Modeling vaccination prioritization strategies for post-pandemic COVID-19 in the Republic of Korea accounting for under-reporting and age-structure
Background: Vaccination has played a key role in limiting the impacts of COVID-19. Even though the acute phase of the COVID-19 pandemic is now over, the potential for substantial numbers of cases and deaths due to novel SARS-CoV-2 variants remains. In the Republic of Korea, a strategy of vaccinating...
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Elsevier
2025-04-01
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| Series: | Journal of Infection and Public Health |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1876034125000371 |
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| author | Geunsoo Jang Jihyeon Kim Robin N. Thompson Hyojung Lee |
| author_facet | Geunsoo Jang Jihyeon Kim Robin N. Thompson Hyojung Lee |
| author_sort | Geunsoo Jang |
| collection | DOAJ |
| description | Background: Vaccination has played a key role in limiting the impacts of COVID-19. Even though the acute phase of the COVID-19 pandemic is now over, the potential for substantial numbers of cases and deaths due to novel SARS-CoV-2 variants remains. In the Republic of Korea, a strategy of vaccinating individuals in high-risk groups annually began in October 2023. Methods: We used mathematical modeling to assess the effectiveness of alternative vaccination strategies under different assumptions about the number of available vaccine doses. An age-structured transmission model was developed using vaccination and seropositivity data. Various vaccination scenarios were considered, taking into account the effect of undetected or unreported cases (with different levels of reporting by age group): S1: prioritizing vaccination towards the oldest individuals; S2: prioritizing vaccination towards the youngest individuals; and S3: spreading vaccines among all age groups. Results: Our analysis reveals three key findings. First, administering vaccines to older age groups reduces the number of deaths, while instead targeting younger individuals reduces the number of infections. Second, with approximately 6,000,000 doses available annually, it is recommended that older age groups are prioritized for vaccination, achieving a substantial reduction in the number of deaths compared to a scenario without vaccination. Finally, since case detection (and subsequent isolation) affects transmission, the number of cumulative cases was found to be affected substantially by changes in the reporting rate. Conclusions: In conclusion, vaccination and case detection (facilitated by contact tracing) both play important roles in limiting the impacts of COVID-19. The mathematical modeling approach presented here provides a framework for assessing the effectiveness of different vaccination strategies in scenarios with limited vaccine supply. |
| format | Article |
| id | doaj-art-bc530c72fbf1401e83893ca4c1b61d0c |
| institution | Kabale University |
| issn | 1876-0341 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Infection and Public Health |
| spelling | doaj-art-bc530c72fbf1401e83893ca4c1b61d0c2025-02-06T05:11:28ZengElsevierJournal of Infection and Public Health1876-03412025-04-01184102688Modeling vaccination prioritization strategies for post-pandemic COVID-19 in the Republic of Korea accounting for under-reporting and age-structureGeunsoo Jang0Jihyeon Kim1Robin N. Thompson2Hyojung Lee3Nonlinear Dynamics and Mathematical Application Center, Kyungpook National University, Daegu 41566, Republic of KoreaDepartment of Statistics, Kyungpook National University, Daegu 41566, Republic of KoreaMathematical Institute, University of Oxford, Oxford OX2 6GG, United KingdomDepartment of Statistics, Kyungpook National University, Daegu 41566, Republic of Korea; Corresponding author.Background: Vaccination has played a key role in limiting the impacts of COVID-19. Even though the acute phase of the COVID-19 pandemic is now over, the potential for substantial numbers of cases and deaths due to novel SARS-CoV-2 variants remains. In the Republic of Korea, a strategy of vaccinating individuals in high-risk groups annually began in October 2023. Methods: We used mathematical modeling to assess the effectiveness of alternative vaccination strategies under different assumptions about the number of available vaccine doses. An age-structured transmission model was developed using vaccination and seropositivity data. Various vaccination scenarios were considered, taking into account the effect of undetected or unreported cases (with different levels of reporting by age group): S1: prioritizing vaccination towards the oldest individuals; S2: prioritizing vaccination towards the youngest individuals; and S3: spreading vaccines among all age groups. Results: Our analysis reveals three key findings. First, administering vaccines to older age groups reduces the number of deaths, while instead targeting younger individuals reduces the number of infections. Second, with approximately 6,000,000 doses available annually, it is recommended that older age groups are prioritized for vaccination, achieving a substantial reduction in the number of deaths compared to a scenario without vaccination. Finally, since case detection (and subsequent isolation) affects transmission, the number of cumulative cases was found to be affected substantially by changes in the reporting rate. Conclusions: In conclusion, vaccination and case detection (facilitated by contact tracing) both play important roles in limiting the impacts of COVID-19. The mathematical modeling approach presented here provides a framework for assessing the effectiveness of different vaccination strategies in scenarios with limited vaccine supply.http://www.sciencedirect.com/science/article/pii/S1876034125000371Mathematical modelingVaccinationCOVID-19Unreported rateAge-structured model |
| spellingShingle | Geunsoo Jang Jihyeon Kim Robin N. Thompson Hyojung Lee Modeling vaccination prioritization strategies for post-pandemic COVID-19 in the Republic of Korea accounting for under-reporting and age-structure Journal of Infection and Public Health Mathematical modeling Vaccination COVID-19 Unreported rate Age-structured model |
| title | Modeling vaccination prioritization strategies for post-pandemic COVID-19 in the Republic of Korea accounting for under-reporting and age-structure |
| title_full | Modeling vaccination prioritization strategies for post-pandemic COVID-19 in the Republic of Korea accounting for under-reporting and age-structure |
| title_fullStr | Modeling vaccination prioritization strategies for post-pandemic COVID-19 in the Republic of Korea accounting for under-reporting and age-structure |
| title_full_unstemmed | Modeling vaccination prioritization strategies for post-pandemic COVID-19 in the Republic of Korea accounting for under-reporting and age-structure |
| title_short | Modeling vaccination prioritization strategies for post-pandemic COVID-19 in the Republic of Korea accounting for under-reporting and age-structure |
| title_sort | modeling vaccination prioritization strategies for post pandemic covid 19 in the republic of korea accounting for under reporting and age structure |
| topic | Mathematical modeling Vaccination COVID-19 Unreported rate Age-structured model |
| url | http://www.sciencedirect.com/science/article/pii/S1876034125000371 |
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