Lessons learned of emerging Chikungunya virus in two populations of social vulnerability of the Colombian tropics: epidemiological analysis

• Main Authors: Misael Oviedo-Pastrana, Nelson Méndez, Salim Mattar, Germán Arrieta, Luty Gomezcaceres
• Format: Article
• Language: English
• Published: BMC 2018-07-01
• Series: Archives of Public Health
• Subjects: Epidemiology; Public health systems; Cullicidae
• Online Access: http://link.springer.com/article/10.1186/s13690-018-0284-2

Abstract Background Notwithstanding the strong epidemiological impact of the Chikungunya in the Colombian Caribbean, in 2014, not the entire population were affected in the same way. This study describe the demographic, socio-economic, clinical and epidemiological aspects of the de Chikungunya in Ovejas and Corozal, two neighboring municipalities with high vulnerability in health in the Colombian Caribbean. Methods A cross-sectional study was performed in February 2015. A convenience sampling was carried out in 971 families affected with chikungunya. Also, a socio-demographics, clinical and epidemiological questionnaire was carried out for people who met the definition of suspected Chikungunya clinical case. For the statistical analysis, data and variables, frequencies, proportions and means were compared in the two municipalities studied. A logistic regression model was constructed to explain the effect of factors studied on the risk of family infection (RFI) or likelihood of contagion within each household. Was used the software EpiInfo 7.2.2.2 and a significance level with p-value < 0.05. Results In Ovejas, 516 households were affected by Chikungunya, 48% (1269/2631) of their inhabitants became sick; in Corozal, 455 families were affected and 42% (839/1999) of their members became sick. The evolution of the epidemic curves of Chikungunya outbreak was different in the two studied areas, the disease was more aggressive in Ovejas. Ten variables were pre-selected by univariate analysis to explain the RFI by Chikungunya, and were integrated into a logistic regression model. The final model was constructed with the following variables: municipality, gender, occupation, family income, use of repellent and fumigation. The logistic model was assessed as appropriate; however, the biases in the selection of the surveyed dwellings and in the selection of symptomatic patients could influence the results. Conclusions It was demonstrated the epidemiological complexity of Chikungunya and the serious problem caused in populations with high vulnerability in health. The accurate association observed in the logistic regression model suggests the role of the factors studied as determinant in the rate of infection of the Chikungunya; coverage problems and surveillance in health care, demographic aspect, socio-economic problems and lack of preventive measures could explains the risk of family infection by Chikungunya in some areas tropics of Colombia. Trial registration number approval 007–2016 ethics committee-IIBT.