{"title":"A compartmental epidemic model with age stratification for insurance premium calculation.","authors":"Shirali Kadyrov, Gauhar Kayumova, Asilbek Yallaboyev, Shirali Kadyrov","doi":"10.3934/mbe.2025114","DOIUrl":null,"url":null,"abstract":"<p><p>This paper develops a mathematical framework for life and health insurance premium calculation under epidemic conditions, incorporating age-structured population dynamics and disease compartments. We proposed a compartmental epidemic model with three age groups and four states (susceptible, infectious, recovered, deceased) to reflect heterogeneity in disease progression and risk exposure. The model captures differential mortality and morbidity risks across age groups and infection states, enabling dynamic adjustment of insurance premiums. By integrating actuarial principles with epidemic-driven transition probabilities, we derived explicit premium formulas and validated them through numerical simulations. Our results demonstrate that age stratification and detailed infection stages significantly impact premium pricing, particularly for older populations with higher mortality risks. Sensitivity analysis reveals that recovery and mortality rates are key drivers of premium variability. The framework provides insurers with a robust tool for pandemic risk assessment, ensuring solvency while maintaining affordability.</p>","PeriodicalId":49870,"journal":{"name":"Mathematical Biosciences and Engineering","volume":"22 12","pages":"3088-3106"},"PeriodicalIF":2.6000,"publicationDate":"2025-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mathematical Biosciences and Engineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.3934/mbe.2025114","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Mathematics","Score":null,"Total":0}
引用次数: 0
Abstract
This paper develops a mathematical framework for life and health insurance premium calculation under epidemic conditions, incorporating age-structured population dynamics and disease compartments. We proposed a compartmental epidemic model with three age groups and four states (susceptible, infectious, recovered, deceased) to reflect heterogeneity in disease progression and risk exposure. The model captures differential mortality and morbidity risks across age groups and infection states, enabling dynamic adjustment of insurance premiums. By integrating actuarial principles with epidemic-driven transition probabilities, we derived explicit premium formulas and validated them through numerical simulations. Our results demonstrate that age stratification and detailed infection stages significantly impact premium pricing, particularly for older populations with higher mortality risks. Sensitivity analysis reveals that recovery and mortality rates are key drivers of premium variability. The framework provides insurers with a robust tool for pandemic risk assessment, ensuring solvency while maintaining affordability.
期刊介绍:
Mathematical Biosciences and Engineering (MBE) is an interdisciplinary Open Access journal promoting cutting-edge research, technology transfer and knowledge translation about complex data and information processing.
MBE publishes Research articles (long and original research); Communications (short and novel research); Expository papers; Technology Transfer and Knowledge Translation reports (description of new technologies and products); Announcements and Industrial Progress and News (announcements and even advertisement, including major conferences).