中国打造周边卫生健康共同体的路径与策略
The Path and Strategy of Building Neighboring Community of Health for All
冯羿凯 1石珺怡 1金音子 2许铭 2许利平3
作者信息
- 1. 北京大学 公共卫生学院,北京 100191
- 2. 北京大学 公共卫生学院,北京 100191;北京大学 全球健康发展研究院,北京 100871
- 3. 中国社会科学院 亚太与全球战略研究院,北京 100007
- 折叠
摘要
打造周边卫生健康共同体是中国与周边国家合作共建人类卫生健康共同体的具体实践,是人类卫生健康共同体的重要使命.中国与周边国家由于频繁的贸易和人员往来及相似的文化和自然环境,存在诸多共同的卫生挑战,必须依靠集体、协调的合作行动加以应对.本文基于全球卫生治理理论及国际合作机制研究框架阐述周边卫生健康共同体的内涵,选取东南亚国家联盟、上海合作组织、中日韩合作、亚太经合组织四个在中国周边发挥重要作用的区域合作机制,依据周边卫生治理路径框架分析其机制特点及职能实现情况,总结中国打造周边卫生健康共同体面临的挑战,探索打造周边卫生健康共同体的策略.
Abstract
Neighboring Community of Health for All is an important component of Community of Common Health for Mankind.Building a Neighboring Community of Health for All is a concrete practice of jointly building a Community of Common Health for Mankind with neighboring countries and cooperation mechanisms.Frequent trade and personnel exchanges between China and neighbor-ing countries,as well as similar cultural and natural environments,have created shared health chal-lenges that must be addressed through collective and coordinated cooperative actions.This article elaborates on the connotations of the Neighboring Community of Health for All based on the theo-retical framework of global health governance and international cooperation mechanisms.It selects four regional cooperation mechanisms that play important roles in China's periphery,namely the Association of Southeast Asian Nations(ASEAN),the Shanghai Cooperation Organization(SCO),China-Japan-Korea cooperation,and the Asia-Pacific Economic Cooperation(APEC).Based on the framework of peripheral health governance pathways,it analyzes the characteristics of these mecha-nisms and their functional implementation.It summarizes the challenges faced by China in building Neighboring Community of Health for All and explores strategies for building it.
关键词
全球卫生治理/卫生健康共同体/公共卫生安全/卫生合作/策略Key words
Global health governance/Common health for mankind/Public health security/Health cooperation/Strategy引用本文复制引用
基金项目
国家社科基金重点项目(22AZD107)
科技部对发展中国家科技援助项目(KY202101004)
出版年
2024
NETL
NSTL
万方数据