{"title":"通过第三剂疫苗接种在泰国消灭 COVID-19 的可能性:建模方法。","authors":"Pannathon Kreabkhontho, Watchara Teparos, Thitiya Theparod","doi":"10.3934/mbe.2024298","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":49870,"journal":{"name":"Mathematical Biosciences and Engineering","volume":null,"pages":null},"PeriodicalIF":2.6000,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Potential for eliminating COVID-19 in Thailand through third-dose vaccination: A modeling approach.\",\"authors\":\"Pannathon Kreabkhontho, Watchara Teparos, Thitiya Theparod\",\"doi\":\"10.3934/mbe.2024298\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":49870,\"journal\":{\"name\":\"Mathematical Biosciences and Engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2024-08-09\",\"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.2024298\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Mathematics\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mathematical Biosciences and Engineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.3934/mbe.2024298","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Mathematics","Score":null,"Total":0}
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 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.
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).