Article

Inferring unobserved vector dynamics for dengue forecasting using physics-informed neural networks and mechanistic transmission models

2026-02-14

Abstract excerpt

Accurately characterising mosquito infection dynamics is essential for effective dengue prevention and control, yet these dynamics are rarely observable through routine surveillance. Here, we integrate a reduced SI-SIR transmission model with monthly dengue incidence data using physics-informed neural networks (PINNs) to develop a Dengue-Informed Neural Network (DINN). The DINN simultaneously fits reported dengue...

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Literature Corpus work: 79d840a2-fa6e-5d8b-94f7-c6eea2faf4aa
DOI: 10.64898/2026.02.13.705693

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