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        <datestamp>2026-09-22T09:14:51Z</datestamp>
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          <dc:title>Supporting data for "Evolution and the Effect of Population Immunity Structure of SARS-CoV-2 and Influenza Viruses"</dc:title>
          <dc:creator>Xiaojuan Zhang (13127814)</dc:creator>
          <dc:subject>Clinical microbiology</dc:subject>
          <dc:subject>Health surveillance</dc:subject>
          <dc:subject>Virology</dc:subject>
          <dc:subject>SARS-CoV-2 antibody response</dc:subject>
          <dc:subject>frailty and COVID-19</dc:subject>
          <dc:subject>immune escape capacity</dc:subject>
          <dc:subject>influenza</dc:subject>
          <dc:description>&lt;p dir="ltr"&gt;Respiratory viruses continuously evolve into new lineages, which can compromise the immunity conferred by prior vaccination or infection, or lead to increased disease severity. Understanding this dynamic interplay is crucial, as it guides public health strategies by informing the impact of these novel variants. To enable accurate risk assessment of emerging respiratory viruses, we established an integrated framework that combined genomic, serological, and organoid-based virus characterization. We characterized emerging respiratory viruses from both viral and host perspectives using this framework. At the viral level, we analyzed the immune escape of SARS-CoV-2 variants and explored the mechanism underlying the replacement of XBB.1.9.1 by EG.5.1, comparing their replication capacity, fusion efficiency, and immune evasion. At the host level, we evaluated immune responses against SARS-CoV-2 and influenza viruses in individuals with diverse infection and vaccination histories, and further identified factors associated with low neutralizing antibody titers and poor T cell responses in vulnerable populations. In parallel, we assessed the replication capacity and binding affinity of HPAI H5N1 subtype D1.1 and B3.13. &lt;/p&gt;&lt;p dir="ltr"&gt;The dataset is provided as 7 folders containing all raw data presented in this thesis. Each folder is clearly labeled according to the corresponding thesis chapter and includes all original records and data files, such as Excel spreadsheets documenting antibody titers, participant demographics, and vaccination/infection histories, as well as fluorescence microscope images.&lt;/p&gt;</dc:description>
          <dc:date>2026-09-22T09:14:51Z</dc:date>
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          <dc:identifier>10.25442/hku.33340344.v1</dc:identifier>
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