Version 1
: Received: 29 June 2020 / Approved: 30 June 2020 / Online: 30 June 2020 (11:40:43 CEST)
Version 2
: Received: 15 February 2021 / Approved: 16 February 2021 / Online: 16 February 2021 (13:18:54 CET)
How to cite:
Zingano, P.; Zingano, J.; Silva, A.; Zingano, C. Defining and Computing Reproduction Numbers to Monitor the Outbreak of Covid-19 or Other Epidemics. Preprints2020, 2020060370. https://doi.org/10.20944/preprints202006.0370.v2
Zingano, P.; Zingano, J.; Silva, A.; Zingano, C. Defining and Computing Reproduction Numbers to Monitor the Outbreak of Covid-19 or Other Epidemics. Preprints 2020, 2020060370. https://doi.org/10.20944/preprints202006.0370.v2
Zingano, P.; Zingano, J.; Silva, A.; Zingano, C. Defining and Computing Reproduction Numbers to Monitor the Outbreak of Covid-19 or Other Epidemics. Preprints2020, 2020060370. https://doi.org/10.20944/preprints202006.0370.v2
APA Style
Zingano, P., Zingano, J., Silva, A., & Zingano, C. (2021). Defining and Computing Reproduction Numbers to Monitor the Outbreak of Covid-19 or Other Epidemics. Preprints. https://doi.org/10.20944/preprints202006.0370.v2
Chicago/Turabian Style
Zingano, P., Alessandra Silva and Carolina Zingano. 2021 "Defining and Computing Reproduction Numbers to Monitor the Outbreak of Covid-19 or Other Epidemics" Preprints. https://doi.org/10.20944/preprints202006.0370.v2
Abstract
We present a general approach to define reproduction ratios or numbers to monitor the outbreak of epidemics that are modeled by mathematical evolution equations. This provides a solution to an important topic that has not been completely settled in the literature, especially in the case of complex epidemiological models. We illustrate our procedure with a full implementation of a standard deterministic SEIR model that is applied to examine the Covid-19 outbreaks and the effects of intervention measures in several countries in America (Argentina, Brazil, Mexico, USA) and Europe (France, Italy, Spain and UK) in 2020. Our code is also used to investigate herd immunity levels for Covid-19, indicating values between 85% and 90%.
Computer Science and Mathematics, Computational Mathematics
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Received:
16 February 2021
Commenter:
Paulo Zingano
Commenter's Conflict of Interests:
Author
Comment:
The new text has been updated and enlarged to include: (1) a discussion of the INITIALIZATION PROBLEM for the SEIR model (Section 2), not covered before; (2) an updated description of the evolution of the Covid-19 epidemic in the 8 countries chosen, now covering the entire year (2020) and including the original predictions made on June/2020 for comparison purposes; (3) estimation of herd immunity levels for covid-19 in 2 distinct scenarios (unwarned/warned populations); (4) an updated bibliography (following referee's suggestions)
Commenter: Paulo Zingano
Commenter's Conflict of Interests: Author
(1) a discussion of the INITIALIZATION PROBLEM for the SEIR model (Section 2), not covered before;
(2) an updated description of the evolution of the Covid-19 epidemic in the 8 countries chosen, now covering the entire year (2020) and including the original predictions made on June/2020 for comparison purposes;
(3) estimation of herd immunity levels for covid-19 in 2 distinct scenarios (unwarned/warned populations);
(4) an updated bibliography (following referee's suggestions)