ArticleFrontiers in medicine2020
What Can We Estimate From Fatality and Infectious Case Data Using the Susceptible-Infected-Removed (SIR) Model? A Case Study of Covid-19 Pandemic.
Article in Frontiers in medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Predictive Models for Forecasting Public Health Scenarios: Practical Experiences Applied during the First Wave of the COVID-19 Pandemic.International journal of environmental research and public health · 2022Pooled it
- Mathematical models to characterize the early phase of the COVID-19 pandemic in New Mexico, USA.Mathematical biosciences and engineering : MBE · 2025Article
- A tight fit of the SIR dynamic epidemic model to daily cases of COVID-19 reported during the 2021-2022 Omicron surge in New York City: A novel approach.Statistical methods in medical research · 2024Article
- Is It Possible to Predict COVID-19? Stochastic System Dynamic Model of Infection Spread in Kazakhstan.Healthcare (Basel, Switzerland) · 2023Article
- Pandemic effects in the Solow growth model.Bulletin of economic research · 2022Article
- Explicit formulae for the peak time of an epidemic from the SIR model. Which approximant to use?Physica D. Nonlinear phenomena · 2021Article
- COVID-19 outbreak in Wuhan demonstrates the limitations of publicly available case numbers for epidemiological modeling.Epidemics · 2021Article
- Inefficiency of SIR models in forecasting COVID-19 epidemic: a case study of Isfahan.Scientific reports · 2021Article
- Analytical Parameter Estimation of the SIR Epidemic Model. Applications to the COVID-19 Pandemic.Entropy (Basel, Switzerland) · 2020Article
- Intelligent Pandemic Surveillance via Privacy-Preserving Crowdsensing.IEEE intelligent systemsArticle
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5 authors.
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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.
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