Introduction
The Monkeypox (Mpox) epidemic has revitalized the use of epidemiological models to predict and mitigate the spread of infectious diseases. This study proposes an extension of the Susceptible-Exposed-Infectious-Recovered (SEIR) model, integrating vital dynamics such as birth and death rates, to more realistically assess the dynamics of infection and epidemic control in the United States. This improved model aims to provide a detailed understanding of transmission patterns, infection peaks, and intervention strategies.
Methodology
Primary data on Monkeypox cases were collected from a public global health repository, focusing on the US context due to the comprehensiveness of its database. Data were processed using Python scripts, with rigorous cleaning steps including interpolation to fill in missing values, duplicate elimination, and selection of relevant variables such as date, location, new cases, and cumulative totals.
The SEIR model was mathematically formulated as a system of coupled differential equations representing the transitions between population compartments (Susceptible, Exposed, Infectious, and Recovered). Parameters such as transmission rate (β), rate of progression from exposure to infection (σ), and recovery rate (γ) were estimated through nonlinear least squares fitting and sensitivity analysis. The model was implemented and optimized in Python, using Gaussian filters to smooth out irregularities in the data and refine parameters to accurately represent the epidemic curve.
Results
The results highlighted that the inclusion of vital dynamics in the SEIR model increases the accuracy in predicting infection patterns, considering changes in the population over time. Simulations indicated that measures such as vaccination and isolation are essential to control the epidemic in the long term. The transmission rate (β) was identified as one of the most sensitive parameters, with a significant impact on the trajectory of the outbreak. The analysis revealed the importance of early interventions to mitigate the spread and reduce the burden of the disease in the population.
Discussion
The refined modeling has proven effective in simulating a variety of scenarios, allowing the evaluation of public health strategies such as large-scale vaccination campaigns and quarantine measures. The vital dynamics included in the model are particularly relevant for long-term epidemics, highlighting the need for adaptive strategies based on epidemiological and demographic data.
Reference :
RODRIGUES, F. de AA; JIN-YON BRYNE, T. Modeling the monkeypox outbreak with the refined SEIR model including vital dynamics for the US. Journal of Bioinnovation, v. 14, no. 1, p. 85–98, 2025. DOI: https://doi.org/10.46344/JBINO.2025.v14i01.05.
