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Last Updated: 20 September 2022

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Stochastic SIR model predicts the evolution of COVID-19 epidemics from public health and wastewater data in small and medium-sized municipalities: A one year study.

Monte Carlo Methods replicated the inherent stochasticity of the SARS-CoV-2 virus epidemic by reinterpreting the conventional compartmental models of infectious diseases as chemical reaction networks modelled by the Chemical Master Equation and solved by Monte Carlo Methods in this research.

Source link: https://doi.org/10.1016/j.chaos.2022.112671


Use of a modified SIR-V model to quantify the effect of vaccination strategies on hospital demand during the Covid-19 pandemic.

To estimate hospital shortage in Italy due to COVID-19 pandemics, a novel compartmental scheme that includes vaccination prevention, permanence in hospital wards, and tracing of infected patients has been developed. Even when vaccination programs are available, this report provides evidence for the ability of deterministic SIR-based models to accurately forecast hospital demand dynamics and help inform informed decisions on hospitalization and technologies to respond to large-scale epidemics.

Source link: https://doi.org/10.1109/EMBC48229.2022.9871957


Analysing the Effect of Test-and-Trace Strategy in an SIR Epidemic Model.

If such a traced individual tests positive it is isolated, the contact tracing is resumed. The process of to-be-traced components of the epidemic begins at an early stage of the disease when the To-be-traced components" of the disease behaves like a branching process, while for the epidemic's main stage, where the process of to-be-traced components converges to a deterministic process defined by a system of differential equations, this model is analyzed using large population approximations. The reproduction number for component branching is not linearly declining in the tracing rate, according to a survey, but the individual reproduction number is expected to be monotonic as expected. Further, in the situation where people also self-report for testing, the tracking probability is more reliable than the screening rate.

Source link: https://doi.org/10.1007/s11538-022-01065-9


Modified SIR model for COVID-19 transmission dynamics: Simulation with case study of UK, US and India.

Corona virus disease 2019 is an infectious disease with a worldwide reach, with outbreaks spanning more than 200 countries since its inception in December 2019. Here we have developed Susceptible-Exposed-Infected-Asymptomatic-Recovered, a specialized disease model that is based on the classic Susceptible-Infected-Recovered model, which examines such things as symptomatic transmission and patient quarantine. The Reproductive Rate of the disease has remained stable over a long period and gives improved model results when the model is constructed over a shorter time period, according to our review. With the most accurate representation of real world results, disease spreading factors such as infection rate, recovery rate, and mortality rate can be accurately assessed. This model has a good R-Square rating, which is 0. In different waves of the disease in the United Kingdom, USA, and India, there was a 95% - 5 % MAPE.

Source link: https://doi.org/10.1016/j.rinp.2022.105855


Minimizing the epidemic final size while containing the infected peak prevalence in SIR systems.

We investigate how to minimize the E F S while keeping the I P intact at any time in this research, which is based on a new analysis of SIR-type models' dynamical behavior under control steps. A new approach is suggested to tailor NPIs by separating transient from stationary control goals: the COVID-19 pandemic's results illustrate the strategy's potential benefits.

Source link: https://doi.org/10.1016/j.automatica.2022.110496

* Please keep in mind that all text is summarized by machine, we do not bear any responsibility, and you should always check original source before taking any actions

* Please keep in mind that all text is summarized by machine, we do not bear any responsibility, and you should always check original source before taking any actions