Potential impact of climatic variability on the epidemiology of dengue in Risaralda, Colombia, 2010-2011
- Liseth L. Quintero-Herrera,
- Valeria Ramírez-Jaramillo,
- Sergio Bernal-Gutiérrez,
- Erika V. Cárdenas-Giraldo,
- Edwin A. Guerrero-Matituy,
- Anderson H. Molina-Delgado
- Universidad Tecnológica de Pereira,
- Vector-Borne Diseases Control Program,
- Asociación Colombiana de Infectología,
- Fundación Cenit Colombia
Open access
Publication Information
Output type
Original language
EnglishPages from-to (Number of pages)
Pages 291-297 (7 pages)Journal (Volume, Issue Number)
Journal of Infection and Public Health (Volume 8, Issue 3)Publication milestones
- Published - 01/05/2015
Publication status
ISSN
1876-0341Publication IDs
- Scopus: 84928388882
- PubMed: 25564418
Abstract
Dengue continues to be the most important viral vector-borne disease in the world, particularly in Asia and Latin America, and is significantly affected by climate variability. The influence of climate in an endemic region of Colombia, from 2010 to 2011, was assessed. Epidemiological surveillance data (weekly cases) were collected, and incidence rates were calculated. Poisson regression models were used to assess the influence of the macroclimatic variable ONI (Oscillation Niño Index) and the microclimatic variable pluviometry (mm of rain for Risaralda) on the dengue incidence rate, adjusting by year and week. During the study period, 13,650 cases were reported. In 2010, the rates ranged from 8.6 cases/100,000 pop. up to a peak of 75.3 cases/100,000 pop. for a cumulative rate of 456.2 cases/100,000 pop. in that week. The climate variability in 2010 was higher (ONI 1.6, El Niño to -1.5, La Niña) than in 2011 (ONI -1.4, La Niña to -0.2, Neutral). The mean pluviometry was 248.45mm (min 135.9-max 432.84). During El Niño, cases were significantly higher (mean 433.81) than during the climate neutral period (142.48) and during the La Niña (52.80) phases (ANOVA F=66.59; p<0.001). Regression models showed that the ONI (coefficient 0.329; 95%CI 0.209-0.450) and pluviometry (coefficient 0.003; 95%CI 0.002-0.004) were highly significant independent variables associated with dengue incidence rate, after adjusting by year and week (p<0.001, pseudo r2=0.6913). El Niño significantly affected the incidence of dengue in Risaralda. This association with climate change and variability should be considered in the elements influencing disease epidemiology. In addition, predictive models should be developed further with more available data from disease surveillance.
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Sustainable Development Goals
- SDG 3 Good Health and Well
- SDG 13 Climate Action
