Economic burden of COVID-19: a systematic review

F Richards, P Kodjamanova, X Chen, N Li… - ClinicoEconomics …, 2022 - Taylor & Francis
Objective To review and qualitatively synthesize the evidence related to the economic
burden of COVID-19, including healthcare resource utilization and costs. Methods A …

An evaluation of prospective COVID-19 modelling studies in the USA: from data to science translation

K Nixon, S **dal, F Parker, NG Reich… - The Lancet Digital …, 2022 - thelancet.com
Infectious disease modelling can serve as a powerful tool for situational awareness and
decision support for policy makers. However, COVID-19 modelling efforts faced many …

A differential equations model-fitting analysis of COVID-19 epidemiological data to explain multi-wave dynamics

MJ Beira, PJ Sebastião - Scientific Reports, 2021 - nature.com
Compartmental epidemiological models are, by far, the most popular in the study of
dynamics related with infectious diseases. It is, therefore, not surprising that they are …

Digital twins based on bidirectional LSTM and GAN for modelling the COVID-19 pandemic

C Quilodrán-Casas, VLS Silva, R Arcucci, CE Heaney… - Neurocomputing, 2022 - Elsevier
The outbreak of the coronavirus disease 2019 (COVID-19) has now spread throughout the
globe infecting over 150 million people and causing the death of over 3.2 million people …

A novel scheme for classification of epilepsy using machine learning and a fuzzy inference system based on wearable-sensor health parameters

A Kadu, M Singh, K Ogudo - Sustainability, 2022 - mdpi.com
The tremendous growth of health-related digital information has transformed machine
learning algorithms, allowing them to deliver more relevant information while remotely …

A Koopman operator-based prediction algorithm and its application to COVID-19 pandemic and influenza cases

I Mezić, Z Drmač, N Črnjarić, S Maćešić… - Scientific reports, 2024 - nature.com
Future state prediction for nonlinear dynamical systems is a challenging task. Classical
prediction theory is based on a, typically long, sequence of prior observations and is rooted …

Prediction of Covid-19 spreading and optimal coordination of counter-measures: From microscopic to macroscopic models to Pareto fronts

H Wulkow, TOF Conrad, N Djurdjevac Conrad… - PLoS …, 2021 - journals.plos.org
The Covid-19 disease has caused a world-wide pandemic with more than 60 million positive
cases and more than 1.4 million deaths by the end of November 2020. As long as effective …

Analysis of COVID-19 in Japan with extended SEIR model and ensemble Kalman filter

Q Sun, T Miyoshi, S Richard - Journal of computational and applied …, 2023 - Elsevier
We introduce an extended SEIR infectious disease model with data assimilation for the
study of the spread of COVID-19. In this framework, undetected asymptomatic and pre …

Data assimilation predictive GAN (DA-PredGAN) applied to a spatio-temporal compartmental model in epidemiology

VLS Silva, CE Heaney, Y Li, CC Pain - Journal of Scientific Computing, 2023 - Springer
We propose a novel use of generative adversarial networks (GANs)(i) to make predictions in
time (PredGAN) and (ii) to assimilate measurements (DA-PredGAN). In the latter case, we …

Data assimilation method for improving the global spatiotemporal predictions of epidemic dynamics yielded by an ensemble Kalman filter and Metropolis–Hastings …

F Liu, X Nie, A Wu, Z Zhao, C Ma, L Ning, Y Zhu… - Nonlinear …, 2023 - Springer
Assimilating the latest epidemic data can improve the predictions of epidemic dynamics
compared with those using only dynamic models. However, capturing the nonlinear …