An Improved SEIR Dynamics Model For Actual Infection Scale Estimation of COVID-19

Journal of Circuits Systems and Computers, Journal Year: 2024, Volume and Issue: unknown

Published: July 12, 2024

It is crucial to capture the actual infection scale of communicable diseases. However, official case numbers cannot equal in society, because a large number asymptomatic individuals are not recognized. To deal with this challenge, paper takes COVID-19 as object, and develops an improved SEIR dynamics model estimate its scale. Generalized circumstances work, we improve classical by considering three implicit factors: self-recovered individuals, recovered deceased individuals. The process inside expressed using mathematical formulas, parameter estimation scheme given accordingly. evaluate effect proposal, employ pandemic data from 10 representative countries build experimental scenario. results obtained through fitting demonstrate that estimated approximately 10–30 times higher than reported average “newly confirmed cases”. Furthermore, our findings reveal noteworthy negative correlation between transmission coefficient vaccination rate, confirming beneficial role mitigating spreading.

Language: Английский

Significant Driving Factors in the Evolution of the COVID-19 Epidemic

Sustainability, Journal Year: 2024, Volume and Issue: 17(1), P. 110 - 110

Published: Dec. 27, 2024

The progression of the COVID-19 pandemic has demonstrated significant oscillatory characteristics, underscoring importance investigating impact driving factors on its evolution. This study included an in-depth analysis influence various pandemic’s fluctuations, identifying key elements, to enhance comprehension transmission mechanisms and improve scientific precision in formulating mitigation strategies. experimental outcomes indicate that Geographically Temporally Neural Network Weighted Regression (GTNNWR) model achieved commendable accuracy with minimal error forecasting number infected individuals. Leveraging results from GTNNWR model, research meticulously examines temporal spatial correlations between pandemic, delineated spatiotemporal distribution patterns each factor’s influence, quantified their significance. reveals substantial vaccines, masks, social distancing measures across different regions periods, effects affected individuals being 2 10 times more pronounced than other factors. These findings contribute a deeper understanding dynamics offering critical decision-making support for control prevention efforts.

Language: Английский