Respiratory viral infections such as influenza threaten public health. It is spread through infectious respiratory droplets containing influenza virus. Annually, prior to the COVID-19 pandemic, an estimated 500,000 influenza-related deaths occurred globally, with young children and older adults being the most vulnerable. Despite the availability of influenza vaccines and anti-viral, the ever-evolving nature of influenza strains, coupled with variations in transmission dynamics, presents significant challenges to the efficacy of prevention and control strategies. Very few studies are available to understand the influenza transmission dynamics in the local community setting, particularly in a semi-isolated community setting such as an island city. Moreover, the islands are the natural laboratory for studying infectious disease transmissions. Thus, it can help us better understand the role of different factors, such as virus-virus interference, on influenza transmission dynamics. Therefore, the current study performed between the 2010 and 2018 influenza seasons in the population of Kamigoto Island, Japan, aims to 1. Examine the transmission dynamics of influenza virus by using longitudinal influenza surveillance data, 2. Identify transmission links and sources of outbreaks by constructing the phylogenetic tree of circulating influenza viruses, and 3. Explore the influence of virus-virus codetection on influenza transmission patterns. To address the research questions: 1. A mathematical modeling approach was employed to understand the transmission patterns of the influenza virus. 2. Whole genome sequencing was performed on 198 influenza-confirmed human nasopharyngeal swab (NPS) samples to examine transmission links of the influenza clusters and the role of importation events. 3. Genetic characterization of 13 respiratory viruses was performed on 2,313 NPS samples, and the difference in the within-host diversity of influenza virus was studied. To address the transmission dynamics of influenza within the small island city, a newly developed model, “o2geosocial,” an R package, was applied to analyze the fine-scale longitudinal influenzas surveillance data spanning eight influenza seasons. I chose this model because it allows the transmission tree reconstruction when sequence data are not available. Moreover, the model takes account of the probability of the connection between the different regions, which is particularly important for the current study in a small island city. The study found that preschool and school-aged children, high population density, low local vaccination coverage, and dominant strain of influenza play significant roles in shaping similar geographical transmission patterns across the seasons studied. Moreover, individual vaccination status did not show a significant association with onward transmissibility, suggesting that while vaccination may reduce the severity of infection, it may not prevent transmission. Influenza-like illness (ILI) and/or rapid influenza diagnostic test (RIDT) diagnosed influenza data is insufficient to understand the transmission link of influenza. Genomic sequence data plays a crucial role in revealing the relatedness of the cases in the transmission chains. Moreover, the genomic data can explain the relatedness of influenza strains in the island to mainland Japan or other parts of the world. The second part of this thesis aims to provide whole genome sequencing (WGS) data on influenza viruses by applying next-generation sequencing (NGS) technologies. Reversed reverse transcriptase polymerase chain reaction (RT-PCR) confirmed influenza samples from Kamigoto Island during the 2011/12 and 2012/13 seasons were sequenced. The web-based bioinformatic platform, “INSaFLU, " was used to conduct the phylogenetic study of influenza virus transmission patterns at the local community level. 229 NPS samples were successfully sequenced and identified as A/H3N2 subtypes. All these sequence data were deposited into the gene bank. During the study period, seasonal influenza A(H3N2) activities in the islands were marked by multiple introductions of influenza strains from outside the island and fuelled by local onward transmission. The circulating strains during the study periods were identified as Clade 3C.2 and 3C. At least five transmission clusters were observed during the study period. All the observed transmission clusters circulated simultaneously, which may be misinterpreted as part of the same cluster without sequenced data, highlighting the importance of genomic surveillance. The study also revealed that the first sequenced case and a large number of cases came from the busiest district of the island and spread to the other parts of the island. The epidemic was suggestive to be initiated in the adult working age group (19-64 years old) and spread to different age groups. In an influenza season, other respiratory viruses, including but not limited to the human respiratory syncytial virus (RSV), human rhinovirus (hRV), and human metapneumovirus (MPV), also co-circulate. Despite evidence of virus-virus interactions, their influence on the within-host influenza viral diversity is unclear. In the last part of the Ph.D., 13 respiratory viruses (influenza A and B, hRSV, hRV, hmpv, parainfluenza virus I-IV, adenovirus, bocavirus, human coronavirus (OC43, 229E) were identified in ILI samples using an in-house multiplex RT-PCR protocol. The ILI samples collected during the 2012/13 Influenza season were used for viral identification. Due to the low availability of WGS samples with high genome coverage, only 150 influenza WGS samples were available for variant calling to measure the within-host viral influenza. The study did not identify a significant difference in the influenza viral diversity within the host between those with only influenza-infected versus influenza-virus-infected cases. The within-host influenzas viral diversity is a random event, suggesting a minor or negligible contribution of these viral codetections to the evolution of influenza viruses. However, the sample size available is small, and thus, further study with larger sample sizes is needed. In conclusion, this PhD research contributes to understanding influenza transmission dynamics in a unique community setting. The research demonstrates the importance of integrating surveillance and genetic data to study respiratory virus transmission. The current research also contributed to broader accessibility of the influenza sequence data from Japan, as there are limited whole genome sequences (WGS) available from Japan for that period (less than 10 in 2011/12 and zero in the 2012/13 influenza season). This research also explored virus-virus codetection on the influenza evolution with the host. However, given the low sample size, further studies are warranted for more in-depth investigations to conclusively determine the impact of virus-virus interactions on influenza virus genetic diversity.