Dengue dynamics, predictions, and future increase under changing monsoon climate in India

Area of Science:

• Environmental Science
• Public Health
• Epidemiology

Background:

• Global dengue burden is increasing, with India facing a significant share.
• Climate change exacerbates dengue transmission, but non-linear relationships and data gaps hinder accurate predictions.
• Pune, India, a dengue hotspot, experiences monsoonal climate patterns influencing disease dynamics.

Purpose of the Study:

• To investigate the non-linear relationship between climate variables and dengue mortality in Pune.
• To develop a predictive model for near-term and future dengue mortality.
• To project future dengue mortality trends under climate change scenarios.

Main Methods:

• Analysis of twelve-year dengue mortality and meteorological data (2004-2015) using statistical and machine learning techniques.
• Development of a random forest regression model to forecast dengue mortality.
• Integration of climate change simulations (CMIP6) for future projections.

Main Results:

• Temperature, rainfall, and relative humidity significantly influence dengue mortality with a 2-5 month lag.
• Moderate monsoon rains increase, while heavy rains decrease dengue mortality.
• Machine learning model achieved a correlation of r=0.77 and NMSE of 0.52 for a two-month lead time.
• Temperature (41%), rainfall (39%), and humidity (20%) are key predictors of dengue mortality in Pune.
• Projected increases in dengue mortality by 13% (near future), 23-40% (mid-century), and 30-112% (late century).

Conclusions:

• Established significant climate-dengue mortality links in Pune, enabling early warning systems.
• The developed model accurately predicts dengue mortality with a two-month lead time.
• Climate change is projected to substantially increase dengue mortality in Pune, necessitating adaptive public health strategies.