Post-acute COVID-19 conditions, commonly referred to as Long COVID, have emerged as a persistent and heterogeneous public health challenge with significant geographic variability across populations. Despite increasing recognition of its clinical and socioeconomic burden, limited analytical frameworks exist for systematically evaluating spatial disparities in symptom prevalence and severity across U.S. states and metropolitan regions. This study develops a multilevel analytical framework integrating epidemiological surveillance, socioeconomic stratification, and health system capacity indicators to assess geographic inequalities in Long COVID outcomes. Drawing on national surveillance datasets and prior empirical evidence, the framework conceptualizes Long COVID as a layered outcome influenced by individual-level infection severity, community-level vulnerability, and structural determinants of health.

The findings synthesized from existing literature highlight substantial disparities in Long COVID prevalence, with higher burdens observed in socioeconomically disadvantaged and geographically diverse regions. Evidence suggests that post-acute sequelae are strongly associated with pre-existing health inequities, occupational exposure risks, and uneven access to healthcare resources. The study further emphasizes the need for standardized surveillance mechanisms and integrated data systems to capture long-term outcomes. As highlighted in national research planning discussions, the current response to Long COVID remains insufficiently coordinated and requires stronger analytical infrastructure to guide policy decisions (Abbasi, 2022).

The proposed framework provides a scalable model for understanding spatial heterogeneity in post-COVID conditions and supports targeted intervention strategies. Ultimately, this work contributes to advancing population health analytics by integrating multilevel determinants into a unified geographic disparity assessment model.

Long COVID, geographic disparities, multilevel modeling, post-acute sequelae

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