ReviewNonlinear dynamics2020
A fractional-order SEIHDR model for COVID-19 with inter-city networked coupling effects.
Review in Nonlinear dynamics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.
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Who cites it
26 citing papers in PubMed, 1 synthesis or guideline pooled it, 74 citations in OpenAlex.
- Reliability of Early Estimates of the Basic Reproduction Number of COVID-19: A Systematic Review and Meta-Analysis.International journal of environmental research and public health · 2022Pooled it
- Fractional study of the Covid-19 model with different types of transmissions.Kuwait journal of science · 2023Article
- Uncertainty quantification in mechanistic epidemic models via cross-entropy approximate Bayesian computation.Nonlinear dynamics · 2023Article
- The effect mitigation measures for COVID-19 by a fractional-order SEIHRDP model with individuals migration.ISA transactions · 2023Article
- A case study of 2019-nCoV in Russia using integer and fractional order derivatives.Mathematical methods in the applied sciences · 2022Article
- Article
- Qualitative and quantitative analysis of the COVID-19 pandemic by a two-side fractional-order compartmental model.ISA transactions · 2022Article
- How efficient is contact tracing in mitigating the spread of COVID-19? a mathematical modeling approach.Applied mathematical modelling · 2022Article
- A fractional SVIR-B epidemic model for Cholera with imperfect vaccination and saturated treatment.European physical journal plus · 2022Article
- Chaotic dynamics in a novel COVID-19 pandemic model described by commensurate and incommensurate fractional-order derivatives.Nonlinear dynamics · 2022Review
- Article
- Time-variant reliability-based prediction of COVID-19 spread using extended SEIVR model and Monte Carlo sampling.Results in physics · 2021Article
- Fractional model for the spread of COVID-19 subject to government intervention and public perception.Applied mathematical modelling · 2021Article
- A fractional-order compartmental model for the spread of the COVID-19 pandemic.Communications in nonlinear science & numerical simulation · 2021Article
- Modeling COVID-19 spreading dynamics and unemployment rate evolution in rural and urban counties of Alabama and New York using fractional derivative models.Results in physics · 2021Article
- A fractional order SITR mathematical model for forecasting of transmission of COVID-19 of India with lockdown effect.Results in physics · 2021Article
- Assessing the role of quarantine and isolation as control strategies for COVID-19 outbreak: A case study.Chaos, solitons, and fractals · 2021Article
- A fractional-order SIRD model with time-dependent memory indexes for encompassing the multi-fractional characteristics of the COVID-19.Chaos, solitons, and fractals · 2021Article
- Dynamics of fractional order COVID-19 model with a case study of Saudi Arabia.Results in physics · 2021Article
- A Mathematical Model of COVID-19 Pandemic: A Case Study of Bangkok, Thailand.Computational and mathematical methods in medicine · 2021Article
Corrections and comments
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Authors and funding
7 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In the end of 2019, a new type of coronavirus first appeared in Wuhan. Through the real-data of COVID-19 from January 23 to March 18, 2020, this paper proposes a fractional SEIHDR model based on the coupling effect of inter-city networks. At the same time, the proposed model considers the mortality rates (exposure, infection and hospitalization) and the infectivity of individuals during the incubation period. By applying the least squares method and prediction-correction method, the proposed system is fitted and predicted based on the real-data from January 23 to March
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.