Influenza A virus subtypes are determined based on envelope proteins encoded by the hemagglutinin (HA) gene and the neuraminidase (NA) gene, which are involved in attachment to the host, pathogenicity, and progeny production. Here, we evaluated such differences through co-evolution analysis between the HA and NA genes based on subtype and host. Event-based cophylogeny analysis revealed that humans had higher cospeciation values than avian. In particular, the yearly ML phylogenetic trees for the H1N1 and H3N2 subtypes in humans displayed similar topologies between the two genes in humans. Substitution analysis was verifying the strong positive correlation between the two genes in the H1N1 and H3N2 subtypes in humans compared with those in avian and swine. These results provided a proof of principle for the further development of vaccines according to hosts and subtypes against Influenza A virus.

Background: In South Korea, the epidemiological characteristics of children and adolescents infected with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) have not been reported to date. The purpose of this study was to identify major epidemiological characteristics and transmission patterns of coronavirus disease 2019 (COVID-19) in children and adolescents. Methods: This study was conducted through a system integrated in an epidemiological investigation by the Korea Disease Control and Prevention Agency from January 20, 2020, to June 5, 2021. We analyzed the epidemiological characteristics of 14,967 children and adolescents with COVID-19 according to the age groups and transmission age patterns of 3721 infector-infectee pairs in South Korea. Results: Among the total confirmed COVID-19 cases, 14,967 patients were aged 0-18 years. The most affected age group among children and adolescents were those aged 16-18 years (3589, 24.0%). For all age groups, the infection route through friends and family members (31.9%) was the highest. For the contact age pattern analysis, infection from infectors aged 30-49 years to infectees aged 0-12 years showed a statistically significant relation (p <0.001) compared to that in other age groups. On the other hand, among the infectees aged 13-15 years and 16-18 years were significantly related with adolescents aged 10-19 years (p <0.05). Conclusion: These results suggest that adolescents aged 13-18 years were more infected with COVID-19 than those aged 0-12 years. Furthermore, they are particularly more likely to be infected by friends and family members. Besides, in patients aged 13-18 years, transmission of SARS-CoV-2 was more common from adolescents to adolescents than from adults to adolescents. This research will provide scientific evidence for school policies and vaccine strategies for COVID-19 prevention in children and adolescents.

The world faced with emerge infectious disease including Middle East Respiratory Syndrome and Zika virus. These infectious diseases are associated with extremely rapid and complex propagation patterns due to diversified transportation increased international trades. Against this, we conducted study on predicting disease spread patterns using various public data including the GIS of South Korea. A simulation was performed using an agent-based model with highway traffic data and census data for each of the fourteen provinces. The findings indicated a correlation between the spread pattern of influenza during the 2009 influenza pandemic and some of the traffic movement patterns. Therefore, the possibility of using population movement through highway data as predictive parameter for the spread of infectious diseases was confirmed through a public open data based analysis.

We developed simulation tool for influenza virus variation (SimFluVar), an analytics software for calculating genomic variation among members of the influenza virus group. This study is related to computational evolutionary biology and evolutionary bioinformatics. SimFluVar is an analytical tool that can be used to calculate codon substitution patterns of viral genes. Designed to compare a large number of nucleotide sequences, SimFluVar provides precise patterns of codon variations between two viral groups, especially for the influenza virus. SimFluVar also provides useful functions, such as editing and visualization of the result matrix. This new tool can be used to analyze codon variation patterns over time as well as to analyze the genomic differences between viruses obtained from different geographical locations. SimFluVar is developed in C++, and Java RCP is used as a distribution package. SimFluVar, including the associated documentation, manuals, and examples, is publicly available at http://lcbb.snu.ac.kr/simfluvar.