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2020 Volume 11 Issue 4

Information Generation Rate and its Relationship with the Entropy of Non-Linear Models: Covid-19 Case, Peru 2020


Danny Villegas Rivas, Manuel Milla Pino, Salli Villegas Rivas, Erick Delgado Bazan, Yary Pérez Pérez, Zadith Garrido Campaña, Martín Grados Vasquez, Cesar Osorio Carrera, Luis Ramírez Calderón, José Paredes Carranza, Ricardo Shimabuku Ysa
Abstract

In this paper, entropy was studied in non-linear models including exponential, Gompertz, and logistic, to estimate epidemiological parameters of interest in data from confirmed cases of infection by COVID-19 in Peru. The data related to the spread of COVID-19 in Peru comes from the information available on the INS-Peru institutional portal (2020). The Akaike information criterion (AIC) and the residual standard error (ERR) were considered to evaluate the entropy of the models. The estimation of the parameters of the models was carried out using maximum likelihood and by the Bootstrap method. The results showed that the entropy of the models is related to the information generation rate, associated with the differential in the number of tests applied. Entropy severely affected maximum likelihood estimators. The Bootstrap estimators showed better performance against EMV with the estimated peak of confirmed cases. Bootstrap estimators were significantly affected by sample size, especially when n ≤ 10. The results of this research suggest considering the entropy and the information generation rate (differential in the application of tests for the diagnosis of COVID-19 in Peru), as well as the use of Bootstrap estimators as an alternative to estimate parameters of epidemiological models.


How to cite this article
Rivas D V, Pino M M, Rivas S V, Bazan E D, Pérez Y P, Campaña Z G et al. Information Generation Rate and its Relationship with the Entropy of Non-Linear Models: Covid-19 Case, Peru 2020. J Biochem Technol 2020;11(4):8-14
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JOURNAL OF BIOCHEMICAL TECHNOLOGY
JOURNAL OF BIOCHEMICAL TECHNOLOGY
Journal of Biochemical Technology is a peer reviewed International Journal published by the Sevas Publishing on behalf of the Biochemical Technology Society, a Registered Charity Organization from India

AREA OF INTEREST
AREA OF INTEREST
Areas of high interest, cover new advances in enzymatic and protein mechanims; applied molecular genetics and biotechnology; genomics and proteomics; metabolic; medical, environmental, food and agro biotechnology.

FOCUS AND SCOPE
FOCUS AND SCOPE
Journal Of Biochemical Technology” Provides A Medium For The Rapid Publication Of Full-Length Articles, Mini-Reviews Of New And Emerging Products And Short Communications On All Aspects Of ...

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