Forecasting of the Epidemic Propagation Based on Solving the Inverse Problem for Discrete and Continuous Mathematical Models of Epidemics with Vaccination

Discrete and continuous compartmental models of the spread of the epidemic are considered, taking into account vaccination and limited time spent in groups.Models include the following groups of people: susceptible, contacted, three categories of patients that are undetected, isolated and hospitalized, immunized, vaccinated, and contact vaccinated.Conducted qualitative and quantitative proposed models.The influence of process parameters is investigated.The problems of restoring the coefficients of the equations under consideration are set based on the results of measuring the number of registered patients, vaccinated and deceased.The inverse problems under consideration are solved using the corresponding optimization methods.As an example, the spread of the COVID-19 epidemic in Kazakhstan is being studied.

Publication Details

Journal
Advanced mathematical models & applications.
Published
2025-08-03
DOI
https://doi.org/10.62476/amma.102224
Primary Topic
COVID-19 epidemiological studies
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Forecasting of the Epidemic Propagation Based on Solving the Inverse Problem for Discrete and Continuous Mathematical Models of Epidemics with Vaccination

Advanced mathematical models & applications.
COVID-19 epidemiological studies
article

Forecasting of the Epidemic Propagation Based on Solving the Inverse Problem for Discrete and Continuous Mathematical Models of Epidemics with Vaccination

article en

Abstract

Discrete and continuous compartmental models of the spread of the epidemic are considered, taking into account vaccination and limited time spent in groups.Models include the following groups of people: susceptible, contacted, three categories of patients that are undetected, isolated and hospitalized, immunized, vaccinated, and contact vaccinated.Conducted qualitative and quantitative proposed models.The influence of process parameters is investigated.The problems of restoring the coefficients of the equations under consideration are set based on the results of measuring the number of registered patients, vaccinated and deceased.The inverse problems under consideration are solved using the corresponding optimization methods.As an example, the spread of the COVID-19 epidemic in Kazakhstan is being studied.

Advanced mathematical models & applications.
Al-Farabi Kazakh National University
Good health and well-being
Openalex Percentile: Top 77%
COVID-19 epidemiological studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.