One health (Amsterdam, Netherlands) · 2026
Climatic drivers of the 2024 malaria outbreak in two neighbouring districts in northeastern India and its corridor: The indirect role of El Niño.
СтатьяНазвание и аннотация: Перевод в очереди
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Sam Avik Kumar, Gogoi Ujjal, Maji Ananta, Borgohain Arup, Pebam Rocky, Bhatnagar Tarun, Barman Keshab, Chaudhuri Supriya, Baruah Kalpana, Phuleria Harish C, Bhowmick Ipsita Pal
Аннотация
BACKGROUND: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSION: 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.
METHODS: 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.
RESULTS: 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.
CONCLUSION: 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.