Modeling of gender differences in tuberculosis prevalence
Matematičeskaâ biologiâ i bioinformatika, Tome 13 (2018) no. 2, pp. 308-321.

Voir la notice de l'article provenant de la source Math-Net.Ru

Epidemiological studies have shown that gender differences in tuberculosis prevalence can be explained by physiological, behavioral and social factors. In our work, the quantitative evaluation of the effect of such factors has been received. With this purpose, we developed a mathematical model of tuberculosis dynamics in two-gender population. The model consists of twelve nonlinear differential equations and describes such epidemiological processes as tuberculosis transmission from infectious individuals to susceptible ones, the activation of latent diseases, public health actions in revealing and treating tuberculosis cases. This model has been fitted to data for Moscow. The results of parameter identification demonstrate that low prevalence of tuberculosis among females is mainly accounted for by higher natural resistance to mycobacterium. Higher rate of tuberculosis revealing and more effective treatment in females can be attributed to behavioral factors.
@article{MBB_2018_13_2_a8,
     author = {V. Y. Kisselevskaya-Babinina and T. E. Sannikova and A. A. Romanyukha and A. S. Karkach},
     title = {Modeling of gender differences in tuberculosis prevalence},
     journal = {Matemati\v{c}eska\^a biologi\^a i bioinformatika},
     pages = {308--321},
     publisher = {mathdoc},
     volume = {13},
     number = {2},
     year = {2018},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/MBB_2018_13_2_a8/}
}
TY  - JOUR
AU  - V. Y. Kisselevskaya-Babinina
AU  - T. E. Sannikova
AU  - A. A. Romanyukha
AU  - A. S. Karkach
TI  - Modeling of gender differences in tuberculosis prevalence
JO  - Matematičeskaâ biologiâ i bioinformatika
PY  - 2018
SP  - 308
EP  - 321
VL  - 13
IS  - 2
PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/item/MBB_2018_13_2_a8/
LA  - ru
ID  - MBB_2018_13_2_a8
ER  - 
%0 Journal Article
%A V. Y. Kisselevskaya-Babinina
%A T. E. Sannikova
%A A. A. Romanyukha
%A A. S. Karkach
%T Modeling of gender differences in tuberculosis prevalence
%J Matematičeskaâ biologiâ i bioinformatika
%D 2018
%P 308-321
%V 13
%N 2
%I mathdoc
%U http://geodesic.mathdoc.fr/item/MBB_2018_13_2_a8/
%G ru
%F MBB_2018_13_2_a8
V. Y. Kisselevskaya-Babinina; T. E. Sannikova; A. A. Romanyukha; A. S. Karkach. Modeling of gender differences in tuberculosis prevalence. Matematičeskaâ biologiâ i bioinformatika, Tome 13 (2018) no. 2, pp. 308-321. http://geodesic.mathdoc.fr/item/MBB_2018_13_2_a8/

[1] P. H. Mason, C. Degeling, J. Denholm, “Sociocultural dimensions of tuberculosis: an overview of key concepts”, The International Journal of Tuberculosis and Lung Disease, 19:10 (2015), 1135–1143 | DOI

[2] K. Lonnroth, E. Jaramillo, B. G. Williams, C. Dye, M. Raviglione, “Drivers of tuberculosis epidemics: the role of risk factors and social determinants”, Social Science Medicine, 68:12 (2009), 2240–2246 | DOI

[3] O. Neyrolles, L. Quintana-Murci, “Sexual inequality in tuberculosis”, PLoS Medicine, 6:12 (2009), e1000199 | DOI

[4] P. Hudelson, Gender differentials in tuberculosis: the role of socio-economic and cultural factors, 77:5 (1996), 391–400 | DOI

[5] C. B. Holmes, H. Hausler, P. Nunn, “A review of sex differences in the epidemiology of tuberculosis”, The International Journal of Tuberculosis and Lung Disease, 2:2 (1998), 96–104 | MR

[6] O. A. Melnichenko, A. A. Romanyukha, “Model epidemiologii tuberkuleza. Analiz dannykh i otsenka parametrov”, Matematicheskoe modelirovanie, 20:8 (2008), 107–128 | Zbl

[7] E. E. McClell, J. M. Smith, “Gender specific differences in the immune response to infection”, Archivum Immunologiae et Therapiae Experimentalis, 59:3 (2011), 203–213 | DOI

[8] N. M. Koretskaya, A. A. Narkevich, A. N. Narkevich, “Gendernye osobennosti vpervye vyyavlennogo infiltrativnogo tuberkuleza legkikh”, Pulmonologiya, 2014, no. 1, 77–80 | DOI

[9] O. N. Burmykina, “Gendernye razlichiya v praktikakh zdorovya: podkhody k ob'yasneniyu i empiricheskii analiz”, Zhurnal sotsiologii i sotsialnoi antropologii, 9:2 (2006)

[10] H. Waaler, A. Geser, S. Andersen, “The use of mathematical models in the study of the epidemiology of tuberculosis”, American Journal of Public Health and the Nations Health, 52:6 (1962), 1002–1013 | DOI

[11] S. Brogger, “Systems analysis in tuberculosis control: a model”, American Review of Respiratory Disease, 95:3 (1967), 419–434

[12] Y. Azuma, “A simple simulation model of tuberculosis epidemiology for use without large-scale computers”, Bulletin of the World Health Organization, 52:3 (1975), 313 | MR

[13] S. M. Blower, P. M. Small, P. C. Hopewell, “Control strategies for tuberculosis epidemics: new models for old problems”, Science, 273:5274 (1996), 497–500 | DOI

[14] K. K. Avilov, A. A. Romanyukha, “Matematicheskie modeli rasprostraneniya i kontrolya tuberkuleza (obzor)”, Matematicheskaya biologiya i bioinformatika, 2:2 (2007), 188–318 | DOI

[15] K. K. Avilov, A. A. Romanyukha, “Matematicheskoe modelirovanie protsessov rasprostraneniya tuberkuleza i vyyavleniya bolnykh”, Avtomatika i telemekhanika, 2007, no. 9, 145–160 | MR | Zbl

[16] M. I. Perelman, G. I. Marchuk, S. E. Borisov, B. Y. Kazennykh, K. K. Avilov, A. S. Karkach, A. A. Romanyukha, “Tuberculosis epidemiology in Russia: the mathematical model and data analysis”, Russian Journal of Numerical Analysis and Mathematical Modelling, 19:4 (2004), 305–314 | DOI | MR | Zbl

[17] A. V. Belostotskii, T. Ch. Kasaeva, N. V. Kuzmina, N. V. Nelidova, “Problema priverzhennosti bolnykh tuberkulezom k lecheniyu”, Tuberkulez i bolezni legkikh, 2015, no. 4, 4–9

[18] E. V. Sukhova, “Povedencheskii otvet bolnykh na «kleimo» tuberkuleza”, Sotsialnaya psikhologiya i obschestvo, 6:1 (2015), 127–136

[19] D. A. Zhukov, Biologiya povedeniya. Gumoralnye mekhanizmy, Rech, SPb., 2007