Phylogenetic study of local patterns influenza A(H3N2) virus transmission in a semi-isolated population in a remote island in Japan between 2011-2013

Background The spatial spread and importation risk of influenza A viruses in rural settings remains unclear due to the sparsity of representative spatiotemporal sequence data. Methods Nasopharyngeal (NPS) samples of Rapid Influenza Diagnostic Test (RIDT) positive individuals in Kamigoto Island, Japan, were confirmed using quantitative polymerase chain reaction (RT-PCR). The confirmed influenza A positive samples were processed for whole- genome sequencing. Time-resolved phylogenetic trees were built from HA sequences to classify the circulating clades, with events of introductions and local clustering. Spatio-temporal transmission patterns were then analyzed for the largest local clusters. Results We obtained 178 whole-genome sequences of influenza A/H3N2 collected during 2011/12 and 2012/13 influenza seasons. The time-resolved phylogenetic tree identified at least six independent introduction events in 2011/12 and 2012/13. Majority of Kamigoto strains are closely related to strains from mainland Japan. All 2011/12 strains were identified as clade 3 C.2 (n=29), while 2012/13 strains fell into two clades: clade 3C.2 (n=129), and 3C.3a (n=20). No local persistence over one year was observed for Kamigoto strains. The spatio-temporal analysis of the largest cluster revealed that the first case and a large number of cases came from the busiest district of the island and spread towards the other parts of the island. Conclusion Influenza A(H3N2) virus outbreaks in Kamigoto island were marked by multiple introductions and fueled by local transmission. All the identified clusters in 2012/13 season circulate simultaneously. These cases may be misinterpreted as part of the same cluster without sequencing data, highlighting the importance of genomic surveillance. The results of this study are based on a two-year analysis of influenza sequences from the island; repeated analyzes for different influenza seasons and geographic locations will help us better understand detailed transmission patterns.