Estimation and prediction of doubling time for COVID-19 epidemic in Bangladesh: a study of first 14 month’s daily confirmed new cases and deaths

Haque, Mohammad Farhadul; Rahman, Mohammad Meshbahur; Alif, Sheikh M; Akter, Emily; Barua, Shomrita; Paul, Gowranga Kumar; Haider, Najmul

Abstract

Background: The doubling time is a reliable indicator to estimate the rate at which the pandemic is spreading. We evaluated and predicted the doubling time for the daily COVID-19 cases and deaths in Bangladesh.

Methods: Publicly available daily data on COVID-19 new cases from 8 March, 2020 to 14 February, 2021 and the daily deaths data from 18 March, 2020 to 14 February, 2021 were used to predict doubling time based on records from seven days prior. Then, short-term predictions for the next 14 days (1 to 14 February, 2021) were performed to validate the accuracy of our prediction. Finally, using the doubling time data up to 14 February, 2021, a two months (15 February- 15 April, 2021) prediction was made for both daily new COVID-19 cases and deaths.

Results: The median doubling time for daily new COVID-19 cases and deaths were 90.51 and 86.02 days respectively in the entire period. The doubling period for cases was lowest in the second to third week of March, 2020 [ranged 2.33-8.43 days] and longest in the second week of March, 2021 [ranged 834-2187 days]. Our prediction suggests that the doubling time for daily confirmed new COVID-19 case will be 1310.33 days [95% CI: 854.33 - 1766.32] and deaths will be 683.04 days [556.05 - 810.03] on 15 April, 2021 in Bangladesh.

Conclusion: Our prediction is based on current testing strategies. Any changes in daily number of tests or sudden changes of the dynamics of COVID-19 transmission would affect these predictions.

Citation

Haque, M. F., Rahman, M. M., Alif, S. M., Akter, E., Barua, S., Paul, G. K., & Haider, N. (2021). Estimation and prediction of doubling time for COVID-19 epidemic in Bangladesh: a study of first 14 month’s daily confirmed new cases and deaths. Global Biosecurity, 3(1), 11. https://doi.org/10.31646/gbio.91

• Journal Article Type: Article
• Acceptance Date: Apr 1, 2021
• Online Publication Date: Apr 26, 2021
• Publication Date: Apr 26, 2021
• Deposit Date: May 17, 2021
• Journal: Global Biosecurity
• Print ISSN: 2652-0036
• Electronic ISSN: 2652-0036
• Publisher: University of New South Wales
• Peer Reviewed: Peer Reviewed
• Volume: 3
• Issue: 1
• Pages: 11
• DOI: https://doi.org/10.31646/gbio.91
• Public URL: https://rvc-repository.worktribe.com/output/1548925
• Publisher URL: https://jglobalbiosecurity.com/articles/10.31646/gbio.91/