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

被引:3
|
作者
Sequeira, Joao [1 ,2 ]
Louca, Jorge [1 ]
Mendes, Antonio M. [3 ]
Lind, Pedro G. [4 ,5 ,6 ]
机构
[1] Inst Univ Lisboa ISCTE IUL, ISTAR IUL, Av Forcas Armadas, P-1649026 Lisbon, Portugal
[2] Hosp Santa Cruz, Av Prof Dr Reinaldo Santos, P-2790134 Carnaxide, Portugal
[3] Univ Lisbon, Fac Med, Inst Med Mol Joao Lobo Antunes, Av Prof Egas Moniz, P-1649028 Lisbon, Portugal
[4] OsloMet Oslo Metropolitan Univ, Dept Comp Sci, N-0130 Oslo, Norway
[5] Oslo Metropolitan Univ, Artificial Intelligence Lab, N-0166 Oslo, Norway
[6] NordSTAR Nord Ctr Sustainable & Trustworthy AI Re, Pilestredet 52, N-0166 Oslo, Norway
来源
APPLIED SCIENCES-BASEL | 2022年 / 12卷 / 01期
关键词
malaria; Hurst exponent; Shannon entropy; long range dependence; autocorrelation function; stochastic long memory; gametocytemia; RANGE; MEMORY;
D O I
10.3390/app12010496
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
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.
引用
收藏
页数:27
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