Analyzing the spread of the COVID-19 pandemic using the SIR model

8 pages•Published: July 19, 2023

Ngoc Minh Tam Nguyen, Thi My Ngoc Nguyen, Quang Le, Hieu Huy Lam, Thuy Linh Hoang and Trung Nghia Tran

Abstract

It is difficult to control the SARS-CoV-2 virus with many complicated strains with a fast- spreading speed. In Vietnam, the number of new infections gradually shows signs of increasing, potentially posing many future diseases outbreak risks. The SIR model is a model that provides a practical approach to current and future epidemics; the SIR model is a classical, simple model of community infection. The model can add or change relevant components in the community, such as mortality, immigration or birth rates, resilience, and immunity. In this paper, we focus on COVID-19 data from Vietnam and model it is using the SIR epidemiological model to analyze the spread of the disease and forecast the future disease situation. The results include an assessment of the fit or not of the model through the prediction over the periods.

Keyphrases: covid 19, sars cov 2, sir model, vietnam

In: Trung Nghia Tran, Quoc Khai Le, Tich Thien Truong, Thanh Nha Nguyen and Hoang Nhut Huynh (editors). Proceedings of International Symposium on Applied Science 2022, vol 5, pages 91-98.

Links:	https://easychair.org/publications/paper/h3rG
	https://doi.org/10.29007/8sjf

BibTeX entry

@inproceedings{ISAS2022:Analyzing_spread_COVID_19,
  author    = {Ngoc Minh Tam Nguyen and Thi My Ngoc Nguyen and Quang Le and Hieu Huy Lam and Thuy Linh Hoang and Trung Nghia Tran},
  title     = {Analyzing the spread of the COVID-19 pandemic using the SIR model},
  booktitle = {Proceedings of International Symposium on Applied Science 2022},
  editor    = {Trung Nghia Tran and Quoc Khai Le and Tich Thien Truong and Thanh Nha Nguyen and Hoang Nhut Huynh},
  series    = {EPiC Series in Engineering},
  volume    = {5},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2516-2330},
  url       = {/publications/paper/h3rG},
  doi       = {10.29007/8sjf},
  pages     = {91-98},
  year      = {2023}}

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