Epidemic trend analysis of SARS‐CoV ‐2 in South Asian Association for Regional Cooperation countries using modified susceptible‐infected‐recovered predictive model

Autor: Samrat Kumar Dey, Md. Mahbubur Rahman, Kabid Hassan Shibly, Umme Raihan Siddiqi, Arpita Howlader
Rok vydání: 2022
Předmět:
Zdroj: Engineering Reports. 5
ISSN: 2577-8196
DOI: 10.1002/eng2.12550
Popis: A novel coronavirus causing the severe and fatal respiratory syndrome was identified in China, is now producing outbreaks in more than 200 countries around the world, and became pandemic by the time. In this article, a modified version of the well-known mathematical epidemic model susceptible-infected-recovered (SIR) is used to analyze the epidemic's course of COVID-19 in eight different countries of the South Asian Association for Regional Cooperation (SAARC). To achieve this goal, the parameters of the SIR model are identified by using publicly available data for the corresponding countries: Afghanistan, Bangladesh, Bhutan, India, the Maldives, Nepal, Pakistan, and Sri Lanka. Based on the prediction model, we estimated the epidemic trend of COVID-19 outbreak in SAARC countries for 20, 90, and 180 days, respectively. A short-mid-long term prediction model has been designed to understand the early dynamics of the COVID-19 epidemic in the southeast Asian region. The maximum and minimum basic reproduction numbers (
Databáze: OpenAIRE