Abstract: Objective to construct an evaluation index system and assess emergency response capacity of Guangdong CDCs. Methods Health emergency response capacity evaluation index system of Guangdong CDCs was drafted based upon expert consultation, documentary analysis and focus group discussion on the basis of Guangdong CDCs’ duties and features of emergency work. The evaluation index system was established by applying Delphi method two rounds to consult 26 experts chosen from Guangdong Province. By conducting a questionnaire survey, a general investigation was made for 22 cities of Guangdong Province including Shunde. Analytic hierarchy process was applied to calculate the weight of primary and secondary indexes and proportionate allocation method was used to calculate the third-level. Hierarchical clustering was applied for the classification of the CDCs. Results Two rounds of expert consultations were conducted, 26 and 24 questionnaires were sent in each round, 24 and 23 were recovered respectively, and general recovery rate was 94% (47/50). Kendall's coefficient of concordance was 0.412 and 0.490 at the first and second round of expert consultations respectively. After two rounds of consultations, the evaluation index system was established and its overall Crowns Bach alpha coefficient was 0.858. The constructed index system consists of 8 primary indexes, 24 secondary indexes, and 60 third-level indexes. The eight primary indexes included emergency management system, human resources, surveillance and early-warning ability, emergency response capacity, laboratory’s testing capability, emergent supply capability, trainings and drills, health education and media communication, whose systematic weights were 0.119 8, 0.131 2, 0.121 3 0.193 6,0.129 3, 0.127 8, 0.099 5, and 0.077 5, respectively. The emergency capacity assessment states that the top 3 cities with the highest scores were Shenzhen (0.922), Guangzhou (0.913) and Zhuhai (0.877) while Shanwei (0.475), Heyuan (0.523) and Yunfu (0.541) were the last 3 cities with the lowest scores. The 22 CDCs in the province were classified into 4 categories through hierarchical clustering. The cities of Classes 3 and 4, with a lower emergency response capacity, were mainly in the western, eastern, and northern parts of Guangdong. A positive correlation was found between the scores and local GDP levels (r=0.828 9, P<0.01). Conclusion The index system constructed in this study possesses a high credibility. The emergency response capacity among CDCs in Guangdong is not balanced and the capability of CDCs in economic less-developed areas is relatively weak.