Authors
Avik Kumar Sam, Ujjal Gogoi, Ananta Maji, Arup Borgohain, Rocky Pebam, Tarun Bhatnagar, Keshab Barman, Supriya Chaudhuri, Kalpana Baruah, Harish C Phuleria, Ipsita Pal Bhowmick
Published in
One health (Amsterdam, Netherlands). Volume 23. Pages 101538. Epub Aug 19, 2026.
Abstract
Despite the progress made, malaria continues to impose a major global and regional burden. India contributes to almost half of the malaria cases in South-East Asia. In 2024, an unusual increase in malaria cases was observed in Alipurduar and neighbouring Kokrajhar district in Northeast India; regions that had maintained an API below 1 for several years. Thus, understanding the climatic and environmental factors of this outbreak is critical for early detection and prevention.
Monthly epidemiological data on confirmed malaria cases in both districts were analysed from 2018 to 2024 along with meteorological variables and El Niño-Southern Oscillation indices. Multiple Poisson regression models incorporating lagged climatic parameters were developed separately and assessed using the RMSE for out-of-sample prediction performance.
The marked increase in malaria cases observed between August and December 2024 in both districts was primarily driven by Plasmodium vivax infections (∼95% cases in Alipurduar). The models showed no heteroscedasticity (p > 0.05) and captured the outbreak trend well in both districts. The lagged temperature was identified as a common significant predictor variable in both districts, with a delayed effect of 2-3 months. Precipitation was negatively associated with malaria in both districts, with a 1-month lagged impact in Alipurduar and none in Kokrajhar. The non-transferability of the models confirms a differential impact of weather variables, along with local vector dynamics, and an independent, indirect effect modification of El Niño conditions on the reported malaria cases in both districts.
The lagged temperature increase associated with El Niño-driven climatic anomalies exerted a strong influence on the 2024 malaria outbreaks in Alipurduar and Kokrajhar. These results emphasise the role of integrating ENSO-based forecasting within malaria in early-warning systems. Early, climate-informed surveillance and planning for vector control would prevent localized resurgence and sustain malaria elimination gains, especially in low-API districts.
PMID:
42701675
Bibliographic data and abstract were imported from PubMed on 06 Sep 2026.
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