The occurrence and spread of infectious diseases pose considerable challenges to public health. While the relationship between the built environment and the spread of infectious diseases is well-documented, there is a dearth of urban planning tools specifically designed for conducting Health Impact Assessments (HIAs) targeted at infectious diseases. To bridge this gap, this paper develops a comprehensive framework of an HIA for Urban Planning and Epidemic (HIA4UPE), formulated by considering the progression of public health incidents and the distinct transmission patterns of infectious diseases. This framework is designed to provide a comprehensive assessment by including a health risk-overlay assessment, health resource-quality assessment, health resource-equality assessment, and health outcome-impact prediction, enabling a multidimensional evaluation of the potential impacts of current environmental conditions or planning proposals on the incidence of infectious diseases. Furthermore, this paper advances the application of spatial analysis and computation, comprehensive assessment methodologies, and predictive analytics to conduct specific assessments. The theoretical framework and analytical tools presented in this paper contribute to the academic discourse and offer practical utility in urban planning and policymaking on epidemic prevention and control.

Composite indicators support policy comparison by compressing multidimensional information, but different indicator configurations can appear similar in aggregate. This study develops and applies a contribution-structure audit to China’s 86 county-level urban-rural integration pilot units. Using 2019–2023 multi-source spatial data, we apply principal component analysis (PCA) to indicators of economic-activity change, built-up expansion, public-service facility nodes, and transport-service nodes. Along the dominant axis, built-up and economic-activity changes oppose facility- and transport-node changes, enabling different indicator configurations to occupy nearby composite positions through compensation. Across all 3655 pairs among the 86 units, composite-position and contribution-structure distances constructed from the same standardized indicators and PCA weights are positively associated (Pearson $r=0.543$), reflecting their internal alignment. The baseline Q25/Q75 same-zone strict screen identifies 11 pairs in which close composite positions coexist with divergent contribution structures. Such pairs also appear in alternative checks that vary screening thresholds, regional composition, POI variables, and distance definitions. Their counts and identities change across specifications. This finding supports inspecting contribution structures when selecting apparently similar cases. For comparative learning among pilot units, the audit identifies cases requiring contextual evidence on institutions, implementation, and outcomes before their experiences are assessed for replication.