Using compartmental models and Particle Swarm Optimization to assess Dengue basic reproduction number R 0 for the Republic of Panama in the 1999-2022 period

Vicente Alonso Navarro Valencia; Yamilka Díaz; Jose Miguel Pascale; Maciej F Boni; Javier E Sanchez-Galan

doi:10.1016/j.heliyon.2023.e15424

Using compartmental models and Particle Swarm Optimization to assess Dengue basic reproduction number R ₀ for the Republic of Panama in the 1999-2022 period

Heliyon. 2023 Apr 13;9(4):e15424. doi: 10.1016/j.heliyon.2023.e15424. eCollection 2023 Apr.

Authors

Vicente Alonso Navarro Valencia¹, Yamilka Díaz², Jose Miguel Pascale^{3

4}, Maciej F Boni⁵, Javier E Sanchez-Galan^{6

4}

Affiliations

¹ Facultad de Ciencias y Tecnología, Universidad Tecnológica de Panamá, Campus Victor Levi Sasso, Panama, Panama.
² Department of Research in Virology and Biotechnology, Gorgas Memorial Institute of Health Studies, Panama, Panama.
³ Unit of Diagnosis, Clinical Research and Tropical Medicine, Gorgas Memorial Institute of Health Studies, Panama, Panama.
⁴ Sistema Nacional de Investigación, SENACYT, Ciudad del Saber, Panama, Panama.
⁵ Center for Infectious Disease Dynamics, Department of Biology, Pennsylvania State University, University Park, USA.
⁶ Grupo 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.

Abstract

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, $R_{0}$ , 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 $R_{0}$ estimates ranging from 1.09 to 1.74. This study provides, to the best of our understanding, the first calculation of $R_{0}$ for Dengue outbreaks in the Republic of Panama.

Keywords: Dengue; ODE; PSO; Panama; R0; SEIR; SIR; SIR-SI.