Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/99621
Title: | Forecast of the COVID-19 trend in India : a simple modelling approach | Authors: | Song, H Fan, G Zhao, S Li, H Huang, Q He, D |
Issue Date: | 2021 | Source: | Mathematical biosciences and engineering, 2021, v. 18, no. 6, p. 9775-9786 | Abstract: | By February 2021, the overall impact of the COVID-19 pandemic in India had been relatively mild in terms of total reported cases and deaths. Surprisingly, the second wave in early April becomes devastating and attracts worldwide attention. Multiple factors (e.g., Delta variants with increased transmissibility) could have driven the rapid growth of the epidemic in India and led to a large number of deaths within a short period. We aim to reconstruct the transmission rate, estimate the infection fatality rate and forecast the epidemic size. We download the reported COVID-19 mortality data in India and formulate a simple mathematical model with a flexible transmission rate. We use iterated filtering to fit our model to deaths data. We forecast the infection attack rate in a month ahead. Our model simulation matched the reported deaths well and is reasonably close to the results of the serological study. We forecast that the infection attack rate (IAR) could have reached 43% by July 24, 2021, under the current trend. Our estimated infection fatality rate is about 0.07%. Under the current trend, the IAR will likely reach a level of 43% by July 24, 2021. Our estimated infection fatality rate appears unusually low, which could be due to a low case to infection ratio reported in previous study. Our approach is readily applicable in other countries and with other types of data (e.g., excess deaths). | Keywords: | COVID 19 India Mathematical modelling Iterated filtering Forecast |
Publisher: | American Institute of Mathematical Sciences | Journal: | Mathematical biosciences and engineering | ISSN: | 1547-1063 | EISSN: | 1551-0018 | DOI: | 10.3934/mbe.2021479 | Rights: | © 2021 the Author(s), licensee AIMS Press. T hi s is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0) The following publication Haitao Song, Guihong Fan, Shi Zhao, Huaichen Li, Qihua Huang, Daihai He. Forecast of the COVID-19 trend in India: A simple modelling approach[J]. Mathematical Biosciences and Engineering, 2021, 18(6): 9775-9786 is available at https://doi.org/10.3934/mbe.2021479. |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Song_Forecast_Covid-19_Trend.pdf | 883.48 kB | Adobe PDF | View/Open |
Page views
77
Citations as of Apr 14, 2025
Downloads
55
Citations as of Apr 14, 2025
SCOPUSTM
Citations
19
Citations as of Jun 6, 2025
WEB OF SCIENCETM
Citations
19
Citations as of Jun 5, 2025

Google ScholarTM
Check
Altmetric
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.