Optimal distribution problem of COVID-19 vaccines: Russia's experience using linear programming method.

This research aims to develop and assess a mathematical model based on linear programming (LP) to optimize the distribution of COVID-19 vaccines, considering population priority groups, epidemic dynamics, and vaccine availability. We analyzed data on morbidity, mortality, and vaccine distribution in...

Descripción completa

Detalles Bibliográficos
Publicado en:Electronic Journal of General Medicine Vol. 22; no. 4; pp. 1 - 13
Autores principales: Zakharova, Kseniya, Ermakov, Dmitriy, Kartashova, Oxana, Berechikidze, Iza, Aysina, Taisiya
Formato: equations & formulas research tables/charts Journal Article
Publicado: Modestum Publications Aug2025
Acceso en línea:Ver este registro en EBSCOhost
fields @attributes:
  recordID: 1
pdfLink:
plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=186565045&site=ehost-live
header:
  @attributes:
    shortDbName: ccm
    uiTerm: 186565045
    longDbName: CINAHL Complete
    uiTag: AN
  controlInfo:
    bkinfo:
    dissinfo:
    jinfo:
      jid:
        25163507
        LNCB
      jtl: Electronic Journal of General Medicine
      issn: 25163507
      maglogo: N
    pubinfo:
      dt: Aug2025
      vid: 22
      iid: 4
      pid: 52459
      pub: Modestum Publications
      place: , <Blank>
    artinfo:
      ui:
        186565045
        186565045
        186565045
        10.29333/ejgm/16367
        186565045
      ppf: 1
      ppct: 12
      formats:
      tig:
        atl: Optimal distribution problem of COVID-19 vaccines: Russia's experience using linear programming method.
      aug:
        au:
          Zakharova, Kseniya
          Ermakov, Dmitriy
          Kartashova, Oxana
          Berechikidze, Iza
          Aysina, Taisiya
        affil: Department of Propaedeutics of Dental Diseases, Institute of Dentistry named after E. V. Borovsky, I. M. Sechenov First Moscow State Medical University (Sechenov University), Moscow, RUSSIA
      sug:
        subj:
          COVID-19 Prevention and Control
          COVID-19 Vaccines Supply and Distribution
          Models, Statistical Evaluation
          Human
          Russia
          Male
          Female
          Adolescence
          Adult
          Middle Age
          Aged
          Aged, 80 and Over
          COVID-19 Mortality
          Death Prevention and Control
          Vaccination Coverage
          Population Characteristics
          Vaccine Efficacy
          Morbidity
          Risk Assessment
          Stratified Random Sample
          Probability
          Descriptive Statistics
          Data Analysis Software
          T-Tests
          Inferential Statistics
          Disease Hotspot
          Sex Factors
          Calibration
          Analysis of Variance
          Adolescent: 13-18 years
          Adult: 19-44 years
          Middle Aged: 45-64 years
          Aged: 65+ years
          Aged, 80 & over
          Male
          Female
      ab: This research aims to develop and assess a mathematical model based on linear programming (LP) to optimize the distribution of COVID-19 vaccines, considering population priority groups, epidemic dynamics, and vaccine availability. We analyzed data on morbidity, mortality, and vaccine distribution in Russia using LP methods, scenario modeling, and statistical analysis. The findings of the study indicate a significant reduction in overall mortality to 5.2 per 100,000 individuals, with a vaccine effectiveness of 89% and vaccination coverage reaching 80%. The model incorporates epidemic parameters such as morbidity, mortality rates, virus spread rate, and characteristics of population groups, including age categories, healthcare and education workers, and vulnerable groups such as the elderly and those with chronic conditions. LP was applied to optimize vaccine distribution by formulating an objective function and constraints based on factors such as vaccine availability, population priorities, and epidemic dynamics, with scenario modeling used to simulate different epidemic conditions and assess the model's stability and effectiveness. The assessment of differences using a 99.5% confidence interval and statistical significance in vaccine distribution changes yielded p < 0.001. The developed LP model effectively optimized vaccine distribution, reducing overall mortality and ensuring vaccination efficiency. The results were adapted to various epidemic scenarios and successfully correlated with real-world data obtained from official statistical reports of the Ministry of Health of the Russian Federation, regional epidemiological centers (including the Moscow Center), and vaccine manufacturers. The data covered the period from January 2021 to December 2022. To achieve a substantial impact of vaccines, it is essential to reach a population coverage of 60-70%.
      pubtype: Academic Journal
      doctype:
        equations & formulas
        research
        tables/charts
        Journal Article
      ougenre: Article
    language: English
    refInfo:
    holdings:
      @attributes:
        islocal: N