METHODS: To verify the causative agent of this outbreak and characterise the viral genes, the genes encoding the structural proteins C/prM/E of viruses isolated from local residents were sequenced followed by mutation and phylogenetic analysis. Recombination, selection pressure, potential secondary structure and three-dimensional structure analyses were also performed.
RESULTS: Phylogenetic analysis revealed that all epidemic strains were of the cosmopolitan DENV-2 genotype and were most closely related to the Zhejiang strain (MH010629, 2017) and then the Malaysia strain (KJ806803, 2013). Compared with the sequence of DENV-2SS, 151 base substitutions were found in the sequences of 89 isolates; these substitutions resulted in 20 non-synonymous mutations, of which 17 mutations existed in all samples (two in the capsid protein, six in the prM/M proteins, and nine in the envelope proteins). Moreover, amino acid substitutions at the 602nd (E322:Q → H) and 670th (E390: N → S) amino acids may have enhanced the virulence of the epidemic strains. One new DNA binding site and five new protein binding sites were observed. Two polynucleotide binding sites and seven protein binding sites were lost in the epidemic strains compared with DENV-2SS. Meanwhile, five changes were found in helical regions. Minor changes were observed in helical transmembrane and disordered regions. The 429th amino acid of the E protein switched from a histamine (positively charged) to an asparagine (neutral) in all 89 isolated strains. No recombination events or positive selection pressure sites were observed. To our knowledge, this study is the first to analyse the genetic characteristics of epidemic strains in the first dengue outbreak in Hunan Province in inland China.
CONCLUSIONS: The causative agent is likely to come from Zhejiang Province, a neighbouring province where dengue fever broke out in 2017. This study may help clarify the intrinsic geographical relatedness of DENV-2 and contribute to further research on pathogenicity and vaccine development.
METHODS: Electronic searches were conducted in the Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, MEDLINE (complete), PubMed and Scopus. Eligible studies to be included in this review were cohort studies with participants confirmed by laboratory test for dengue infection and comparison among the different severity of dengue infection by using statistical models. The methodological quality of the paper was assessed by independent reviewers using QUADAS-2.
RESULTS: Twenty-six studies published from 1994 to 2017 were included. Most diagnostic models produced an accuracy of 75% to 80% except one with 86%. Two models predicting severe dengue according to the WHO 2009 classification have 86% accuracy. Both of these logistic regression models were applied during the first three days of illness, and their sensitivity and specificity were 91-100% and 79.3-86%, respectively. Another model which evaluated the 30-day mortality of dengue infection had an accuracy of 98.5%.
CONCLUSION: Although there are several potential predictive or diagnostic models for dengue infection, their limitations could affect their validity. It is recommended that these models be revalidated in other clinical settings and their methods be improved and standardised in future.