8 weeks of COVID-19 cases and deaths; (c) to compare the predictive accuracy of the Autoregressive Integrated Moving Average (ARIMA) and eXtreme Gradient Boosting (XGBoost) for precise modelling of non-linear features and seasonal trends of the time series. The data were collected from the onset of the epidemic in Bangladesh from the Directorate General of Health Service (DGHS) and Institute of Epidemiology, Disease Control and Research (IEDCR). The daily confirmed cases and deaths of COVID-19 of 633 days in Bangladesh were divided into several training and test sets. The ARIMA and XGBoost models were established using those training data, and the test sets were used to evaluate each model’s ability to forecast and finally averaged all the predictive performances to choose the best model. The predictive accuracy of the models was assessed using the mean absolute error (MAE), mean percentage error (MPE), root mean square error (RMSE) and mean absolute percentage error (MAPE). The findings reveal the existence of a nonlinear trend and weekly seasonality in the dataset. The average error measures of the ARIMA model for both COVID-19 confirmed cases and deaths were lower than XGBoost model. Hence, in our study, the ARIMA model performed better than the XGBoost model in predicting COVID-19 confirmed cases and deaths in Bangladesh. The suggested prediction model might play a critical role in estimating the spread of a novel pandemic in Bangladesh and similar countries.

10 citations

Journal ArticleDOI
TL;DR: A substantial percentage of Bangladeshi adults have difficulty practising COVID-19 protective behaviours and have poor comprehension of risk communications, particularly in rural areas and among those with low education, which can aid policymakers in developing tailored CO VID-19 risk communications and mitigation strategies to help prevent future waves of the pandemic.
Abstract: Bangladesh recently experienced a COVID-19 second wave, resulting in the highest number of new cases and deaths in a single day. This study aims to identify the challenges for COVID-19 preventive practices and risk communications and associated factors among Bangladeshi adults. A cross-sectional survey was conducted between December 2020 and January 2021 involving 1382 Bangladeshi adults (aged ≥ 18-years) in randomly selected urban and rural areas from all eight divisions in Bangladesh. Descriptive data analysis was conducted to highlight the challenges for preventive practices and risk communications for COVID-19. Multiple logistic regression analysis was used to determine the sociodemographic groups vulnerable to these challenges. Lack of availability of protective equipment (44.4%), crowded living situations/workspaces (36.8%), inadequate information on the proper use of protective measures (21.9%), inadequate handwashing and sanitation facilities (17.6%), and negative influences on family/friends (17.4%) were identified as barriers to COVID-19 preventive practices. It was also found that males (OR = 1.3, 95% CI = 1.01, 1.7), rural residents (OR = 1.5, 95% CI = 1.2, 2), respondents with a low level of education: no schooling vs. ≥higher secondary (OR = 3.5, 95% CI = 2.3, 5.2), primary vs. ≥higher secondary (OR = 2.5, 95% CI = 1.7, 3.8), respondents engaged in agricultural (OR = 1.7, 95% CI = 1.2, 2.4), laboring (OR = 3.2, 95% CI = 2, 5), and domestic works (OR = 1.6, 95% CI = 1.07, 2.5), and people with disabilities (OR = 1.7, 95% CI = 1.1, 2.6) were all likely to have difficulty in practicing effective COVID-19 protective behaviors. Respondents' education and occupation were significant predictors of inadequate understanding of COVID-19 risk communications and was identified as a problem among 17.4% of the respondents. A substantial percentage of Bangladeshi adults have difficulty practising COVID-19 protective behaviours and have poor comprehension of risk communications, particularly in rural areas and among those with low education. This research can aid policymakers in developing tailored COVID-19 risk communications and mitigation strategies to help prevent future waves of the pandemic.

8 citations

Journal ArticleDOI
10 May 2022-PLOS ONE
TL;DR: Only sex and considering that preventive measures were adequately carried out were associated with good prevention practices in both areas, suggesting prevention measures should be promoted taking into account cultural principles and considering geographical location in the face of present and future outbreaks or pandemics.
Abstract: Objective To determine the factors associated with prevention practices against COVID-19 in the Peruvian population according to rural vs. urban locations. Methods Analytical cross-sectional study, secondary analysis based on a previously collected database. A sample of individuals over 18 years of age, residing in Peru and with no history of COVID-19was evaluated. Factors associated with prevention practices were evaluated using Poisson regressions with variance adjustment by region cluster and stratified by rurality. Results Of 3231 participants included, 2741 (84.8%) were from urban areas and 490 (15.2%) from rural areas. The frequency of good prevention practices against COVID-19 was 27.8% in our total sample. In urban areas the frequency of good prevention practices was 28.8% and in rural areas it was 22.5%. Factors associated with prevention practices against COVID-19 in both urban and rural areas were male sex (urban: aPR 0.64, 95%CI 0.55–0.75; rural: aPR 0.66, 95%CI 0.54–0.80) and self-considering adequately carrying out prevention practices (urban: aPR 2.48, 95%CI 2.13–2.89; rural: aPR 2.70, 95%CI 2.27–3.19). Conclusion The frequency of good prevention practices against COVID-19 was less than 30% in both urban and rural areas. There are differences in the factors associated with good preventive practice against COVID-19. Only sex and considering that preventive measures were adequately carried out were associated with good prevention practices in both areas. In view of this, prevention measures should be promoted taking into account cultural principles and considering geographical location in the face of present and future outbreaks or pandemics.

4 citations