Dengue is an endemic disease in Colombia. Norte de Santander is a region on the border of Colombia and Venezuela and has reported the co-circulation and simultaneous co-infection of different serotypes of the dengue virus (DENV). This study aimed to conduct a phylogenetic analysis on the origin and genetic diversity of DENV strains circulating in this bordering region. Serum samples were collected from patients who were clinically diagnosed with febrile syndrome associated with dengue during two periods. These samples were tested for DENV and serotyping was performed using reverse transcriptase-polymerase chain reaction. Subsequently, positive samples were amplified and the envelope protein gene of DENV was sequenced. Phylogenetic and phylogeographic analyses were performed using the sequences obtained. Basic local alignment search tool analysis confirmed that six and eight sequences belonged to DENV-1 and DENV-2, respectively. The phylogenetic analysis of DENV-1 showed that the sequences belonged to genotype V and clade I; they formed two groups: in the first group, two sequences showed a close phylogenetic relationship with strains from Ecuador and Panama, whereas the other four sequences were grouped with strains from Venezuela and Colombia. In the case of DENV-2, the analysis revealed that the sequences belonged to the Asian–American genotype and clade III. Furthermore, they formed two groups; in the first group, three sequences were grouped with strains from Colombia and Venezuela, whereas the other five were grouped with strains from Venezuela, Colombia and Honduras. This phylogenetic analysis suggests that the geographical proximity between Colombia and Venezuela is favourable for the export and import of different strains among serotypes or clades of the same DENV serotype, which could favour the spread of new outbreaks caused by new strains or genetic variants of this arbovirus. Therefore, this information highlights the importance of monitoring the transmission of DENV at border regions.
As demonstrated with the novel coronavirus pandemic, rapid and accurate diagnosis is key to determine the clinical characteristic of a disease and to improve vaccine development. Once the infected person is identified, hematological findings may be used to predict disease outcome and offer the correct treatment. Rapid and accurate diagnosis and clinical parameters are pivotal to track infections during clinical trials and set protection status. This is also applicable for re-emerging diseases like dengue fever, which causes outbreaks in Asia and Latin America every 4 to 5 years. Some areas in the US are also endemic for the transmission of dengue virus (DENV), the causal agent of dengue fever. However, significant number of DENV infections in rural areas are diagnosed solely by clinical and hematological findings because of the lack of availability of ELISA or PCR-based tests or the infrastructure to implement them in the near future. Rapid diagnostic tests (RDT) are a less sensitive, yet they represent a timely way of detecting DENV infections. The purpose of this study was to determine whether there is an association between hematological findings and the probability for an NS1-based DENV RDT to detect the DENV NS1 antigen. We also aimed to describe the hematological parameters that are associated with the diagnosis through each test.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.