ABSTRACT

ABSTRACT

Dengue is an emerging and re-emerging tropical disease where the main vector is the mosquito Aedes aegipti. This disease is the cause of important seasonal epidemics with high mortality and morbidity rates, which has serious epidemiological, economic, and social impacts, making it an issue of great importance for research. Dengue is a disease considered as a public health priority problem both in national and regional contexts. It is the product of the interaction of various causes generated by socioeconomic, geographic, political, cultural and climatic macro determinants. This research aimed to describe the geographical distribution of dengue in the city of Villavicencio - Colombia and evaluate its relationship with climatic variables. To achieve this, an epidemiological telegram was elaborated for a time window of 10 years. Risk maps were made at the quarterly level for three study years 2017, 2018 and 2019. Additionally, it was evaluated whether there was a relationship between the number of dengue cases and the accumulated precipitation maps for the three chosen years. In general, it was observed that the highest number of cases occurred during wet seasons which correspond with the second and third quarters of the year. It was identified a relationship between the variable precipitation and the number of cases, showing that the periods with the highest number of cases for 2018 and 2019 were characterized by higher rainfall. Regarding the risk maps, it is found that the communities with the highest risk were 4 and 5. The results show that the precipitation variable was significantly associated with the incidence of dengue in Villavicencio. The variability of dengue cases was related to precipitation by 62 % in 2018 and 86% in 2019. Temperature and precipitation variables can predict 30 to 90% of the variability of dengue cases that occurs in Villavicencio for 2018.

Finally, it is recommended to carry out more detailed studies including temperature variables that correspond to the climatic seasons, as well as incorporating social variables in the spatial regressions. Keywords: Dengue virus, Aedes, Geographic Information Systems, Geographic Distribution.