Post-acute sequelae of SARS-CoV-2 infection symptom network centrality analysis of Taiwan population to unveil intricate symptomatology patterns

Abstract Post-acute sequelae of SARS-CoV-2 infection (PASC), or long COVID, present a complex array of persistent symptoms that remain poorly understood. Identifying the central symptoms and their interrelationships is crucial for effective management and intervention. This study applied network centrality analysis to 672 individuals diagnosed with COVID-19 in southern Taiwan, who completed an online survey on persistent symptoms. Participants were classified into two groups: post-acute COVID (symptoms lasting 4–12 weeks post-infection) and long COVID (symptoms lasting > 12 weeks). Symptom networks were constructed using polychoric correlations, with centrality measures (betweenness, closeness, strength, expected influence) used to assess symptom influence. A network comparison test evaluated invariance and global strength between the two groups. The mean age of participants was 38.75 years, with significant age differences between the post-acute COVID group (40.31 years) and the long COVID group (37.76 years). Diarrhea showed high betweenness centrality in both groups, acting as a key connector. Palpitations exhibited higher closeness centrality in long COVID, while fever was central in post-acute cases. Strength centrality was notably high for palpitations and chest pain in long COVID. No gender differences were found, and the global strength of the networks did not differ significantly between the groups (p = 0.93). This study reveals that long COVID has a more tightly interconnected symptom network compared to post-acute COVID, with central symptoms like palpitations and chest pain offering potential targets for tailored treatment strategies. The findings emphasize the importance of symptom interrelationships, though longitudinal studies are needed to further explore causal relationships and the progression of symptoms over time.