TY - JOUR
T1 - Using compartmental models and Particle Swarm Optimization to assess Dengue basic reproduction number R0 for the Republic of Panama in the 1999-2022 period
AU - Navarro Valencia, Vicente Alonso
AU - Díaz, Yamilka
AU - Pascale, Jose Miguel
AU - Boni, Maciej F.
AU - Sanchez-Galan, Javier E.
N1 - Funding Information:
V.N. was supported by a scholarship of the Programa de Fortalecimiento de los Postgrados Nacionales from the National Secretariat for Science, Technology and Innovation (SENACYT-Panama). The Sistema Nacional de Investigación (SNI) of SENACYT-Panama supports research activities by J.M.P. and J.E.S.-G. (SNI 18-2022).
Funding Information:
V.N. was supported by a scholarship of the Programa de Fortalecimiento de los Postgrados Nacionales from the National Secretariat for Science, Technology and Innovation ( SENACYT -Panama). The Sistema Nacional de Investigación (SNI) of SENACYT -Panama supports research activities by J.M.P. and J.E.S.-G. ( SNI 18-2022 ).
Publisher Copyright:
© 2023 The Author(s)
PY - 2023/4
Y1 - 2023/4
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85152733418&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85152733418&partnerID=8YFLogxK
U2 - 10.1016/j.heliyon.2023.e15424
DO - 10.1016/j.heliyon.2023.e15424
M3 - Article
C2 - 37128312
AN - SCOPUS:85152733418
SN - 2405-8440
VL - 9
JO - Heliyon
JF - Heliyon
IS - 4
M1 - e15424
ER -
