An adjoint-based gradient descent method optimizes the timing of multiple dengue vector control interventions by minimizing a time-dependent reproduction number in a non-Markovian Aedes life-cycle model driven by Miami temperature data.
Machine learning algorithms for dengue risk assessment: a case study for s ˜ao lu´ıs do maranh˜ao: Fp rocha, m. giesbrecht
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Optimal Scheduling of Dengue Vector Control
An adjoint-based gradient descent method optimizes the timing of multiple dengue vector control interventions by minimizing a time-dependent reproduction number in a non-Markovian Aedes life-cycle model driven by Miami temperature data.