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Hybrid Model Of Climate Effects On Dengue Forecast And Control In Selangor, Malaysia

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dc.contributor.authorLu, Xinyi
dc.date.accessioned2026-05-06T06:34:20Z
dc.date.available2026-05-06T06:34:20Z
dc.date.issued2025-07
dc.description.abstractExisting dengue forecasting approaches in Malaysia are constrained by two main limitations: deterministic models typically assume a constant mosquito biting rate, neglecting its climate-driven variability, while statistical time series models are usually effective only for short-term forecasts. These constraints hinder the accurate prediction of outbreak dynamics and limit the utility of earlywarning systems. This study develops two integrated approaches: (i) coupled Susceptible-Infective for vector populations and Susceptible-Infective-Recovered for human populations (SI-SIR) and Autoregressive Integrated Moving Average with eXogenous variables (ARIMAX) model, and (ii) SISIR with Multiple Linear Regression and Long Short-Term Memory (MLR-LSTM) model.
dc.identifier.urihttps://erepo.usm.my/handle/123456789/24116
dc.language.isoen
dc.subjectDengue--Selangor (Malaysia)
dc.subjectMathematical models
dc.titleHybrid Model Of Climate Effects On Dengue Forecast And Control In Selangor, Malaysia
dc.typeResource Types::text::thesis::doctoral thesis
dspace.entity.typePublication
oairecerif.author.affiliationUniversiti Sains Malaysia
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Pusat Pengajian Sains Matematik - Tesis