Forecasting the spread of COVID-19 pandemic in Bangladesh using ARIMA model
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Abstract
COVID-19 is one of the most serious global public health threats creating an alarming situation. Therefore, there is an urgent need for investigating and predicting COVID-19 incidence to control its spread more effectively. This study aim to forecast the expected number of daily total confirmed cases, total confirmed new cases, total deaths and total new deaths of COVID-19 in Bangladesh for next 3 weeks. The number of daily total confirmed cases, total confirmed new cases, total deaths and total new deaths of COVID-19 from 8 March2020 to 4 February, 2021 was collected to fit an Autoregressive Integrated Moving Average (ARIMA) model to forecast the spread of COVID-19 in Bangladesh from 5th February 2021 to 25th February 2021. All statistical analyses were conducted using R-3.6.3 software with a significant level of p< 0.05. The ARIMA (1,2,1), ARIMA (1,1,1), ARIMA (1,2,2) and ARIMA (1,1,2) model was adopted for forecasting the number of daily total confirmed cases, total confirmed new cases, total deaths and new deaths of COVID-19, respectively. The results showed that an upward trend for the total confirmed cases and total deaths, while total confirmed new cases and total new death, will become stable in the next 3 weeks if prevention measures are strictly followed to limit the spread of COVID-19. The forecasting results of COVID-19 will not be dreadful for upcoming days in Bangladesh. However, the government and health authorities should take new approaches and keep strong monitoring of the existing strategies to control the further spread of this pandemic. Asian J. Med. Biol. Res. March 2021, 7(1): 21-32
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SciScore for 10.1101/2020.10.22.20217414: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Experimental Models: Organisms/Strains Sentences Resources An ARMA(p,q) model is given by Yt = α1Yt −1 + α2Yt −2 + … + α pYt − p + ut + β1ut −1 + β2ut −2 + … + β put −q 24. −2 + … + α pYt − p + ut + β1ut −1 + β2ut −2 + … + βsuggested: NoneResults from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial …
SciScore for 10.1101/2020.10.22.20217414: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Experimental Models: Organisms/Strains Sentences Resources An ARMA(p,q) model is given by Yt = α1Yt −1 + α2Yt −2 + … + α pYt − p + ut + β1ut −1 + β2ut −2 + … + β put −q 24. −2 + … + α pYt − p + ut + β1ut −1 + β2ut −2 + … + βsuggested: NoneResults from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a protocol registration statement.
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