Bi-logistic model for disease dynamics caused by Mycobacterium tuberculosis in Russia
Author(s) -
Anastasia I. Lavrova,
Eugene B. Postnikov,
Olga Manicheva,
Boris Vishnevsky
Publication year - 2017
Publication title -
royal society open science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.84
H-Index - 51
ISSN - 2054-5703
DOI - 10.1098/rsos.171033
Subject(s) - tuberculosis , mycobacterium tuberculosis , logistic function , population , epidemiology , construct (python library) , subdivision , biology , computer science , mathematics , statistics , geography , environmental health , medicine , pathology , archaeology , programming language
In this work, we explore epidemiological dynamics by the example of tuberculosis in Russian Federation. It has been shown that the epidemiological dynamics correlates linearly with the virulence of Mycobacterium tuberculosis during the period 1987–2012. To construct an appropriate model, we have analysed (using LogLet decomposition method) epidemiological World Health Organization (WHO) data (period 1980–2014) and obtained, as result of their integration, a curve approximated by a bi-logistic function. This fact allows a subdivision of the whole population into parts, each of them satisfies the Verhulst-like models with different constant virulences introduced into each subsystem separately. Such a subdivision could be interconnected with the heterogeneous structure of mycobacterial population that has a high ability of adaptation to the host and strong mutability.
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