Mathematical modeling and forecasting of COVID-19 in Moscow and Novosibirsk region

DOI10.15372/SJNM20200404zbMath1505.92202OpenAlexW4237897758MaRDI QIDQ5048160

Maxim A. Shishlenin, N. M. Prokhoshin, A. Yu. Prikhodko, N. Yu. Zyatkov, Olga I. Krivorotko, Sergey I. Kabanikhin

Publication date: 15 November 2022

Published in: Сибирский журнал вычислительной математики (Search for Journal in Brave)

Full work available at URL: http://mathnet.ru/eng/sjvm756

zbMATH Keywords

optimizationinverse problemmathematical modelinggenetic algorithmidentifiabilityscenariosdifferential evolutionpandemicCOVID-19Moscowannealing simulationNovosibirsk regionSIER-DSIER-HCD

Mathematics Subject Classification ID

Epidemiology (92D30) Qualitative investigation and simulation of ordinary differential equation models (34C60)

Related Items

Modeling epidemics: neural network based on data and SIR-model

Uses Software

• DAISY
• EpiModel

Cites Work

• A theoretical analysis of the peaking phenomenon in classification
• A time delay dynamical model for outbreak of 2019-nCov and the parameter identification
• Mathematical modeling of the spread of the coronavirus disease 2019 (COVID-19) taking into account the undetected infections. The case of China
• Quasi-solution in inverse coefficient problems
• Sensitivity analysis and practical identifiability of some mathematical models in biology
• Identifiability and observability analysis for experimental design in nonlinear dynamical models