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Quantitative Biology > Other Quantitative Biology

arXiv:2003.13890 (q-bio)
COVID-19 e-print

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[Submitted on 31 Mar 2020 (v1), last revised 10 Apr 2020 (this version, v2)]

Title:Robust predictive model for Carriers, Infections and Recoveries (CIR): predicting death rates for CoVid-19 in Spain

Authors:Efren M. Benavides
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Abstract:This article presents a new model to predict the evolution of infective diseases under uncertainty or low-quality information, just as it has happened in the initial scenario during the CoVid-19 spread in China and Europe. The model has been used to predict the death rate in Spain but can be used to predict the demand of ICUs or mechanical ventilators under different restraint policies. The main novelty of the model is that it keeps track of the date of infection of a single individual and uses stochastic distributions to aggregate individuals who share the same date of infection. In addition, it uses two types of infections, mild and serious, with a different recovery time. These features are implemented in a set of differential equations which determine the number of Carriers, Infections, Recoveries, Hospitalized and Deaths. Comparison with real data shows good agreement.
Comments: 11 pages, 2 figures; spelling and typos corrected
Subjects: Other Quantitative Biology (q-bio.OT)
Cite as: arXiv:2003.13890 [q-bio.OT]
  (or arXiv:2003.13890v2 [q-bio.OT] for this version)
  https://doi.org/10.48550/arXiv.2003.13890

Submission history

From: Efrén M. Benavides [view email]
[v1] Tue, 31 Mar 2020 00:52:59 UTC (743 KB)
[v2] Fri, 10 Apr 2020 21:32:27 UTC (1,143 KB)
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