ArticlePhysica D. Nonlinear phenomena2021
Explicit formulae for the peak time of an epidemic from the SIR model.
Article in Physica D. Nonlinear phenomena, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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19 citing papers in PubMed, 75 citations in OpenAlex.
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- Computation of random time-shift distributions for stochastic population models.Journal of mathematical biology · 2024Article
- Evaluations of COVID-19 epidemic models with multiple susceptible compartments using exponential and non-exponential distribution for disease stages.Infectious Disease Modelling · 2022Article
- Machine learning models for prediction of HF and CKD development in early-stage type 2 diabetes patients.Scientific reports · 2022Article
- Limits of epidemic prediction using SIR models.Journal of mathematical biology · 2022Article
- An extended epidemic model with vaccination: Weak-immune SIRVI.Physica A · 2022Article
- There exists the "smartest" movement rate to control the epidemic rather than "city lockdown".Applied mathematical modelling · 2022Article
- A network SIRX model for the spreading of COVID-19.Physica A · 2022Article
- Long-term predictions of current confirmed and dead cases of COVID-19 in China by the non-autonomous delayed epidemic models.Cognitive neurodynamics · 2022Article
- An agent-based model of the dual causality between individual and collective behaviors in an epidemic.Computers in biology and medicine · 2022Article
- Gompertz model in COVID-19 spreading simulation.Chaos, solitons, and fractals · 2022Article
- The changing economic relationship between some of the major COVID-19 impacted countries with prominent wealth: a comparative study from the view point of stock markets.The European physical journal. Special topics · 2022Article
- Analysis of COVID-19 in India using a vaccine epidemic model incorporating vaccine effectiveness and herd immunity.European physical journal plus · 2022Article
- Analysis of the second wave of COVID-19 in India based on SEIR model.The European physical journal. Special topics · 2022Article
- Explicit formulae for the peak time of an epidemic from the SIR model. Which approximant to use?Physica D. Nonlinear phenomena · 2021Article
- Nonlinear science against the COVID-19 pandemic.Physica D. Nonlinear phenomena · 2021Article
- The second and third waves in India: when will the pandemic be culminated?European physical journal plus · 2021Article
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Authors and funding
1 author at 1 institution in 2 countries.
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No grant is acknowledged in the PubMed record.
Abstract
Reducing the peak time of an epidemic disease in order for slowing down the eventual dynamics and getting prepared for the unavoidable epidemic wave is utmost significant to fight against the risks of a contagious epidemic disease. To serve to this purpose, the well-documented infection model of SIR is examined in the current research to propose an analytical approach for providing an explicit formula associated with a straightforward computation of peak time of outbreak. Initially, the time scale from the relevant autonomous SIR epidemic model is formulated analytically via an integral based on the fractions of susceptible and infected compartments. Afterwards, through a series expansion of the logarithmic term of the resultant integrand, the peak time is shown to rely upon the fraction of susceptible, the infectious ratio as well as the initial fractions of ill and susceptible individuals. The approximate expression is shown to rigorously capable of capturing the time threshold of illness for an epidemic from the semi-time SIR epidemiology. Otherwise, it is also successful to predict the peak time from a past history of a disease when all-time epidemic model is adopted. Accuracy of the derived expressions are initially confirmed by direct comparisons with recently reported approximate formulas in the literature. Several other epidemic disease samples including the COVID-19 often studied in the recent literature are eventually attacked with favourable performance of the presented formulae for assessing the peak time occurrence of an epidemic. A quick evaluation of the peak time of a disease certainly enables the governments to take early effective epidemic precautions.
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