Establishment of an indicator framework for global One Health Intrinsic Drivers index based on the grounded theory and fuzzy analytical hierarchy-entropy weight method

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Abstract

Background: One Health has become a global consensus to deal with complex health problems. However, the progress of One Health implementation in many countries is still relatively slow, and there is a lack of systematic evaluation index. The purpose of this study was to establish an indicator framework for global One Health Intrinsic Drivers index (GOH-IDI) to evaluate human, animal and environmental health development process globally. Method: First, 82 studies were deeply analyzed by a grounded theory (GT) method, including open coding, axial coding, and selective coding, to establish a three-level indicator framework, which was composed of three selective codes, 19 axial codes, and 79 open codes. Then, through semi-structured interviews with 28 health-related experts, the indicators were further integrated and simplified according to the inclusion criteria of the indicators. Finally, the fuzzy analytical hierarchy process combined with the entropy weight method was used to assign weights to the indicators, thus, forming the evaluation indicator framework of human, animal and environmental health development process. Results: An indicator framework for GOH-IDI was formed consisting of three selective codes, 15 axial codes and 61 open codes. There were six axial codes for “Human Health”, of which “Infectious Diseases” had the highest weight (19.76%) and “Injuries and Violence” had the lowest weight (11.72%). There were four axial codes for “Animal Health”, of which “Animal Epidemic Disease” had the highest weight (39.28%) and “Animal Nutritional Status” had the lowest weight (11.59%). Five axial codes were set under “Environmental Health”, among which, “Air Quality and Climate Change” had the highest weight (22.63%) and “Hazardous Chemicals” had the lowest weight (17.82%). Conclusions: An indicator framework for GOH-IDI was established in this study. The framework were universal, balanced, and scientific, which hopefully to be a tool for evaluation of the joint development of human, animal and environmental health in different regions globally.

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APA

Feng, J., Guo, Z., Ai, L., Liu, J., Zhang, X., Cao, C., … Li, S. (2022). Establishment of an indicator framework for global One Health Intrinsic Drivers index based on the grounded theory and fuzzy analytical hierarchy-entropy weight method. Infectious Diseases of Poverty, 11(1). https://doi.org/10.1186/s40249-022-01042-3

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