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Dengue dynamics in India: Harnessing auto regressive integrated moving average model for predictive insights
Sashikanta Tripathy1, Amit Kumar Mishra1, Manisha Ruikar1
1Department of Community and Family Medicine, All India Institute of Medical Sciences, Raipur, Chhattisgarh, India.
Background:
Dengue, a mosquito-borne viral disease caused by the Dengue virus (DENV), poses a significant threat to global health. Nearly half of the world's population is at risk, with an estimated 100-400 million infections annually. South East Asian countries, including India, are particularly vulnerable due to their temperate climate and changing environmental conditions, leading to a rise in Dengue cases every year.
Objectives:
The current study was done to analyse the trend of Dengue in India and to forecast Dengue cases and deaths in India.
Methods:
The study employed a time series analysis approach, collecting Dengue data from 1999 to 2023 from the National Health Profile and NVBCDCP. Gretl software was used to develop an appropriate ARIMA (Auto Regressive Integrated Moving Average) model based on the available data to forecast Dengue cases and deaths. The model was checked for stationarity and used to predict Dengue cases and deaths for the next 3 years (2024-2026).
Results:
The analysis revealed an increasing trend in Dengue cases and deaths in India over the study period. The forecasted data for 2024-2026 also indicate a continued rise in both cases and deaths. The projected Dengue cases for 2026 are 309,836 (95% CI; 240,337-379,334), while the projected deaths are 533 (95% CI; 285-781).
Conclusion:
The increasing trend in Dengue burden highlights the urgent need for targeted interventions to mitigate the public health impact. Hence, it is recommended that the policymakers and health authorities must prioritize the planning and implementation of effective preventive measures to curb the increasing trend of Dengue in India.
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