Dengue dynamics, predictions, and future increase under changing monsoon climate in India
Abstract The global burden of dengue disease is escalating under the influence of climate change, with India contributing a third of the total. The non-linearity and regional heterogeneity inherent in the climate-dengue relationship and the lack of consistent data makes it difficult to make useful p...
Saved in:
| Main Authors: | , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-01-01
|
| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-025-85437-w |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832585726156341248 |
|---|---|
| author | Yacob Sophia Mathew Koll Roxy Raghu Murtugudde Anand Karipot Amir Sapkota Panini Dasgupta Kalpana Baliwant Sujata Saunik Abhiyant Tiwari Rajib Chattopadhyay Revati K. Phalkey |
| author_facet | Yacob Sophia Mathew Koll Roxy Raghu Murtugudde Anand Karipot Amir Sapkota Panini Dasgupta Kalpana Baliwant Sujata Saunik Abhiyant Tiwari Rajib Chattopadhyay Revati K. Phalkey |
| author_sort | Yacob Sophia |
| collection | DOAJ |
| description | Abstract The global burden of dengue disease is escalating under the influence of climate change, with India contributing a third of the total. The non-linearity and regional heterogeneity inherent in the climate-dengue relationship and the lack of consistent data makes it difficult to make useful predictions for effective disease prevention. The current study investigates these non-linear climate-dengue links in Pune, a dengue hotspot region in India with a monsoonal climate and presents a model framework for predicting both the near-term and future dengue mortalities. Dengue mortality and meteorological conditions over a twelve-year period (2004–2015) are analyzed using statistical tools and machine learning methods. Our findings point to a significant influence of temperature, rainfall, and relative humidity on dengue mortality in Pune, at a time-lag of 2–5 months, providing sufficient lead time for an early warning targeted at curbing dengue outbreaks. We find that moderate rains spread over the summer monsoon season lead to an increase in dengue mortality, whereas heavy rains reduce it through the flushing effect, indicating the links between dengue and monsoon intraseasonal variability. Additionally, warm temperatures above 27°C and humidity levels between 60% and 78% elevate the risk of dengue. Based on these weather-dengue associations, we developed a machine-learning model utilizing the random forest regression algorithm. The dengue model yields a skillful forecast, achieving a statistically significant correlation coefficient of r = 0.77 and a relatively low Normalized Root Mean Squared Error score of 0.52 between actual and predicted dengue mortalities, at a lead time of two months. The model finds that the relative contributions of temperature, rainfall, and relative humidity to dengue mortality in Pune are 41%, 39%, and 20%, respectively. We use the dengue model in conjunction with the climate change simulations from the Coupled Model Intercomparison Project phase 6 for the future dengue mortality projections under a global warming scenario. In a changing climate, dengue-related mortality in Pune is projected to rise by 13% in the near future (2021–2040), 23–40% in the mid-century (2041–2060), and 30–112% in the late century (2081–2100) under low-to-high emission pathways in response to the associated increase in temperature and changes in monsoon rainfall patterns. |
| format | Article |
| id | doaj-art-95e5718965cd41598884b75977de07ce |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-95e5718965cd41598884b75977de07ce2025-01-26T12:32:29ZengNature PortfolioScientific Reports2045-23222025-01-0115111610.1038/s41598-025-85437-wDengue dynamics, predictions, and future increase under changing monsoon climate in IndiaYacob Sophia0Mathew Koll Roxy1Raghu Murtugudde2Anand Karipot3Amir Sapkota4Panini Dasgupta5Kalpana Baliwant6Sujata Saunik7Abhiyant Tiwari8Rajib Chattopadhyay9Revati K. Phalkey10Centre for Climate Change Research, Indian Institute of Tropical Meteorology, Ministry of Earth SciencesCentre for Climate Change Research, Indian Institute of Tropical Meteorology, Ministry of Earth SciencesEarth System Science Interdisciplinary Center (ESSIC)/DOAS, University of MarylandDepartment of Atmospheric and Space Sciences, Savitribai Phule Pune UniversityDepartment of Epidemiology and Biostatistics, School of Public Health, University of MarylandFuture Innovation Institute, Seoul National UniversityHealth Department, Pune Municipal CorporationHarvard TH Chan School of Public HealthNatural Resources Defense CouncilCentre for Climate Change Research, Indian Institute of Tropical Meteorology, Ministry of Earth SciencesHeidelberg Institute of Global Health, University of HeidelbergAbstract The global burden of dengue disease is escalating under the influence of climate change, with India contributing a third of the total. The non-linearity and regional heterogeneity inherent in the climate-dengue relationship and the lack of consistent data makes it difficult to make useful predictions for effective disease prevention. The current study investigates these non-linear climate-dengue links in Pune, a dengue hotspot region in India with a monsoonal climate and presents a model framework for predicting both the near-term and future dengue mortalities. Dengue mortality and meteorological conditions over a twelve-year period (2004–2015) are analyzed using statistical tools and machine learning methods. Our findings point to a significant influence of temperature, rainfall, and relative humidity on dengue mortality in Pune, at a time-lag of 2–5 months, providing sufficient lead time for an early warning targeted at curbing dengue outbreaks. We find that moderate rains spread over the summer monsoon season lead to an increase in dengue mortality, whereas heavy rains reduce it through the flushing effect, indicating the links between dengue and monsoon intraseasonal variability. Additionally, warm temperatures above 27°C and humidity levels between 60% and 78% elevate the risk of dengue. Based on these weather-dengue associations, we developed a machine-learning model utilizing the random forest regression algorithm. The dengue model yields a skillful forecast, achieving a statistically significant correlation coefficient of r = 0.77 and a relatively low Normalized Root Mean Squared Error score of 0.52 between actual and predicted dengue mortalities, at a lead time of two months. The model finds that the relative contributions of temperature, rainfall, and relative humidity to dengue mortality in Pune are 41%, 39%, and 20%, respectively. We use the dengue model in conjunction with the climate change simulations from the Coupled Model Intercomparison Project phase 6 for the future dengue mortality projections under a global warming scenario. In a changing climate, dengue-related mortality in Pune is projected to rise by 13% in the near future (2021–2040), 23–40% in the mid-century (2041–2060), and 30–112% in the late century (2081–2100) under low-to-high emission pathways in response to the associated increase in temperature and changes in monsoon rainfall patterns.https://doi.org/10.1038/s41598-025-85437-w |
| spellingShingle | Yacob Sophia Mathew Koll Roxy Raghu Murtugudde Anand Karipot Amir Sapkota Panini Dasgupta Kalpana Baliwant Sujata Saunik Abhiyant Tiwari Rajib Chattopadhyay Revati K. Phalkey Dengue dynamics, predictions, and future increase under changing monsoon climate in India Scientific Reports |
| title | Dengue dynamics, predictions, and future increase under changing monsoon climate in India |
| title_full | Dengue dynamics, predictions, and future increase under changing monsoon climate in India |
| title_fullStr | Dengue dynamics, predictions, and future increase under changing monsoon climate in India |
| title_full_unstemmed | Dengue dynamics, predictions, and future increase under changing monsoon climate in India |
| title_short | Dengue dynamics, predictions, and future increase under changing monsoon climate in India |
| title_sort | dengue dynamics predictions and future increase under changing monsoon climate in india |
| url | https://doi.org/10.1038/s41598-025-85437-w |
| work_keys_str_mv | AT yacobsophia denguedynamicspredictionsandfutureincreaseunderchangingmonsoonclimateinindia AT mathewkollroxy denguedynamicspredictionsandfutureincreaseunderchangingmonsoonclimateinindia AT raghumurtugudde denguedynamicspredictionsandfutureincreaseunderchangingmonsoonclimateinindia AT anandkaripot denguedynamicspredictionsandfutureincreaseunderchangingmonsoonclimateinindia AT amirsapkota denguedynamicspredictionsandfutureincreaseunderchangingmonsoonclimateinindia AT paninidasgupta denguedynamicspredictionsandfutureincreaseunderchangingmonsoonclimateinindia AT kalpanabaliwant denguedynamicspredictionsandfutureincreaseunderchangingmonsoonclimateinindia AT sujatasaunik denguedynamicspredictionsandfutureincreaseunderchangingmonsoonclimateinindia AT abhiyanttiwari denguedynamicspredictionsandfutureincreaseunderchangingmonsoonclimateinindia AT rajibchattopadhyay denguedynamicspredictionsandfutureincreaseunderchangingmonsoonclimateinindia AT revatikphalkey denguedynamicspredictionsandfutureincreaseunderchangingmonsoonclimateinindia |