ArticleEuropean physical journal plus2020
Describing the COVID-19 outbreak during the lockdown: fitting modified SIR models to data.
Article in European physical journal plus, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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Who cites it
8 citing papers in PubMed.
- Using simulation modelling and systems science to help contain COVID-19: A systematic review.Systems research and behavioral science · 2022Article
- A Hypothesis-Free Bridging of Disease Dynamics and Non-pharmaceutical Policies.Bulletin of mathematical biology · 2022Article
- A novel hybrid SEIQR model incorporating the effect of quarantine and lockdown regulations for COVID-19.Scientific reports · 2021Article
- Article
- Impact of control interventions on COVID-19 population dynamics in Malaysia: a mathematical study.European physical journal plus · 2021Article
- Effect of easing lockdown and restriction measures on COVID-19 epidemic projection: A case study of Saudi Arabia.PloS one · 2021Article
- Modeling of COVID-19 with limited public health resources: a comparative study of three most affected countries.European physical journal plus · 2021Article
- Role of plasmonics in detection of deadliest viruses: a review.European physical journal plus · 2021Review
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In this paper, we analyse the COVID-19 outbreak data with simple modifications of the SIR compartmental model, in order to understand the time evolution of the cases in Italy and Germany, during the first half of 2020. Even if the complexity of the pandemic cannot be easily described, we show that our models are suitable for understanding the data during the application of the social distancing and the lockdown. We compare and contrast different modifications of the SIR model showing the strengths and the weaknesses of each approach. Finally, we discuss the reliability of the model predictions for estimating the near- and far-future evolution of the outbreak.
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Registered trials
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