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Volume 12
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10.3390/app12010496
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Article

Using the Hurst Exponent and Entropy Measures to Predict Effective Transmissibility in Empirical Series of Malaria Incidence

by
João Sequeira
1,2,
Jorge Louçã
1,
António M. Mendes
3 and
Pedro G. Lind
4,5,6,*
1
ISTAR-IUL, Instituto Universitário de Lisboa (ISCTE-IUL), Av. das Forças Armadas, 1649-026 Lisboa, Portugal
2
Hospital Santa Cruz, Av. Prof. Dr. Reinaldo dos Santos, 2790-134 Carnaxide, Portugal
3
Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Av. Prof. Egas Moniz, 1649-028 Lisboa, Portugal
4
Department of Computer Science, OsloMet–Oslo Metropolitan University, N-0130 Oslo, Norway
5
Artificial Intelligence Lab, Oslo Metropolitan University, N-0166 Oslo, Norway
6
NordSTAR—Nordic Center for Sustainable and Trustworthy AI Research, Pilestredet 52, N-0166 Oslo, Norway
*
Author to whom correspondence should be addressed.
Appl. Sci. 2022, 12(1), 496; https://doi.org/10.3390/app12010496
Submission received: 17 October 2021 / Revised: 27 December 2021 / Accepted: 29 December 2021 / Published: 5 January 2022
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Abstract

We analyze the empirical series of malaria incidence, using the concepts of autocorrelation, Hurst exponent and Shannon entropy with the aim of uncovering hidden variables in those series. From the simulations of an agent model for malaria spreading, we first derive models of the malaria incidence, the Hurst exponent and the entropy as functions of gametocytemia, measuring the infectious power of a mosquito to a human host. Second, upon estimating the values of three observables—incidence, Hurst exponent and entropy—from the data set of different malaria empirical series we predict a value of the gametocytemia for each observable. Finally, we show that the independent predictions show considerable consistency with only a few exceptions which are discussed in further detail.
Keywords: malaria; Hurst exponent; Shannon entropy; long range dependence; autocorrelation function; stochastic long memory; gametocytemia malaria; Hurst exponent; Shannon entropy; long range dependence; autocorrelation function; stochastic long memory; gametocytemia

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MDPI and ACS Style

Sequeira, J.; Louçã, J.; Mendes, A.M.; Lind, P.G. Using the Hurst Exponent and Entropy Measures to Predict Effective Transmissibility in Empirical Series of Malaria Incidence. Appl. Sci. 2022, 12, 496. https://doi.org/10.3390/app12010496

AMA Style

Sequeira J, Louçã J, Mendes AM, Lind PG. Using the Hurst Exponent and Entropy Measures to Predict Effective Transmissibility in Empirical Series of Malaria Incidence. Applied Sciences. 2022; 12(1):496. https://doi.org/10.3390/app12010496

Chicago/Turabian Style

Sequeira, João, Jorge Louçã, António M. Mendes, and Pedro G. Lind. 2022. "Using the Hurst Exponent and Entropy Measures to Predict Effective Transmissibility in Empirical Series of Malaria Incidence" Applied Sciences 12, no. 1: 496. https://doi.org/10.3390/app12010496

APA Style

Sequeira, J., Louçã, J., Mendes, A. M., & Lind, P. G. (2022). Using the Hurst Exponent and Entropy Measures to Predict Effective Transmissibility in Empirical Series of Malaria Incidence. Applied Sciences, 12(1), 496. https://doi.org/10.3390/app12010496

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