ArticleRisk analysis : an official publication of the Society for Risk Analysis2023
An SEIR Model with Time-Varying Coefficients for Analyzing the SARS-CoV-2 Epidemic.
Article in Risk analysis : an official publication of the Society for Risk Analysis, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- A history-dependent approach for accurate initial condition estimation in epidemic models.PLoS computational biology · 2025Article
- Systematic Comparison of Different Compartmental Models for Predicting COVID-19 Progression.Epidemiologia (Basel, Switzerland) · 2025Article
- Article
- Integrating socio-psychological factors in the SEIR model optimized by a genetic algorithm for COVID-19 trend analysis.Scientific reports · 2024Article
- Prevention and control of infectious disease transmission in subways: an improved susceptible-exposed-infected-recovered model.Frontiers in public health · 2024Article
- The disutility of compartmental model forecasts during the COVID-19 pandemic.Frontiers in epidemiology · 2024Article
- Modeling the time-dependent transmission rate using gaussian pulses for analyzing the COVID-19 outbreaks in the world.Scientific reports · 2023Article
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Authors and funding
2 authors.
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Abstract
In this study, we propose a time-dependent susceptible-exposed-infected-recovered (SEIR) model for the analysis of the SARS-CoV-2 epidemic outbreak in three different countries, the United States, Italy, and Iceland using public data inherent the numbers of the epidemic wave. Since several types and grades of actions were adopted by the governments, including travel restrictions, social distancing, or limitation of movement, we want to investigate how these measures can affect the epidemic curve of the infectious population. The parameters of interest for the SEIR model were estimated employing a composite likelihood approach. Moreover, standard errors have been corrected for temporal dependence. The adoption of restrictive measures results in flatten epidemic curves, and the future evolution indicated a decrease in the number of cases.
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