Potential for eliminating COVID-19 in Thailand through third-dose vaccination: A modeling approach
The COVID-19 pandemic continues to pose significant challenges to global public health, necessitating the development of effective vaccination strategies to mitigate disease transmission. In Thailand, the COVID-19 epidemic has undergone multiple waves, prompting the implementation of various control...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
AIMS Press
2024-08-01
|
| Series: | Mathematical Biosciences and Engineering |
| Subjects: | |
| Online Access: | https://www.aimspress.com/article/doi/10.3934/mbe.2024298 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832590798899642368 |
|---|---|
| author | Pannathon Kreabkhontho Watchara Teparos Thitiya Theparod |
| author_facet | Pannathon Kreabkhontho Watchara Teparos Thitiya Theparod |
| author_sort | Pannathon Kreabkhontho |
| collection | DOAJ |
| description | The COVID-19 pandemic continues to pose significant challenges to global public health, necessitating the development of effective vaccination strategies to mitigate disease transmission. In Thailand, the COVID-19 epidemic has undergone multiple waves, prompting the implementation of various control measures, including vaccination campaigns. Understanding the dynamics of disease transmission and the impact of vaccination strategies is crucial for guiding public health interventions and optimizing epidemic control efforts. In this study, we developed a comprehensive mathematical model, termed $ S{S}_{v}I{H}_{1}C{H}_{2}RD $, to elucidate the dynamics of the COVID-19 epidemic in Thailand. The model incorporates key epidemiological parameters, vaccination rates, and disease progression stages to assess the effectiveness of different vaccination strategies in curbing disease transmission. Parameter estimation and model fitting were conducted using real-world data from COVID-19 patients in Thailand, enabling the simulation of epidemic scenarios and the exploration of optimal vaccination rates. Our results showed that optimizing vaccination strategies, particularly by administering approximately 119,625 doses per day, can significantly reduce the basic reproduction number ($ {R}_{0} $) below 1, thereby accelerating epidemic control. Simulation results demonstrated that the optimal vaccination rate led to a substantial decrease in the number of infections, with the epidemic projected to be completely eradicated from the population by June 19, 2022. These findings underscore the importance of targeted vaccination efforts and proactive public health interventions in mitigating the spread of COVID-19 and minimizing the burden on healthcare systems. Our study provides valuable insights into the optimization of vaccination strategies for epidemic control, offering guidance for policymakers and healthcare authorities in Thailand and beyond. By leveraging mathematical modeling techniques and real-world data, stakeholders can develop evidence-based strategies to combat the COVID-19 pandemic and safeguard public health. |
| format | Article |
| id | doaj-art-25da02c6eced45e0a2c46e16befcee82 |
| institution | Kabale University |
| issn | 1551-0018 |
| language | English |
| publishDate | 2024-08-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | Mathematical Biosciences and Engineering |
| spelling | doaj-art-25da02c6eced45e0a2c46e16befcee822025-01-23T07:47:47ZengAIMS PressMathematical Biosciences and Engineering1551-00182024-08-012186807682810.3934/mbe.2024298Potential for eliminating COVID-19 in Thailand through third-dose vaccination: A modeling approachPannathon Kreabkhontho0Watchara Teparos1Thitiya Theparod2Department of Mathematics, Mahasarakham University, Maha Sarakham 44150, ThailandDepartment of General Science, Faculty of Science and Engineering, Kasetsart University, Chalermphrakiat Sakon Nakhon Province Campus, Sakon Nakhon 47000, ThailandDepartment of Mathematics, Mahasarakham University, Maha Sarakham 44150, ThailandThe COVID-19 pandemic continues to pose significant challenges to global public health, necessitating the development of effective vaccination strategies to mitigate disease transmission. In Thailand, the COVID-19 epidemic has undergone multiple waves, prompting the implementation of various control measures, including vaccination campaigns. Understanding the dynamics of disease transmission and the impact of vaccination strategies is crucial for guiding public health interventions and optimizing epidemic control efforts. In this study, we developed a comprehensive mathematical model, termed $ S{S}_{v}I{H}_{1}C{H}_{2}RD $, to elucidate the dynamics of the COVID-19 epidemic in Thailand. The model incorporates key epidemiological parameters, vaccination rates, and disease progression stages to assess the effectiveness of different vaccination strategies in curbing disease transmission. Parameter estimation and model fitting were conducted using real-world data from COVID-19 patients in Thailand, enabling the simulation of epidemic scenarios and the exploration of optimal vaccination rates. Our results showed that optimizing vaccination strategies, particularly by administering approximately 119,625 doses per day, can significantly reduce the basic reproduction number ($ {R}_{0} $) below 1, thereby accelerating epidemic control. Simulation results demonstrated that the optimal vaccination rate led to a substantial decrease in the number of infections, with the epidemic projected to be completely eradicated from the population by June 19, 2022. These findings underscore the importance of targeted vaccination efforts and proactive public health interventions in mitigating the spread of COVID-19 and minimizing the burden on healthcare systems. Our study provides valuable insights into the optimization of vaccination strategies for epidemic control, offering guidance for policymakers and healthcare authorities in Thailand and beyond. By leveraging mathematical modeling techniques and real-world data, stakeholders can develop evidence-based strategies to combat the COVID-19 pandemic and safeguard public health.https://www.aimspress.com/article/doi/10.3934/mbe.2024298mathematical modelingcontrol strategycovid-19 eliminationthird-dose vaccinationbasic reproduction number |
| spellingShingle | Pannathon Kreabkhontho Watchara Teparos Thitiya Theparod Potential for eliminating COVID-19 in Thailand through third-dose vaccination: A modeling approach Mathematical Biosciences and Engineering mathematical modeling control strategy covid-19 elimination third-dose vaccination basic reproduction number |
| title | Potential for eliminating COVID-19 in Thailand through third-dose vaccination: A modeling approach |
| title_full | Potential for eliminating COVID-19 in Thailand through third-dose vaccination: A modeling approach |
| title_fullStr | Potential for eliminating COVID-19 in Thailand through third-dose vaccination: A modeling approach |
| title_full_unstemmed | Potential for eliminating COVID-19 in Thailand through third-dose vaccination: A modeling approach |
| title_short | Potential for eliminating COVID-19 in Thailand through third-dose vaccination: A modeling approach |
| title_sort | potential for eliminating covid 19 in thailand through third dose vaccination a modeling approach |
| topic | mathematical modeling control strategy covid-19 elimination third-dose vaccination basic reproduction number |
| url | https://www.aimspress.com/article/doi/10.3934/mbe.2024298 |
| work_keys_str_mv | AT pannathonkreabkhontho potentialforeliminatingcovid19inthailandthroughthirddosevaccinationamodelingapproach AT watcharateparos potentialforeliminatingcovid19inthailandthroughthirddosevaccinationamodelingapproach AT thitiyatheparod potentialforeliminatingcovid19inthailandthroughthirddosevaccinationamodelingapproach |