Epidemiology of Dengue Virus Infection in Different Geopolitical Zones of Odisha in Relation to Climatic Variation: An Observational Study.

Authors

Sailendra Panda, Gayatri Patra, Debasmita S Mishra, Birendra K Bindhani, Bhagirathi Dwibedi

Published in

Indian journal of community medicine : official publication of Indian Association of Preventive & Social Medicine. Volume 51. Issue Suppl 4. Pages S669-S676. Epub Aug 17, 2026.

Abstract

Dengue is a major and expanding public health problem in India, with increasing case numbers and geographic spread. Climatic factors, particularly temperature and rainfall, play an important role in its transmission dynamics.
To analyze epidemiological trends and the association of climatic variables with dengue across different geopolitical zones of Odisha during 2012-2016.
This multi-center retrospective observational study was based on passive surveillance, supplemented by active case finding, and conducted across selected healthcare facilities in Odisha between January 2012 and December 2016. A total of 4,325 patients with dengue-like illness were enrolled. Laboratory confirmation was performed using serological and molecular methods. Monthly climatic data were obtained from meteorological sources, and associations with dengue cases were assessed using Spearman correlation with a 1-month lag analysis.
Of 4,325 cases, 2,212 (51.14%) were laboratory confirmed. Adults aged ≥ 20 years and males were more commonly affected. Dengue cases demonstrated a clear seasonal pattern, peaking during August to October. Rainfall showed a strong positive correlation with dengue cases (ρ =0.66, P < 0.01), which increased with a one-month lag (ρ =0.72, P < 0.01). Temperature exhibited a moderate positive association (ρ =0.44, P < 0.05), with higher transmission observed between 27 and 34°C. The Western and Mid-Central Tableland reported the highest number of cases, followed by the Coastal Plains.
Dengue transmission in Odisha shows marked spatial and temporal variation influenced by climatic factors. Rainfall, particularly with a lag effect, is strongly associated with dengue cases. Integration of climatic data into surveillance systems may support early warning and targeted interventions.

PMID:
42699963
Bibliographic data and abstract were imported from PubMed on 06 Sep 2026.

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