A serotype-specific compartmental dengue model incorporating temperature effect

Seminario periodico del Dipartimento di Matematica
16 luglio 2024
Orario di inizio 
Polo Ferrari 1 - Via Sommarive 5, Povo (Trento)
Aula A108
Organizzato da: 
MBM Lab - Dipartimento di Matematica
Comunità universitaria
Comunità studentesca UniTrento
Ingresso libero
Andrea Pugliese e Cinzia Soresina
Università degli Studi Trento 38123 Povo (TN) - Staff Dipartimento di Matematica
+39 0461/281508-1625-1701-3898-1980
Yiran Wang (Imperial College London)


Background: As the most prevalent arboviral disease, dengue imposes a significant burden on global health. However, compartmental models that investigate the serotype-specific dynamics and temperature dependencies of dengue transmission, particularly those using inferential frameworks to calibrate parameters and reconstruct observed data, have not been fully established due to computational challenges associated with its complex transmission system. This hinders reliable estimates of epidemiological parameters, which are crucial for effective dengue control in the context of climate change.

Methods: To address this research gap, we developed a four-strain dengue model that incorporates serotype interactions, including the antibody-dependent enhancement (ADE) effect and the temporary cross-immunity (TCI). The temperature effect is integrated into the model using a Brière function to represent the time-varying transmission rate. Using Bayesian inference and Markov Chain Monte Carlo
methods, we calibrated the model to 10-year time-series serotype-specific case data simulated using daily temperature profiles from different dengue-endemic countries. The model's ability to reconstruct simulated case counts and actual parameter values was assessed through posterior predictive checks.

Results: This model is able to reproduce dengue dynamics simulated under multiple temperature profiles and accurately reconstruct the initial conditions of the compartments, as well as serotype-interaction and temperature-dependent parameters.

Significance: This model can be fitted to the real-world dengue serotype-specific case data to understand the location-specific effects of serotype interactions and temperature on dengue transmission dynamics. Such insights are essential for predicting dengue transmission patterns in both the short and long term under changing climate conditions.