A Comorbidity Network Analysis for Hospitalized Patients to Aid Early Pandemic Preparedness

The COVID-19 pandemic, caused by the new and deadly coronavirus SARS-CoV-2, emerged in late 2019 and then rapidly spread across the globe, leading to widespread illness, significant loss of life, strained healthcare systems, and profound socio-economic disruptions. Characterized by its high transmission rate and elusive nature, the pandemic prompted unprecedented public health measures, including lockdowns, vaccination campaigns, and extensive research efforts to combat and understand the virus. Early response and planning to a pandemic can help achieve efficient resource allocation, targeted public health interventions, accelerated research and vaccine development, informed economic and social planning, global collaboration, and the fostering of public trust, collectively minimizing the impact and facilitating a coordinated response. In this study, we employ a comorbidity network analysis (CNA) approach, which maps interconnections between diverse medical conditions within patient populations, to uncover hidden associations and patterns among co-occurring diseases. We also compare the networks before and during the pandemic using the National (Nationwide) Inpatient Sample (NIS) data. NIS is an all-payer inpatient healthcare database designed to produce U.S. regional and national estimates of inpatient utilization, access, cost, quality, and outcomes. The results of this study can help enhance our understanding of complex health interactions and provide guidance for care planning upon a pandemic outbreak.