A One Health performance evaluation system for urban parasitic disease prevention and control: The Shanghai, China pilot scheme

Background: Growing complexity of urban parasitic disease transmission, driven by interlinked human, animal, and environmental factors, demands a One Health approach for effective surveillance and control. Yet, standardized, weighted frameworks to assess these integrated systems are lacking in megacities. This study developed and piloted a One Health indicator system to evaluate parasitic disease surveillance/control capacities across 16 districts which conduct such surveillance in Shanghai, a city in Eastern China, aiming to preliminarily quantify county-level performance and identify key gaps. Methods: The study used a rigorous, multi-step framework based on the Global One Health Index (GOHI). First, a preliminary indicator pool drew from systematic reviews of policies, technical schemes, and peer-reviewed papers. A two-round Delphi consultation with 19 interdisciplinary experts refined indicators. The Analytic Hierarchy Process (AHP) determined indicator weights; all consistency ratios (CR < 0.1) verified logical consistency. For the Shanghai pilot, data from 16 districts were collected; missing values were imputed via mean values from socio-economically similar districts. Indicators were normalized to a 60-100 scale using min-max or benchmark methods; PCA with PAM clustering assessed social-ecological vulnerability. Data analysis/visualization used R (v4.5.1). Results: The final One Health indicator system included 2 first-level domains, 6 second-level, 40 third-level, and 121 fourth-level indicators. Shanghai pilot results showed three key findings: (1) A U-shaped relationship between social-ecological vulnerability and control performance-medium-vulnerability districts (PCA-stratified into 3 clusters) scored significantly lower (mean = 94.68, range≈9) than high/low ones, indicating a "resourcing trap"; (2) Domain-specific heterogeneity: "Work Execution" (mean = 99.82) and "Risk Judgement" (mean = 96.29) performed well, while "Control Efficacy" (mean = 89.97) was weak (e.g., uneven diagnostics for amoebiasis/angiostrongyliasis); (3) Key capacity gaps: 31.25% of district laboratories had CNAS accreditation; 6/16 met the 95% schistosomiasis knowledge benchmark; imported malaria (281 cases, 2017-2022; 99.3% from Africa) clustered in high-mobility districts. Soil-transmitted helminth prevalence fell to <0.1% (2015-2023) but persisted in high-risk groups (farmers: 0.109%). Conclusions: This study developed the first weighted One Health evaluation system for urban parasitic disease control, filling the gap of standardized assessment tools in megacities. Delphi-AHP ensures rigor; PCA-PAM enables targeted vulnerability stratification. Shanghai results highlight needs to address "mid-vulnerability resource misallocation," strengthen control efficacy (e.g., laboratory accreditation, high-risk group interventions), and enhance importation surveillance. The framework provides a data-driven basis for optimizing Shanghai's control strategies and a "Shanghai Blueprint" for global megacities to build resilient, integrated One Health systems against parasitic and zoonotic threats.