Using compartmental models and Particle Swarm Optimization to assess Dengue basic reproduction number R0 for the Republic of Panama in the 1999-2022 period
Nowadays, the ability to make data-driven decisions in public health is of utmost importance. To achieve this, it is necessary for modelers to comprehend the impact of models on the future state of healthcare systems. Compartmental models are a valuable tool for making informed epidemiological decis...
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| Format: | Article |
| Language: | English |
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Elsevier
2023-04-01
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| Series: | Heliyon |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2405844023026312 |
| _version_ | 1797836896515129344 |
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| author | Vicente Alonso Navarro Valencia Yamilka Díaz Jose Miguel Pascale Maciej F. Boni Javier E. Sanchez-Galan |
| author_facet | Vicente Alonso Navarro Valencia Yamilka Díaz Jose Miguel Pascale Maciej F. Boni Javier E. Sanchez-Galan |
| author_sort | Vicente Alonso Navarro Valencia |
| collection | DOAJ |
| description | Nowadays, the ability to make data-driven decisions in public health is of utmost importance. To achieve this, it is necessary for modelers to comprehend the impact of models on the future state of healthcare systems. Compartmental models are a valuable tool for making informed epidemiological decisions, and the proper parameterization of these models is crucial for analyzing epidemiological events. This work evaluated the use of compartmental models in conjunction with Particle Swarm Optimization (PSO) to determine optimal solutions and understand the dynamics of Dengue epidemics. The focus was on calculating and evaluating the rate of case reproduction, R0, for the Republic of Panama. Three compartmental models were compared: Susceptible-Infected-Recovered (SIR), Susceptible-Exposed-Infected-Recovered (SEIR), and Susceptible-Infected-Recovered Human-Susceptible-Infected Vector (SIR Human-SI Vector, SIR-SI). The models were informed by demographic data and Dengue incidence in the Republic of Panama between 1999 and 2022, and the susceptible population was analyzed. The SIR, SEIR, and SIR-SI models successfully provided R0 estimates ranging from 1.09 to 1.74. This study provides, to the best of our understanding, the first calculation of R0 for Dengue outbreaks in the Republic of Panama. |
| first_indexed | 2024-04-09T15:17:18Z |
| format | Article |
| id | doaj.art-8fc3feb4e01d489d8bc852ba2d9b437c |
| institution | Directory Open Access Journal |
| issn | 2405-8440 |
| language | English |
| last_indexed | 2024-04-09T15:17:18Z |
| publishDate | 2023-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Heliyon |
| spelling | doaj.art-8fc3feb4e01d489d8bc852ba2d9b437c2023-04-29T14:56:42ZengElsevierHeliyon2405-84402023-04-0194e15424Using compartmental models and Particle Swarm Optimization to assess Dengue basic reproduction number R0 for the Republic of Panama in the 1999-2022 periodVicente Alonso Navarro Valencia0Yamilka Díaz1Jose Miguel Pascale2Maciej F. Boni3Javier E. Sanchez-Galan4Facultad de Ciencias y Tecnología, Universidad Tecnológica de Panamá, Campus Victor Levi Sasso, Panama, PanamaDepartment of Research in Virology and Biotechnology, Gorgas Memorial Institute of Health Studies, Panama, PanamaUnit of Diagnosis, Clinical Research and Tropical Medicine, Gorgas Memorial Institute of Health Studies, Panama, Panama; Sistema Nacional de Investigación, SENACYT, Ciudad del Saber, Panama, PanamaCenter for Infectious Disease Dynamics, Department of Biology, Pennsylvania State University, University Park, USAGrupo de Investigación en Biotecnología, Bioinformática y Biología de Sistemas (GIBBS), Facultad de Ingeniería de Sistemas Computacionales, Universidad Tecnológica de Panamá, Campus Victor Levi Sasso, Panama, Panama; Sistema Nacional de Investigación, SENACYT, Ciudad del Saber, Panama, Panama; Corresponding author.Nowadays, the ability to make data-driven decisions in public health is of utmost importance. To achieve this, it is necessary for modelers to comprehend the impact of models on the future state of healthcare systems. Compartmental models are a valuable tool for making informed epidemiological decisions, and the proper parameterization of these models is crucial for analyzing epidemiological events. This work evaluated the use of compartmental models in conjunction with Particle Swarm Optimization (PSO) to determine optimal solutions and understand the dynamics of Dengue epidemics. The focus was on calculating and evaluating the rate of case reproduction, R0, for the Republic of Panama. Three compartmental models were compared: Susceptible-Infected-Recovered (SIR), Susceptible-Exposed-Infected-Recovered (SEIR), and Susceptible-Infected-Recovered Human-Susceptible-Infected Vector (SIR Human-SI Vector, SIR-SI). The models were informed by demographic data and Dengue incidence in the Republic of Panama between 1999 and 2022, and the susceptible population was analyzed. The SIR, SEIR, and SIR-SI models successfully provided R0 estimates ranging from 1.09 to 1.74. This study provides, to the best of our understanding, the first calculation of R0 for Dengue outbreaks in the Republic of Panama.http://www.sciencedirect.com/science/article/pii/S2405844023026312ODEPSOSIRSEIRSIR-SIR0 |
| spellingShingle | Vicente Alonso Navarro Valencia Yamilka Díaz Jose Miguel Pascale Maciej F. Boni Javier E. Sanchez-Galan Using compartmental models and Particle Swarm Optimization to assess Dengue basic reproduction number R0 for the Republic of Panama in the 1999-2022 period Heliyon ODE PSO SIR SEIR SIR-SI R0 |
| title | Using compartmental models and Particle Swarm Optimization to assess Dengue basic reproduction number R0 for the Republic of Panama in the 1999-2022 period |
| title_full | Using compartmental models and Particle Swarm Optimization to assess Dengue basic reproduction number R0 for the Republic of Panama in the 1999-2022 period |
| title_fullStr | Using compartmental models and Particle Swarm Optimization to assess Dengue basic reproduction number R0 for the Republic of Panama in the 1999-2022 period |
| title_full_unstemmed | Using compartmental models and Particle Swarm Optimization to assess Dengue basic reproduction number R0 for the Republic of Panama in the 1999-2022 period |
| title_short | Using compartmental models and Particle Swarm Optimization to assess Dengue basic reproduction number R0 for the Republic of Panama in the 1999-2022 period |
| title_sort | using compartmental models and particle swarm optimization to assess dengue basic reproduction number r0 for the republic of panama in the 1999 2022 period |
| topic | ODE PSO SIR SEIR SIR-SI R0 |
| url | http://www.sciencedirect.com/science/article/pii/S2405844023026312 |
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