What Can We Estimate From Fatality and Infectious Case Data Using the Susceptible-Infected (sir) Model? a Case Study of Covid-19 Pandemic
Loading...
Date
2020
Authors
Ahmetolan, Semra
Bilge, Ayşe Hümeyra
Demirci, Ali
Peker-Dobie, Ayşe
Ergönül, Önder
Journal Title
Journal ISSN
Volume Title
Publisher
Frontıers Medıa Sa
Open Access Color
GOLD
Green Open Access
Yes
OpenAIRE Downloads
OpenAIRE Views
Publicly Funded
No
Abstract
The rapidly spreading Covid-19 that affected almost all countries, was first reported at the end of 2019. As a consequence of its highly infectious nature, countries all over the world have imposed extremely strict measures to control its spread. Since the earliest stages of this major pandemic, academics have done a huge amount of research in order to understand the disease, develop medication, vaccines and tests, and model its spread. Among these studies, a great deal of effort has been invested in the estimation of epidemic parameters in the early stage, for the countries affected by Covid-19, hence to predict the course of the epidemic but the variability of the controls over the course of the epidemic complicated the modeling processes. In this article, the determination of the basic reproduction number, the mean duration of the infectious period, the estimation of the timing of the peak of the epidemic wave is discussed using early phase data. Daily case reports and daily fatalities for China, South Korea, France, Germany, Italy, Spain, Iran, Turkey, the United Kingdom and the United States over the period January 22, 2020-April 18, 2020 are evaluated using the Susceptible-Infected-Removed (SIR) model. For each country, the SIR models fitting cumulative infective case data within 5% error are analyzed. It is observed that the basic reproduction number and the mean duration of the infectious period can be estimated only in cases where the spread of the epidemic is over (for China and South Korea in the present case). Nevertheless, it is shown that the timing of the maximum and timings of the inflection points of the proportion of infected individuals can be robustly estimated from the normalized data. The validation of the estimates by comparing the predictions with actual data has shown that the predictions were realized for all countries except USA, as long as lock-down measures were retained.
Description
Keywords
COVID-19, SIR model, Parameter estimation, Mathematical models, Epidemiology, Medicine; General and internal medicine, Mathematical models, Medicine (General), Epidemiology, General and internal medicine, Populations and Evolution (q-bio.PE), COVID-19, Quantitative Biology - Quantitative Methods, R5-920, FOS: Biological sciences, Parameter estimation, Medicine, epidemiology, SIR model, parameter estimation, Quantitative Biology - Populations and Evolution, mathematical models, Quantitative Methods (q-bio.QM), COVID-19; Epidemiology; Mathematical models; Parameter estimation; SIR model
Fields of Science
0301 basic medicine, 03 medical and health sciences, 0302 clinical medicine
Citation
WoS Q
Q1
Scopus Q
Q1

OpenCitations Citation Count
19
Source
Frontiers in Medicine
Volume
7
Issue
Start Page
End Page
PlumX Metrics
Citations
Scopus : 24
PubMed : 9
Captures
Mendeley Readers : 72
SCOPUS™ Citations
24
checked on Feb 10, 2026
Web of Science™ Citations
17
checked on Feb 10, 2026
Page Views
4
checked on Feb 10, 2026
Downloads
150
checked on Feb 10, 2026
Google Scholar™

OpenAlex FWCI
0.17798814
Sustainable Development Goals
3
GOOD HEALTH AND WELL-BEING


