ArticleApplied mathematical modelling2021
Global analysis of the COVID-19 pandemic using simple epidemiological models.
Article in Applied mathematical modelling, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed.
- Modeling the Potential Public Health Impact of Updated COVID-19 Vaccination Strategies in Singapore: Epidemiological Data Update.Pulmonary therapy · 2026Article
- Potential Public Health Impact of Updated COVID-19 Vaccination Strategies in Malaysia: Epidemiological Data Update.Pulmonary therapy · 2026Article
- Nonlinear mixed models and related approaches in infectious disease modeling: A systematic and critical review.Infectious Disease Modelling · 2025Review
- Endemic characteristics of SARS-CoV-2 infection.Scientific reports · 2023Article
- Improvement of the software for modeling the dynamics of epidemics and developing a user-friendly interface.Infectious Disease Modelling · 2023Article
- Global stability and analysing the sensitivity of parameters of a multiple-susceptible population model of SARS-CoV-2 emphasising vaccination drive.Mathematics and computers in simulation · 2023Article
- An approach for joint optimization of probabilistic group test based on cost and time value: taking nucleic acid detection of COVID-19 as an example.Soft computing · 2023Article
- Modeling the impact of combined use of COVID Alert SA app and vaccination to curb COVID-19 infections in South Africa.PloS one · 2023Article
- Systematic description of COVID-19 pandemic using exact SIR solutions and Gumbel distributions.Nonlinear dynamics · 2023Article
- Wastewater-based epidemiology: a new frontier for tracking environmental persistence and community transmission of COVID-19.Environmental science and pollution research international · 2022Review
- Monte Carlo simulation of COVID-19 pandemic using Planck's probability distribution.Bio Systems · 2022Article
- Airborne transmission of COVID-19 virus in enclosed spaces: An overview of research methods.Indoor air · 2022Review
- Modeling approaches for early warning and monitoring of pandemic situations as well as decision support.Frontiers in public health · 2022Review
- Dynamical analysis of the infection status in diverse communities due to COVID-19 using a modified SIR model.Nonlinear dynamics · 2022Article
- Mathematical modeling and impact analysis of the use of COVID Alert SA app.AIMS public health · 2022Article
- Effectiveness of government policies in response to the first COVID-19 outbreak.PLOS global public health · 2022Article
- A model of COVID-19 pandemic evolution in African countries.Scientific African · 2021Article
- Modeling the effects of the contaminated environments on COVID-19 transmission in India.Results in physics · 2021Article
- A comparison of five epidemiological models for transmission of SARS-CoV-2 in India.BMC infectious diseases · 2021Article
- COVID-19: The Second Wave is not due to Cooling-down in Autumn.Journal of epidemiology and global health · 2021Article
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3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Several analytical models have been developed in this work to describe the evolution of fatalities arising from coronavirus COVID-19 worldwide. The Death or 'D' model is a simplified version of the well-known SIR (susceptible-infected-recovered) compartment model, which allows for the transmission-dynamics equations to be solved analytically by assuming no recovery during the pandemic. By fitting to available data, the D-model provides a precise way to characterize the exponential and normal phases of the pandemic evolution, and it can be extended to describe additional spatial-time effects such as the release of lockdown measures. More accurate calculations using the extended SIR or ESIR model, which includes recovery, and more sophisticated Monte Carlo grid simulations - also developed in this work - predict similar trends and suggest a common pandemic evolution with universal parameters. The evolution of the COVID-19 pandemic in several countries shows the typical behavior in concord with our model trends, characterized by a rapid increase of death cases followed by a slow decline, typically asymmetric with respect to the pandemic peak. The fact that the D and ESIR models predict similar results - without and with recovery, respectively - indicates that COVID-19 is a highly contagious virus, but that most people become asymptomatic (D model) and eventually recover (ESIR model).
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