Evidence map›Paper›PMID 40256073›Full record

ArticleJournal of family medicine and primary care2025

Dengue dynamics in India: Harnessing auto regressive integrated moving average model for predictive insights.

Sashikanta Tripathy, Amit Kumar Mishra, Manisha Ruikar

Abstract read
In one paragraph

Article in Journal of family medicine and primary care, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Sashikanta TripathyDepartment of Community and Family Medicine, All India Institute of Medical Sciences, Raipur, Chhattisgarh, India.
Amit Kumar MishraDepartment of Community and Family Medicine, All India Institute of Medical Sciences, Raipur, Chhattisgarh, India.
Manisha RuikarDepartment of Community and Family Medicine, All India Institute of Medical Sciences, Raipur, Chhattisgarh, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

ARIMAcasesdeathsdengueforecasting

Identifiers

PMID40256073
PMCPMC12007755

What OpenQuestion holds

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LicenceCC BY-NC-SA
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.