Geo-information system of tuberculosis spread based on inversion and prediction
-
Sergey Kabanikhin
,
Aliya Takuadina
Abstract
The monitoring, analysis and prediction of epidemic spread in the region require the construction of mathematical model, big data processing and visualization because the amount of population and the size of the region could be huge. One of the important steps is refinement of mathematical model, i.e. determination of initial data and coefficients of system of differential equations of epidemiologic processes using additional information. We analyze numerical method for solving inverse problem of epidemiology based on genetic algorithm and traditional optimization approach. Our algorithms are applied to analysis and prediction of epidemic situation in regions of Russian Federation, Republic of Kazakhstan and People’s Republic of China. Due to a great amount of data we use a special software ”Digital Earth” for visualization of epidemic.
Funding source: Russian Science Foundation
Award Identifier / Grant number: 18-71-10044
Funding statement: This work is supported by the Russian Science Foundation (project No. 18-71-10044).
Acknowledgements
Authors are grateful to Igor Marinin for the help in construction of prediction map with GIS “Digital Earth”.
References
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Articles in the same Issue
- Frontmatter
- The fluid-solid interaction scattering problem with unknown buried objects
- Ambarzumyan-type theorem for the impulsive Sturm–Liouville operator
- Error estimates for the iteratively regularized Newton–Landweber method in Banach spaces under approximate source conditions
- The Sommerfeld problem and inverse problem for the Helmholtz equation
- Geo-information system of tuberculosis spread based on inversion and prediction
- Simultaneously identifying the thermal conductivity and radiative coefficient in heat equation from Dirichlet and Neumann boundary measured outputs
- Inverse problems for stochastic parabolic equations with additive noise
- Parametric PSF estimation based on recursive SURE for sparse deconvolution
- The methods of dynamical reconstruction of an input in a system of ordinary differential equations
- Retraction of: Convergence of a series associated with the convexification method for coefficient inverse problems
Articles in the same Issue
- Frontmatter
- The fluid-solid interaction scattering problem with unknown buried objects
- Ambarzumyan-type theorem for the impulsive Sturm–Liouville operator
- Error estimates for the iteratively regularized Newton–Landweber method in Banach spaces under approximate source conditions
- The Sommerfeld problem and inverse problem for the Helmholtz equation
- Geo-information system of tuberculosis spread based on inversion and prediction
- Simultaneously identifying the thermal conductivity and radiative coefficient in heat equation from Dirichlet and Neumann boundary measured outputs
- Inverse problems for stochastic parabolic equations with additive noise
- Parametric PSF estimation based on recursive SURE for sparse deconvolution
- The methods of dynamical reconstruction of an input in a system of ordinary differential equations
- Retraction of: Convergence of a series associated with the convexification method for coefficient inverse problems
