Literature DB >> 33027318

Correction to: System inference for the spatio-temporal evolution of infectious diseases: Michigan in the time of COVID-19.

Z Wang1, X Zhang1, G H Teichert1, M Carrasco-Teja1, K Garikipati1.   

Abstract

[This corrects the article DOI: 10.1007/s00466-020-01894-2.]. © Springer-Verlag GmbH Germany, part of Springer Nature 2020.

Entities:  

Year:  2020        PMID: 33027318      PMCID: PMC7526514          DOI: 10.1007/s00466-020-01925-y

Source DB:  PubMed          Journal:  Comput Mech        ISSN: 0178-7675            Impact factor:   4.014


Correction to: Comput Mech 10.1007/s00466-020-01894-2

The original article was published with errors in some sentences. The correct sentences are provided in this correction. The word “rate” in the sentence “It follows that is the effective reproduction rate: the total number...” under the section “2 The compartmental model of infectious disease dynamics” should read as “number”. The sentence “The F-test is achieved through the following algorithm” below the equation 20 should read as “The F-test is achieved through the application of Algorithm 2”. Also, under the section “6.1 Systemidentification and ODE-constrained Optimization”, the word “rate” in the sentence “...rapid decline of the effective reproduction rate, r0(t).” in the third paragraph should read as number”. The word “East” in the sentence “By contrast, Washtenaw County, about 50 km to the East, but” in the fourth paragraph should read as “west”. Under the section “6.2 Deep and Bayesian neural networks” the word “Appendix” in the sentence “Regions are given in Appendix...” in fourth paragraph should read as “Appendices” In the fifth paragraph, the word “rate” in the sentence “The effective reproduction rate r0(t)...” should read as “number” and the word “Appendix” in the sentence “The regional results in Appendix “DNN” should read as “Appendices”. The word “rate” in the caption of Fig. 6 “Parameters of time-dependent SIRD coefficients, , , , and the effective reproduction rate, r0(t), for Regions 1–8 (see Fig. 1) of Michigan” should read as “number”. In the seventh paragraph, the word “rate” in the sentence “...effective reproduction rate r0(t)” should read as “number”. The Eqs. 43, 44 and 45 was published incorrectly. The correct equations are provided below.The word “rate” under the section “7.3 Results of system identification of two dimensional SIRDmodel with diffusion” in the fourth line should read as “number” and the sentence “While the preliminary nature of these warrants caution...” should read as “While the preliminary nature of these results warrants caution..”. The word “open” in the caption of Fig. 16 “Regions 1–8: Time-dependent coefficients identified by DNNs, where an increased infection rate after the open (O) of lockdown on June 1st is observed” should read as “opening”. The word “open” in the caption of Fig. 18 “Regions 1–8: Time-dependent coefficients identified by BNNs, where an increased infection rate after the open (O) of lockdown on June 1st is observed. Bands correspond to ± standard deviation over the mean” should read as “opening”. Original article has been corrected.
  6 in total

1.  Optimization in the Context of COVID-19 Prediction and Control: A Literature Review.

Authors:  Elizabeth Jordan; Delia E Shin; Surbhi Leekha; Shapour Azarm
Journal:  IEEE Access       Date:  2021-09-17       Impact factor: 3.476

2.  Is it safe to lift COVID-19 travel bans? The Newfoundland story.

Authors:  Kevin Linka; Proton Rahman; Alain Goriely; Ellen Kuhl
Journal:  Comput Mech       Date:  2020-08-29       Impact factor: 4.014

3.  Global and local mobility as a barometer for COVID-19 dynamics.

Authors:  Kevin Linka; Alain Goriely; Ellen Kuhl
Journal:  Biomech Model Mechanobiol       Date:  2021-01-15

4.  Towards Providing Effective Data-Driven Responses to Predict the Covid-19 in São Paulo and Brazil.

Authors:  Fabio Amaral; Wallace Casaca; Cassio M Oishi; José A Cuminato
Journal:  Sensors (Basel)       Date:  2021-01-13       Impact factor: 3.576

5.  System Inference Via Field Inversion for the Spatio-Temporal Progression of Infectious Diseases: Studies of COVID-19 in Michigan and Mexico.

Authors:  Zhenlin Wang; Mariana Carrasco-Teja; Xiaoxuan Zhang; Gregory H Teichert; Krishna Garikipati
Journal:  Arch Comput Methods Eng       Date:  2021-10-01       Impact factor: 7.302

6.  Assessing the Spatio-temporal Spread of COVID-19 via Compartmental Models with Diffusion in Italy, USA, and Brazil.

Authors:  Malú Grave; Alex Viguerie; Gabriel F Barros; Alessandro Reali; Alvaro L G A Coutinho
Journal:  Arch Comput Methods Eng       Date:  2021-07-27       Impact factor: 7.302

  6 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.