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October 13, 2025Open Access

Bayesian spatio-temporal modelling for infectious disease outbreak detection

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This methodology detects disease outbreaks in structured populations, highlighting the relevance of spatio-temporal modeling.

New Bayesian spatio-temporal models successfully detect infectious disease outbreaks across multiple regions and timeframes.
The methodology integrates dynamic Hamiltonian Monte Carlo and improves upon previous models, outperforming them in accuracy.
Systematic simulation studies validate the model, demonstrating effective outbreak detection and strong reliability in model comparison.
Application to invasive meningococcal disease incidence data from 28 countries reveals significant outbreaks across various months.

Adeoye et al. (2025) studied this question.

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