People’s Concerns With the Prediction of COVID-19 in Bangladesh: Application of Autoregressive Integrated Moving Average Model

  • Hossain M
  • Saleheen A
  • Haq I
  • et al.
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Abstract

Introduction: The coronavirus disease 2019 (COVID-19) has become a public health concern, and behavioral adjustments will minimize its spread worldwide by 80%. The main purpose of this research was to examine the factors associated with concerns about COVID-19 and the future direction of the COVID-19 scenario of Bangladesh. Methods: The binary logistic regression model was performed to assess the impact of COVID-19 concern in Bangladesh. Based on data obtained through online surveys in November 2020 and to predict the next 40 days daily confirmed and deaths of COVID-19 in Bangladesh by applying the Autoregressive Integrated Moving Average (ARIMA) model. Results: The study enrolled 400 respondents, with 253 (63.2%) were male, and 147 (36.8%) were female. The mean age of respondents was 25.13 ± 5.74 years old. Almost 70% of them were found to be concerned about the COVID-19 pandemic. The result showed that respondents’ education level, knowledge regarding COVID-19 transmits, households with aged people, seasonal flu and HD/respiratory problems, and materials used while sneezing/coughing significantly influenced COVID-19 concerns. The analysis predicted that confirmed cases would gradually decrease for the ARIMA model while death cases will be constant for the next 40 days in Bangladesh. Conclusion: The current study suggested that knowledge about COVID-19 spread and education played a vital role in the decline of COVID-19 concerned. A particular program should focus on creating an awareness of the disadvantages of concerns about the COVID-19 pandemic by augmenting knowledge about COVID-19 spread, enhancing Education in Bangladesh.

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APA

Hossain, Md. I., Saleheen, A. A. S., Haq, I., Zinnia, M. A., Hasan, Md. R., Kabir, S., … Talukder, A. (2021). People’s Concerns With the Prediction of COVID-19 in Bangladesh: Application of Autoregressive Integrated Moving Average Model. International Journal of Travel Medicine and Global Health, 9(2), 84–93. https://doi.org/10.34172/ijtmgh.2021.14

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