Objective This study aims to compare the performance of open-source surveillance systems and official reporting systems in the early detection of chikungunya fever outbreaks, and to examine the consistency of trends between the former and historical case data.

Methods Reports on chikungunya-related events were collected from the Program for Monitoring Emerging Diseases (ProMED) and the World Health Organization Disease Outbreak News (WHO DON) between January 1, 2000 and September 30, 2025. In addition, historical global case data from 2000 to 2024 were compiled based on information publicly released through official websites and the published literature. The large language model is used to assist in the automatic identification and extraction of events, and the events are merged and classified according to the country ( or region ), time and economic development level. Timeliness was evaluated by comparing the reporting dates of events in ProMED and WHO DON, while the representativeness of ProMED event trends was assessed using reported case numbers as a reference.

Results  A total of 1 322 ProMED events were obtained, covering 95 countries ( or regions ). There were 33 WHO DON events, covering 26 countries ( or regions ). Among the 28 events that matched the two, the median reporting time of ProMED was 13 days earlier than that of WHO DON, and about 67.86 % of the events were reported earlier in ProMED. Global Chikungunya fever cases peaked three times in 2006,2014 and 2024, and the number of ProMED events also increased significantly in the corresponding years. The two showed consistency in the main epidemic stages. The trend of the two groups shows obvious synchronicity in the low-income group, the middle-high income group and the high-income group, and the trendof the middle-low income group is quite different.

Conclusion ProMED demonstrates superiority over WHO DON in capturing early signals of chikungunya outbreaks, providing more acute detection of endemic and small-scale occurrences, whereas WHO DON places greater emphasis on major events with international implications. ProMED events’ temporal trends exhibit high consistency with historical case data, indicating its effectiveness in reflecting epidemic dynamics at a macro level. Integrating both datasets enhances the timeliness and comprehensiveness of global infectious disease surveillance systems, providing valuable reference for early warning systems against future public health emergencies. The event reports and case reports used in this study depend on the availability of local open source information and the completeness of the infectious disease surveillance system. Especially in the low-income group and the middle-low income group, they cannot fully reflect the local epidemic situation, and still need to be comprehensively evaluated in combination with on-site investigations.