Haque, MF, Rahman, MM, Alif, SM, Akter, E, Barua, S, Paul, GK and 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). ISSN 2652-0036

[thumbnail of 3. 3. 2021. 1 Doubling time_Covid-19_Bangladesh_Global BS_2021.pdf]
3. 3. 2021. 1 Doubling time_Covid-19_Bangladesh_Global BS_2021.pdf - Published Version

Download (601kB) | Preview


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.

Item Type: Article
Additional Information: Copyright © 2021 The Author(s). This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See http://creativecommons.org/licenses/by/4.0/ .
Subjects: R Medicine > R Medicine (General)
R Medicine > R Medicine (General) > R735 Medical education. Medical schools. Research
Depositing User: Symplectic
Date Deposited: 04 Nov 2022 10:59
Last Modified: 04 Nov 2022 10:59
URI: https://eprints.keele.ac.uk/id/eprint/11624

Actions (login required)

View Item
View Item