Dual-Model Framework for CHIKV Transmission Modeling: ODE and Petri Net Analysis of the 2025 Foshan Outbreak

TL;DR

This paper introduces a dual-model framework combining ODEs and Petri Nets to analyze the 2025 Foshan CHIKV outbreak, demonstrating high accuracy and providing insights into intervention effects and transmission dynamics.

Contribution

It presents the first systematic comparison of ODE and Petri Net models for vector-borne diseases, offering a novel dual-model approach for epidemic analysis.

Findings

Models predicted epidemic peak 3 days early with 6% error.

Reproduction number decreased to near zero after interventions.

Recovery rate was identified as the most sensitive parameter.

Abstract

This study constructs a dual-model framework integrating Ordinary Differential Equations (ODE) and Petri Nets (PN) to analyze the 2025 Chikungunya outbreak in Foshan City, China. We employ SEICR compartmental modeling to compare two distinct approaches under identical epidemiological scenarios and evaluate intervention effectiveness through three-phase fitting protocols. Both models demonstrate excellent accuracy with MAE of 18.77-18.91 cases and RMSE of 36.52-36.54 cases. Models predicted epidemic peaks at day 32 (406 cases), 3 days earlier than observed (day 35, 432 cases), with 6.0% peak value error. Reproduction number analysis revealed initial R0 of 14.67 (ODE)/13.90 (PN), with effective reproduction numbers decreasing through intervention phases: 7.85/7.86 after Phase 1, 7.59/7.56 after Phase 2, and 0.059 in Phase 3, achieving transmission blockade. Sensitivity analysis showed recovery rate) as the most sensitive parameter (Sobol index 0.9672), explaining 96.72% of R0 variation. This study presents the first systematic ODE-Petri Net comparison, providing a novel dual-model framework for vector-borne disease modeling with significant theoretical and practical value for epidemic control strategy formulation.