About neural network modeling and prediction epizootic tulartmia at tula state territory

V. Evstegneeva; Tatyana Chestnova; O. Smolyaninova

doi:doi:10.12737/7240

About neural network modeling and prediction epizootic tulartmia at tula state territory

Published в Journal of New Medical Technologies. eJournal · Volume 8, Issue 1, 2014 · Pages 0–0 · Rubrics: BIOLOGY OF COMPOUND SYSTEMS. MATHEMATIC BIOLOGY AND BIOINFORMATION IN MEDICOBIOLOGICAL SYSTEMS

DOI 10.12737/7240

Received: 18.12.2014 Accepted: 18.12.2014 Published: 18.12.2014 Language of publication: RUS

Authors

V. Evstegneeva · Tatyana Chestnova · O. Smolyaninova

ABSTRACT

Epizootical monitoring of natural tularemia focuses for 1976-4014 years showed that main carrier of infection is common vole (Microtus arvalis). For the part of all obtained cultures of tularemia bacteria common vole has 51,2%. Its strength and infection can change. At period for 1976-2006 years, natural tularemia focuses were at high activity level, but since 2007 year for now, they are at low activity level. By using method artificial neural network made mathematical model of prediction epizootical tularemia; found that climatic factors (downfalls, temperature, snow depth) playing main role at processes reduction activity and strength of natural tularemia focuses, for example, tularemia epizootia can happen in case of froze December, numerous downfalls and high snow depth.

KEYWORDS

tularemia epizootia common vole (Microtus arvalis) artificial neural network strength infection natural tularemia focus climatic factors.

Information References

Authors:

Type:

Article

Pages:

from 0 to 0

Status:

Published

Language:

Russian

Keywords:

tularemia, epizootia, common vole (Microtus arvalis), artificial neural network, strength, infection, natural tularemia focus, climatic factors.

References

1. Chestnova T.V., Khromushin V.A. Kontekstno-razvivayushchayasya baza dannykh dlya logicheskoy intel-lektual´noy sistemy, ispol´zuemoy v zdravookhranenii. Epidemiologiya i infektsionnye bolezni. 2001. № 4. S. 38-40.

2. Chestnova T.V. Logiko-matematicheskaya model´ differentsial´noy diagnostiki listerioza. Epidemiologiya i infektsionnye bolezni. 2001. № 5. S. 49-50.

3. Novokhatka A.D., Smol´yaninova O.L., Chestnova T.V. Vliyanie infitsirovannosti i chislennosti melkikh mlekopitayushchikh po landshaftno-geograficheskim zonam Tul´skoy oblasti na zabolevaemost´ leptospirozom serogruppy grippotifoza. Vestnik novykh meditsinskikh tekhnologiy. 2005. №1. S.122-124.

4. Chestnova T.V., Smol´yaninova O.L., Logvinov S.I. K voprosu o vybore metoda prognozirovaniya zabolevaemosti leptospirozom. Vestnik novykh meditsinskikh tekhnologiy. 2011. № 4. S. 18-21.

5. Chestnova T.V., Smol´yaninova O.L., Smol´yaninova V.A. K voprosu prognozirovaniya chislenno-sti iksodovykh kleshchey I. ricinus v prirodnykh biotopakh s pomoshch´yu iskusstvennykh neyronnykh setey. Vestnik novykh meditsinskikh tekhnologiy. 2012. № 1. S. 231-232.

6. Smol´yaninova O.L., Chestnova T.V. Leptospiroz v Tul´skoy oblasti. Tula: izdatel´stvo Tul-GU, 2013. 201 s.

7. Smol´yaninova O.L., Chestnova T.V. Sistemnyy analiz i prognozirovanie zabolevaemosti lep-tospirozom. Tula: Izdatel´stvo TulGU, 2006. 116 s.

8. Chestnova T.V., Smol´yaninova O.L. Laboratornaya diagnostika osobo opasnykh infektsionnykh zabolevaniy. Tula, 2009. 168 s.

9. Chestnova T.V. Epidemiologicheskiy nadzor pri listerioze. Tula, 2003. 140 s.

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