Dataset for climate-driven LSTM-SIR Modeling of dengue transmission in Guangdong, China (2016-2024)

This dataset contains the processed time-series data used to drive and validate the LSTM - SIR hybrid model in a study on dengue transmission dynamics. It comprises monthly dengue case counts and aggregated daily meteorological variables(maximum, mean, and minimum temperature, precipitation, and relative humidity) at the provincial level for Guangdong, China, along with quantified indicators of non-pharmaceutical intervention (NPI) intensity. The collection further incorporates semi - monthly Aedes mosquito surveillance data and corresponding daily meteorological variables from ten prefecture - level cities in the Province.