Keralam dengue risk may rise 20% by 2040 as climate change shifts monsoon: IITM study

Dengue in Keralam follows a sharply seasonal pattern, and a changing climate could make outbreaks more frequent and more intense, according to a study by the Centre for Climate Change Research at the Indian Institute of Tropical Meteorology (IITM), Pune.

The study, titled 'Climate-informed dengue prediction and future risks under a changing monsoon climate in Keralam', found that nearly 60% of the State's dengue cases are reported during the southwest monsoon, from June to September, closely mirroring the State's rainfall cycle. Case numbers begin to climb in May and peak in June and July. It was published in GeoHealth, a peer-reviewed, open-access journal.

The research was carried out with experts from the Department of Atmospheric and Space Sciences at Savitribai Phule Pune University; the ICMR-National Institute of Translational Virology and AIDS Research, Pune; the School of Public Health at the Kerala University of Health Sciences (KUHS); Government Medical College, Thrissur; and KUHS.

Rainfall, humidity and the El Niño-Southern Oscillation (ENSO) — a recurring shift in Pacific Ocean temperatures that influences weather worldwide, including India's monsoon — were identified as the main drivers of transmission. Locally, warmer pre-monsoon temperatures of 30.5°C to 32.5°C, moderate humidity of 66% to 79%, and monthly monsoon rainfall of about 180 mm to 450 mm were found to favour higher dengue incidence.

Simulations using different machine-learning models suggest that dengue risk in Keralam could rise by 16% to 20% during 2021-2040, and by up to 113% by 2081-2100 under low- to high-emission pathways. Such projections depend on the emissions trajectory the world follows, the assumptions built into each model and the quality of available data. They are intended to guide long-term planning rather than to predict a fixed number of cases.

The inclusion of ENSO as a predictor is a key contribution of the study, the authors say. Both El Niño and La Niña were found to influence dengue risk through their regional climate effects, though La Niña events — generally associated with cooler and wetter conditions — were linked to relatively lower risk than El Niño.

Climate scientist Roxy Mathew Koll of IITM, Pune, who led the study, said the model can identify the peak and weaker phases of transmission more accurately when high-resolution climate and epidemiological data are available. Block-level data matter in Keralam, he said, because maritime and orographic influences, monsoon rainfall and its active and break phases vary across the State. The southwest monsoon, for instance, is usually stronger in the northern districts, while the southern districts receive more intense rainfall during the northeast monsoon. Changes in atmospheric pressure, temperature and relative humidity during active and break phases can affect local mosquito breeding.

Post-monsoon dengue also varied considerably from year to year, possibly reflecting differences in how monsoon rainfall is distributed across the State.

The researchers cautioned that such projections carry uncertainties. Changes in circulating dengue virus strains could trigger sudden surges in cases, while future deployment of vaccines still under development could substantially reduce risk. The model, they said, could be strengthened through better disease surveillance, improved representation of vector biology and socio-demographic factors, and continuous validation. Even so, it showed reasonable forecasting accuracy and offered region-specific insights.

Dengue is transmitted by Aedes mosquitoes, which breed in stagnant water and are sensitive to temperature and rainfall. Early warnings that flag when and where risk is likely to rise can help health authorities time vector-control measures, such as clearing breeding sites and fogging, and prepare hospitals for a surge in patients.

Mr. Koll said the same modelling approach could potentially be extended to other vector-borne diseases by including detailed temperature, rainfall and epidemiological data.