Early warning signal for dengue outbreaks and identification of high risk areas for dengue fever in Colombia using climate and non-climate datasets

BMC Infectious Diseases

Research Article

Victor M. Herrera¹  Luis Villar¹  Mabel Carabali²  Jung-Seok Lee³  Andrew Farlow³  Il-Yeon Park⁴  Jacqueline K. Lim⁴ 

[1] Clinical Epidemiology Unit, School of Medicine, Universidad Industrial de Santander, Cra 32 # 29 - 31 Office, 304, Bucaramanga, Santander, Colombia;Department of Epidemiology, McGill University, Biostatistics and Occupational Health, Purvis Hall, 1020 Pine Avenue West, H3A1A2, Quebec, Montreal, Canada;International Vaccine Institute, SNU Research Park, San 4-8, 151-919, Seoul, Nakseongdae-dong, Gwanak-gu, South Korea;Department of Zoology, The University of Oxford, The Tinbergen Building, South Parks Road, OX1 3PS, Oxford, UK;International Vaccine Institute, SNU Research Park, San 4-8, 151-919, Seoul, Nakseongdae-dong, Gwanak-gu, South Korea;

关键词: Dengue;    Early warning system;    Dengue epidemic;    Population at risk for dengue fever;   

DOI  :  10.1186/s12879-017-2577-4

 received in 2017-01-11, accepted in 2017-06-29,  发布年份 2017

来源: Springer

【 摘 要 】

BackgroundDengue has been prevalent in Colombia with high risk of outbreaks in various locations. While the prediction of dengue epidemics will bring significant benefits to the society, accurate forecasts have been a challenge. Given competing health demands in Colombia, it is critical to consider the effective use of the limited healthcare resources by identifying high risk areas for dengue fever.MethodsThe Climate Risk Factor (CRF) index was constructed based upon temperature, precipitation, and humidity. Considering the conditions necessary for vector survival and transmission behavior, elevation and population density were taken into account. An Early Warning Signal (EWS) model was developed by estimating the elasticity of the climate risk factor function to detect dengue epidemics. The climate risk factor index was further estimated at the smaller geographical unit (5 km by 5 km resolution) to identify populations at high risk.ResultsFrom January 2007 to December 2015, the Early Warning Signal model successfully detected 75% of the total number of outbreaks 1 ~ 5 months ahead of time, 12.5% in the same month, and missed 12.5% of all outbreaks. The climate risk factors showed that populations at high risk are concentrated in the Western part of Colombia where more suitable climate conditions for vector mosquitoes and the high population level were observed compared to the East.ConclusionsThis study concludes that it is possible to detect dengue outbreaks ahead of time and identify populations at high risk for various disease prevention activities based upon observed climate and non-climate information. The study outcomes can be used to minimize potential societal losses by prioritizing limited healthcare services and resources, as well as by conducting vector control activities prior to experiencing epidemics.

【 授权许可】

CC BY   
© The Author(s). 2017

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