Background <p>The One Health approach recognizes the interconnectedness of human, animal, and environmental health to address global health threats. While the global One Health Index (GOHI) has been applied nationally, its adaptation to sub-national contexts remains unexplored. This study aimed to adapt GOHI to construct localized indicators for Fukuoka, Japan, and assess One Health implementation across municipalities.</p> Methods <p>The research followed a three-phase approach: (1) Indicator Selection, where 34 indicators were selected from GOHI and Fukuoka One Health Promotion Action Plan through expert consultation; (2) Data Collection and Score Standardization using robust scaling methods; and (3) Weight Determination using Fuzzy Analytic Hierarchy Process. Fukuoka One Health Index (FOHI) scores were computed and analyzed using descriptive statistics and Latent Class Analysis (LCA).</p> Results <p>The mean FOHI score was 52.27 (range: 41.01–63.71), with the lowest average score in Core Drivers Index (47.11) compared to Internal Drivers Index (59.17) and External Drivers (50.43). Municipalities performed strongest in zoonotic disease management (72.33) but weakest in One Health governance (6.36). Miyama City achieved the highest overall score, demonstrating strong governance and integrated implementations. LCA identified two municipal classes differentiated by External Drivers Index scores with clear geographic clustering.</p> Conclusions <p>This study demonstrated the feasibility of adapting GOHI to municipal settings and revealed significant variation in One Health implementation across Fukuoka’s municipalities. Performance gaps were identified, particularly in One Health governance despite strong health infrastructure. The methodology offers a blueprint for similar adaptations globally, potentially accelerating the operationalization of One Health principles in local governance contexts.</p>

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Adaptation of global One Health evaluation framework to municipal levels in Fukuoka, Japan

  • Fumihiko Yokota,
  • Yi-Sheng Ning,
  • Shu-Ning Chen,
  • Hisako Nomura,
  • Shunsuke Managi,
  • Jing-Shu Liu,
  • Xiao-Xi Zhang,
  • Xiao-Nong Zhou,
  • Shuji Shimizu

摘要

Background

The One Health approach recognizes the interconnectedness of human, animal, and environmental health to address global health threats. While the global One Health Index (GOHI) has been applied nationally, its adaptation to sub-national contexts remains unexplored. This study aimed to adapt GOHI to construct localized indicators for Fukuoka, Japan, and assess One Health implementation across municipalities.

Methods

The research followed a three-phase approach: (1) Indicator Selection, where 34 indicators were selected from GOHI and Fukuoka One Health Promotion Action Plan through expert consultation; (2) Data Collection and Score Standardization using robust scaling methods; and (3) Weight Determination using Fuzzy Analytic Hierarchy Process. Fukuoka One Health Index (FOHI) scores were computed and analyzed using descriptive statistics and Latent Class Analysis (LCA).

Results

The mean FOHI score was 52.27 (range: 41.01–63.71), with the lowest average score in Core Drivers Index (47.11) compared to Internal Drivers Index (59.17) and External Drivers (50.43). Municipalities performed strongest in zoonotic disease management (72.33) but weakest in One Health governance (6.36). Miyama City achieved the highest overall score, demonstrating strong governance and integrated implementations. LCA identified two municipal classes differentiated by External Drivers Index scores with clear geographic clustering.

Conclusions

This study demonstrated the feasibility of adapting GOHI to municipal settings and revealed significant variation in One Health implementation across Fukuoka’s municipalities. Performance gaps were identified, particularly in One Health governance despite strong health infrastructure. The methodology offers a blueprint for similar adaptations globally, potentially accelerating the operationalization of One Health principles in local governance contexts.