arXiv Open Access 2020

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

Efren M. Benavides
Lihat Sumber

Abstrak

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.

Topik & Kata Kunci

Penulis (1)

E

Efren M. Benavides

Format Sitasi

Benavides, E.M. (2020). Robust predictive model for Carriers, Infections and Recoveries (CIR): predicting death rates for CoVid-19 in Spain. https://arxiv.org/abs/2003.13890

Akses Cepat

Lihat di Sumber
Informasi Jurnal
Tahun Terbit
2020
Bahasa
en
Sumber Database
arXiv
Akses
Open Access ✓