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COVID-19
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COVID-19 @ CIDMA
Projects
Controlo Ótimo e Modelação Matemática da Pandemia COVID-19: contributos para uma estratégia sistémica de intervenção em saúde na comunidade
Predico: Prever a Evolução da Expansão e Incidência da COVID-19
COVID-19: X-Ray Triage Prototype with Artificial Intelligence
Publications
F. Ndairou, I. Area, J. J. Nieto, C. J. Silva and D. F. M. Torres,
Fractional model of COVID-19 applied to Galicia, Spain and Portugal
, Chaos Solitons Fractals 144 (2021), Art. 110652, 7 pp.
Preprint:
http://arxiv.org/abs/2101.0128
7
URL:
http://dx.doi.org/10.1016/j.
chaos.2021.110652
Faiçal Ndairou, Iván Area, Juan J. Nieto and Delfim F. M. Torres,
Mathematical Modeling of COVID-19 Transmission Dynamics with a Case
Study of Wuhan
,
Chaos Solitons Fractals 135 (2020), Art. 109846.
URL:
http://dx.doi.org/10.1016/j.chaos.2020.109846
Faiçal Ndairou, Iván Area, Georg Bader, Juan J. Nieto and Delfim F. M. Torres,
Corrigendum to 'Mathematical Modeling of COVID-19 Transmission Dynamics with a Case Study of Wuhan'
[Chaos Solitons Fractals 135 (2020), 109846]
, Chaos Solitons Fractals 141 (2020), Art. 110311.
URL:
http://dx.doi.org/10.1016/j.ch
aos.2020.110311
C.J. Silva, C. Cruz, D.F.M. Torres, A.P. Munuzuri, A. Carballosa, I. Area, J.J. Nieto, R. Fonseca-Pinto, R. Passadouro da Fonseca, E. Soares dos Santos, W. Abreu and J. Mira,
Optimal control of the COVID-19 pandemic: controlled sanitary deconfinement in Portugal
.
Preprint: arXiv:2009.00660, 1-Sep-2020.
URL:
https://arxiv.org/abs/2009.00660
C.J. Silva, G. Cantin, C. Cruz, R. Fonseca-Pinto, R. Passadouro da Fonseca, E. Soares dos Santos, D.F.M. Torres,
Complex network model for COVID-19: human behavior, pseudo-periodic solutions and multiple epidemic waves.
Preprint: arXiv:2010.02368, 5-Oct-2020.
URL:
https://arxiv.org/abs/2010.02368
J. Couras, I. Area, J. J. Nieto, C. J. Silva and D. F. M. Torres,
Optimal control of vaccination and plasma transfusion with potential usefulness for COVID-19
.
To appear in: Analysis of Infectious Disease Problems (Covid-19) and Their Global Impact, Springer Nature Singapore Pte Ltd, in press.
Preprint: arXiv:2010.04146, 8-Oct-2020.
URL:
https://arxiv.org/abs/2010.041
46
H. Zine, E. M. Lotfi, M. Mahrouf, A. Boukhouima, Y. Aqachmar, K. Hattaf, D. F. M. Torres and N. Yousfi,
Modeling the spread of COVID-19 pandemic in Morocco
.
To appear in: Analysis of Infectious Disease Problems (Covid-19) and Their Global Impact,
Springer Nature Singapore Pte Ltd, in press.
Preprint: arXiv:2010.04115, 8-Oct-2020.
URL:
https://arxiv.org/abs/2010.041
15
H. Zine, A. Boukhouima, E. M. Lotfi, M. Mahrouf, D. F. M. Torres and N. Yousfi,
A stochastic time-delayed model for the effectiveness of Moroccan COVID-19 deconfinement strategy
,
Math. Model. Nat. Phenom. 15 (2020), Art. 50, 14 pp.
Received: 16 May 2020 / Revised: 20 August 2020 / Accepted: 28 October 2020 / Published: 11 November 2020.
DOI:
https://doi.org/10.1051/mmnp/2020040
Ana P. Lemos-Paião, Cristiana J. Silva and Delfim F. M. Torres,
A New Compartmental Epidemiological Model for COVID-19 with a Case Study of Portugal
,
Ecological Complexity 44 (2020) Art. 100885, 8 pp.
Preprint:
https://arxiv.org/abs/2011.087
41
DOI:
https://doi.org/10.1016/j.ecocom.2020.100885
Call for contributions
https://www.researchgate.net/project/Springer-Publisher-Book-on-Recent-Developments-in-the-Mathematical-Modelling-and-Analysis-of-Infectious-Disease-Problems-COVID-19
"Modeling the dynamics of the COVID-19 epidemic and implementation of intervention strategies" in Frontiers in Applied Mathematics and Statistics
https://www.frontiersin.org/re
search-topics/17503/modeling-
the-dynamics-of-the-covid-19-
epidemic-and-implementation-
of-intervention-strategies
News
A investigadora do CIDMA Cristiana J. Silva obteve financiamento para um projecto no âmbito da linha de financiamento “RESEARCH 4 COVID-19” da FCT
Projeto de investigadores da Universidade de Santiago de Compostela, da Universidade de Vigo, do CIDMA-UA e do Centro Nacional de Biotecnología – CSIC financiado pelo Governo de Espanha.
Felipe Freitas, investigador do CIDMA, participa no projeto "Inteligência Artificial para acelerar a triagem de pacientes com COVID-19"