Tracking of COVID-19 Pandemic for Multi-Waves Using a Compartmental Model With Time-Dependent Parameters DOI
Touria Jdid, Idriss Chana, Aziz Bouazi

et al.

Advances in systems analysis, software engineering, and high performance computing book series, Journal Year: 2023, Volume and Issue: unknown, P. 92 - 107

Published: Dec. 29, 2023

Estimating and controlling the COVID-19 pandemic is essential to reduce spread of disease help decision-making efforts in combating public health crises. However, potential presence multiple dynamic changes reported count data or occurrence another wave emerges as a challenge for simulating evolution over long period. In this chapter, account curves, authors propose rate function based on branches logistic function. They assumed compartmental model that recovery transmission rates are time-dependent, they assign each Then, apply daily infection counts Morocco between March 2, 2020 December 31, 2021 using curve fitting through Nelder-Mead optimization method. The simulation outcomes demonstrate model's ability replicate two waves, with goodness fit depending number composing

Language: Английский

Utility of Compartmental Models to Test the Competing Hypotheses of Pathogen Evolution and Human Intervention DOI
Bidhan C. Saha, Majid Bani-Yaghoub,

Chandra Nath Podder

et al.

Published: Jan. 1, 2025

Language: Английский

Citations

0
Cosmological Parameter Estimation with Genetic Algorithms DOI Creative Commons

Ricardo Medel-Esquivel,

Isidro Gómez-Vargas,

Alejandro A. Morales Sánchez

et al.

Universe, Journal Year: 2023, Volume and Issue: 10(1), P. 11 - 11

Published: Dec. 27, 2023

Genetic algorithms are a powerful tool in optimization for single and multimodal functions. This paper provides an overview of their fundamentals with some analytical examples. In addition, we explore how they can be used as parameter estimation cosmological models to maximize the likelihood function, complementing analysis traditional Markov chain Monte Carlo methods. We analyze that genetic provide fast estimates by focusing on maximizing although cannot confidence regions same statistical meaning Bayesian approaches. Moreover, show implementing sharing niching techniques ensures effective exploration space, even presence local optima, always helping find global optima. approach is invaluable context, where exhaustive space parameters essential. use dark energy exemplify estimation, including problem, also output algorithm obtain derived concludes handy within data analysis, without replacing methods but providing different advantages.

Language: Английский

Citations

10
A data-driven test approach to identify COVID-19 surge phases: an alert-warning tool DOI
Arianna Agosto, Paola Cerchiello

Statistics, Journal Year: 2024, Volume and Issue: 58(2), P. 422 - 436

Published: March 3, 2024

The effective monitoring of the pandemic emergency and, specifically, early detection surge phases are crucial to define proper health policies. We propose a statistical testing approach identify acceleration in contagion growth that potentially marks start new waves, based on study reproduction rate dynamics. proposed method can be considered as supplementary warning system assist policymakers attempt anticipate and tailor countermeasures. It also used an ex-post tool date-stamp evaluate impact implemented strategies their timing. effectiveness our is exemplified ten countries' data, reaching robust insightful results assessing timing severity COVID-19 phases.

Language: Английский

Citations

1
Dynamic Resilience Assessment for Urban Healthcare Infrastructure Operations Considering the Spatiotemporal Characteristics of Public Health Emergencies DOI
Ying Zhou,

Shuainan Zhang,

Chenshuang Li

et al.

Journal of Management in Engineering, Journal Year: 2024, Volume and Issue: 40(6)

Published: Aug. 12, 2024

Language: Английский

Citations

1
A COVID-19 vaccine effectiveness model using the susceptible-exposed-infectious-recovered model DOI Creative Commons
Sabariah Saharan,

C J Tee

Healthcare Analytics, Journal Year: 2023, Volume and Issue: 4, P. 100269 - 100269

Published: Oct. 7, 2023

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) caused the start of COVID-19 outbreak in world, including Malaysia and Thailand. This study identifies trend before after vaccination campaign by using Susceptible-Exposed-Infectious-Recovered (SEIR) Susceptible-Exposed-Infectious-Recovered-Vaccinated (SEIRV) models. Moreover, we predict daily reported death recovery cases SEIR model Holt's linear method then evaluate their performance. The data used this is real from SEIRV provides a comprehensive view efficacy vaccinations curbing outbreak. research reveals that outperforms predicting cases.

Language: Английский

Citations

3
Epidemic Modeling using Hybrid of Time-varying SIRD, Particle Swarm Optimization, and Deep Learning DOI
Naresh Kumar, Seba Susan

2022 13th International Conference on Computing Communication and Networking Technologies (ICCCNT), Journal Year: 2023, Volume and Issue: unknown

Published: July 6, 2023

Epidemiological models are best suitable to model an epidemic if the spread pattern is stationary. To deal with non-stationary patterns and multiple waves of epidemic, we develop a hybrid encompassing modeling, particle swarm optimization, deep learning. The mainly caters three objectives for better prediction: 1. Periodic estimation parameters. 2. Incorporating impact all aspects using data fitting parameter optimization 3. Deep learning based prediction In our model, use system ordinary differential equations (ODEs) Susceptible-Infected-Recovered-Dead (SIRD) Particle Swarm Optimization (PSO) stacked-LSTM forecasting Initial or one time parameters not able epidemic. So, estimate periodically (weekly). We PSO identify optimum values next train on optimized parameters, perform upcoming four weeks. Further, fed LSTM forecasted into SIRD forecast number COVID-19 cases. evaluate highly affected countries namely; USA, India, UK. proposed waves, has outperformed existing methods datasets.

Language: Английский

Citations

2
Collaborative optimization of surgery and ICU under uncertainty DOI Creative Commons
Fang Wan, Tao Wang, Julien Fondrevelle

et al.

Expert Systems with Applications, Journal Year: 2023, Volume and Issue: 243, P. 122950 - 122950

Published: Dec. 14, 2023

Language: Английский

Citations

2
An Infectious Disease Model with Asymptomatic Transmission and Waning Immunity DOI Open Access

Sophia Y. Rong

SIAM Undergraduate Research Online, Journal Year: 2024, Volume and Issue: 17

Published: Jan. 1, 2024

Infectious diseases present persistent challenges to global public health, demanding a comprehensive understanding of their dynamics develop effective prevention and control strategies.The presence asymptomatic carriers, individuals capable transmitting pathogens without displaying symptoms, conventional containment approaches focused on symptomatic cases.Waning immunity, the decline in protective response following natural recovery or vaccination, introduces further complexity disease dynamics.In this paper, we developed mathematical model investigate interplay between these factors, aiming inform strategies for management infectious diseases.We derived basic reproduction number showed that would die out when falls below 1.We obtained formula estimate relative contributions transmission number, which remains unchanged vaccination is included model.Through computer simulations with parameter values tailored COVID-19 sensitivity analysis, demonstrated population susceptibility significantly impacts timing magnitude infection peaks.Populations lower experience delayed less severe outbreaks.Vaccination was shown play crucial role control, an increased rate, extended heightened vaccine efficacy proving pivotal.However, effectiveness hinges maintaining low escape proportion.Taken together, study underscores need multifaceted, adaptable management, highlighting central mitigating spread.Further research validation disease-specific data will enhance estimates, improve predictions, evidence-based strategies.

Language: Английский

Citations

0
COVID-19 dynamical system and cellular automaton based on an extended compartment model of contact network and vaccination impact DOI Creative Commons
Zhiyuan Zhou,

Yu Shi,

Wenjun Cao

et al.

Published: April 29, 2024

In this paper, we study a new round of novel coronavirus disease 2019 (COVID-19) infection scenarios due to mutated strain in the middle epidemic.By considering characteristics presence or absence symptoms, severity and vaccination, develop an extended compartmental model containing 11 compartments describe its transformation process from both discrete continuous perspectives by probabilistic cellular automata system ordinary differential equations.Further, analyze relevance endemic equilibrium points as well trajectory types corresponding equations.Based on model, simulate reoccurrence outbreak United States winter 2021, results fit with actual data show consistency between two forms Probabilistic Cellular Ordinary Differential Equations.The effects contact network vaccination are investigated applying different scenarios.The that premature relaxation social isolation campaigns may lead subsequent waves widespread is effective reducing number severe illnesses deaths.The significance paper provide infectious diseases for mid-epidemic assist epidemic prevention policy-making through Automata.

Language: Английский

Citations

0
Optimizing Contact Network Topological Parameters of Urban Populations Using the Genetic Algorithm DOI Creative Commons
Abimael R. Sergio, P.H.T. Schimit

Entropy, Journal Year: 2024, Volume and Issue: 26(8), P. 661 - 661

Published: Aug. 3, 2024

This paper explores the application of complex network models and genetic algorithms in epidemiological modeling. By considering small-world Barabási–Albert models, we aim to replicate dynamics disease spread urban environments. study emphasizes importance accurately mapping individual contacts social networks forecast progression. Using a algorithm, estimate input parameters for construction, thereby simulating transmission within these networks. Our results demonstrate networks’ resemblance real interactions, highlighting their potential predicting spread. underscores significance understanding managing public health crises.

Language: Английский

Citations

0