{"title":"COVID-19 dynamic modeling of immune variability and multistage vaccination strategies: A case study in Malaysia","authors":"Emmanuel A. Nwaibeh , Majid K.M. Ali","doi":"10.1016/j.idm.2024.12.011","DOIUrl":null,"url":null,"abstract":"<div><div>Hybrid-immune and immunodeficient individuals have been identified by the World Health Organization as two vulnerable groups in the context of COVID-19, but their distinct characteristics remain underexplored. To address this gap, we developed an extended <em>SIVS</em> compartmental model that simulates the spread of COVID-19 and the impact of administering three doses of the vaccine (first, second, and booster). This study aims to provide insights into how these vulnerable populations respond to vaccination and the dynamics of waning immunity. Using real-time data from the Ministry of Health of Malaysia (May 2023–April 2024), we estimated key parameters through numerical methods and fitted the model to the data using MATLAB's lsqcurvefit package. We carried out stability and equilibrium analyses, computed the basic reproduction number (<em>R</em><sub>0</sub>), and identified conditions for Hopf bifurcation. Sensitivity analysis highlights the parameters with the greatest impact on infection dynamics. The calculated basic reproduction number and stability results suggest that with current vaccination rates, COVID-19 will persist in the population over an extended period. Our findings provide valuable information for public health agencies, offering recommendations for vaccination strategies targeting hybrid-immune and immunodeficient groups. These insights can inform decisions about vaccine booster schedules and resource allocation to better manage the pandemic.</div></div>","PeriodicalId":36831,"journal":{"name":"Infectious Disease Modelling","volume":"10 2","pages":"Pages 505-521"},"PeriodicalIF":8.8000,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11758414/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Infectious Disease Modelling","FirstCategoryId":"3","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2468042724001374","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0
Abstract
Hybrid-immune and immunodeficient individuals have been identified by the World Health Organization as two vulnerable groups in the context of COVID-19, but their distinct characteristics remain underexplored. To address this gap, we developed an extended SIVS compartmental model that simulates the spread of COVID-19 and the impact of administering three doses of the vaccine (first, second, and booster). This study aims to provide insights into how these vulnerable populations respond to vaccination and the dynamics of waning immunity. Using real-time data from the Ministry of Health of Malaysia (May 2023–April 2024), we estimated key parameters through numerical methods and fitted the model to the data using MATLAB's lsqcurvefit package. We carried out stability and equilibrium analyses, computed the basic reproduction number (R0), and identified conditions for Hopf bifurcation. Sensitivity analysis highlights the parameters with the greatest impact on infection dynamics. The calculated basic reproduction number and stability results suggest that with current vaccination rates, COVID-19 will persist in the population over an extended period. Our findings provide valuable information for public health agencies, offering recommendations for vaccination strategies targeting hybrid-immune and immunodeficient groups. These insights can inform decisions about vaccine booster schedules and resource allocation to better manage the pandemic.
期刊介绍:
Infectious Disease Modelling is an open access journal that undergoes peer-review. Its main objective is to facilitate research that combines mathematical modelling, retrieval and analysis of infection disease data, and public health decision support. The journal actively encourages original research that improves this interface, as well as review articles that highlight innovative methodologies relevant to data collection, informatics, and policy making in the field of public health.