Mathematical modeling of infectious diseases and the impact of vaccination strategies
Mathematical modeling plays a crucial role in understanding and combating infectious diseases, offering predictive insights into disease spread and the impact of vaccination strategies. This paper explored the significance of mathematical modeling in epidemic control efforts, focusing on the interpl...
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| Format: | Article |
| Language: | English |
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AIMS Press
2024-09-01
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| Series: | Mathematical Biosciences and Engineering |
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| Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2024314 |
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| author | Diana Bolatova Shirali Kadyrov Ardak Kashkynbayev |
| author_facet | Diana Bolatova Shirali Kadyrov Ardak Kashkynbayev |
| author_sort | Diana Bolatova |
| collection | DOAJ |
| description | Mathematical modeling plays a crucial role in understanding and combating infectious diseases, offering predictive insights into disease spread and the impact of vaccination strategies. This paper explored the significance of mathematical modeling in epidemic control efforts, focusing on the interplay between vaccination strategies, disease transmission rates, and population immunity. To facilitate meaningful comparisons of vaccination strategies, we maintained a consistent framework by fixing the vaccination capacity to vary from 10 to 100% of the total population. As an example, at a 50% vaccination capacity, the pulse strategy averted approximately 45.61% of deaths, while continuous and hybrid strategies averted around 45.18 and 45.69%, respectively. Sensitivity analysis further indicated that continuous vaccination has a more direct impact on reducing the basic reproduction number $ R_0 $ compared to pulse vaccination. By analyzing key parameters such as $ R_0 $, pulse vaccination coefficients, and continuous vaccination parameters, the study underscores the value of mathematical modeling in shaping public health policies and guiding decision-making during disease outbreaks. |
| format | Article |
| id | doaj-art-16475691b4ea4cf28dcfa4f400eddc3a |
| institution | Kabale University |
| issn | 1551-0018 |
| language | English |
| publishDate | 2024-09-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | Mathematical Biosciences and Engineering |
| spelling | doaj-art-16475691b4ea4cf28dcfa4f400eddc3a2025-01-23T07:47:53ZengAIMS PressMathematical Biosciences and Engineering1551-00182024-09-012197103712310.3934/mbe.2024314Mathematical modeling of infectious diseases and the impact of vaccination strategiesDiana Bolatova0Shirali Kadyrov1Ardak Kashkynbayev2Department of Mathematics and Natural Sciences, SDU University, Kaskelen 040900, KazakhstanDepartment of Mathematics and Natural Sciences, SDU University, Kaskelen 040900, KazakhstanDepartment of Mathematics, School of Sciences and Humanities, Nazarbayev University, Qabanbay Batyr Ave 53, Astana 010000, KazakhstanMathematical modeling plays a crucial role in understanding and combating infectious diseases, offering predictive insights into disease spread and the impact of vaccination strategies. This paper explored the significance of mathematical modeling in epidemic control efforts, focusing on the interplay between vaccination strategies, disease transmission rates, and population immunity. To facilitate meaningful comparisons of vaccination strategies, we maintained a consistent framework by fixing the vaccination capacity to vary from 10 to 100% of the total population. As an example, at a 50% vaccination capacity, the pulse strategy averted approximately 45.61% of deaths, while continuous and hybrid strategies averted around 45.18 and 45.69%, respectively. Sensitivity analysis further indicated that continuous vaccination has a more direct impact on reducing the basic reproduction number $ R_0 $ compared to pulse vaccination. By analyzing key parameters such as $ R_0 $, pulse vaccination coefficients, and continuous vaccination parameters, the study underscores the value of mathematical modeling in shaping public health policies and guiding decision-making during disease outbreaks.https://www.aimspress.com/article/doi/10.3934/mbe.2024314mathematical modelinginfectious diseasesvaccination strategiesepidemic controldisease transmissiondynamical systemsimmunityvaccine effectivenesspublic healthepidemiology |
| spellingShingle | Diana Bolatova Shirali Kadyrov Ardak Kashkynbayev Mathematical modeling of infectious diseases and the impact of vaccination strategies Mathematical Biosciences and Engineering mathematical modeling infectious diseases vaccination strategies epidemic control disease transmission dynamical systems immunity vaccine effectiveness public health epidemiology |
| title | Mathematical modeling of infectious diseases and the impact of vaccination strategies |
| title_full | Mathematical modeling of infectious diseases and the impact of vaccination strategies |
| title_fullStr | Mathematical modeling of infectious diseases and the impact of vaccination strategies |
| title_full_unstemmed | Mathematical modeling of infectious diseases and the impact of vaccination strategies |
| title_short | Mathematical modeling of infectious diseases and the impact of vaccination strategies |
| title_sort | mathematical modeling of infectious diseases and the impact of vaccination strategies |
| topic | mathematical modeling infectious diseases vaccination strategies epidemic control disease transmission dynamical systems immunity vaccine effectiveness public health epidemiology |
| url | https://www.aimspress.com/article/doi/10.3934/mbe.2024314 |
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