Forecasting Trends in the Tuberculosis Epidemic Situation in the Region of the Russian Federation by Dynamic Simulation Model.
Stud Health Technol Inform
; 299: 235-241, 2022 Nov 03.
Article
in English
| MEDLINE | ID: covidwho-2099074
ABSTRACT
The spread of a new coronavirus infection in the last two years together with HIV infection preserves and even increases the potential for the spread of tuberculosis in the world. Sverdlovsk oblast (SO) of Russian Federation is the region with high levels of HIV and tuberculosis (TB). The search for new methods of forecasting of the future epidemic situation for tuberculosis has become particularly relevant. The aim was to develop an effective method for predicting the epidemic situation of tuberculosis using an artificial intelligence (AI) method in the format of a dynamic simulation model based on AI technologies. Statistical data was loaded from the state statistical reporting on TB patients for the period 2007-2017. The parameters were controlled through a system of inequalities. The proposed SDM made it possible to identify and reliably calculate trends of TB epidemiological indicators. Comparison of the predicted values made in 2017 with the actual values of 2018-2021 revealed a reliable coincidence of the trend of movement of TB epidemiological indicators in the region, the maximum deviation was no more than 14.82%. The forecast results obtained with SDM are quite suitable for practical use. Especially, in operational resource planning of measures to counteract the spread of tuberculosis at the regional level.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Tuberculosis
/
HIV Infections
/
Epidemics
Type of study:
Experimental Studies
/
Observational study
/
Prognostic study
Limits:
Humans
Country/Region as subject:
Asia
/
Europa
Language:
English
Journal:
Stud Health Technol Inform
Journal subject:
Medical Informatics
/
Health Services Research
Year:
2022
Document Type:
Article
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