This study presents a comprehensive dataset on Salmonella outbreaks (SO) in China from 1949 to 2023, including 1,134 outbreaks involving over 89,050 patients. The dataset includes 506 high-quality reports and contains over 46,494 entries, with 50 columns, providing detailed information on outbreak characteristics, patient demographics, laboratory findings, and clinical management. The dataset also includes socio-economic and climate data for relevant regions, enabling correlation analysis and predictive modeling. The study aims to improve understanding of SO trends and inform policy-making and outbreak prediction. The dataset is available on Figshare under a CC-BY license. The study highlights the importance of systematic data collection and analysis for understanding and managing infectious diseases. It also identifies limitations, such as potential reporting bias and the need for more comprehensive data. The dataset is designed for use in systematic reviews, meta-analyses, and predictive modeling, and can be integrated with other data sources for further analysis. The study underscores the need for open access and data transparency in public health surveillance. The dataset provides insights into the epidemiological patterns of SO in China, including the increasing trend and higher incidence in certain regions. The study also emphasizes the importance of interdisciplinary research and collaboration in addressing public health challenges. The dataset is a valuable resource for researchers and public health professionals seeking to understand and manage Salmonella outbreaks. The study was supported by various funding sources, including the National Program on Key Research Project of China and the European Union's Horizon 2020 Research and Innovation Programme. The authors declare no competing interests. The study is published under a Creative Commons Attribution 4.0 International License.This study presents a comprehensive dataset on Salmonella outbreaks (SO) in China from 1949 to 2023, including 1,134 outbreaks involving over 89,050 patients. The dataset includes 506 high-quality reports and contains over 46,494 entries, with 50 columns, providing detailed information on outbreak characteristics, patient demographics, laboratory findings, and clinical management. The dataset also includes socio-economic and climate data for relevant regions, enabling correlation analysis and predictive modeling. The study aims to improve understanding of SO trends and inform policy-making and outbreak prediction. The dataset is available on Figshare under a CC-BY license. The study highlights the importance of systematic data collection and analysis for understanding and managing infectious diseases. It also identifies limitations, such as potential reporting bias and the need for more comprehensive data. The dataset is designed for use in systematic reviews, meta-analyses, and predictive modeling, and can be integrated with other data sources for further analysis. The study underscores the need for open access and data transparency in public health surveillance. The dataset provides insights into the epidemiological patterns of SO in China, including the increasing trend and higher incidence in certain regions. The study also emphasizes the importance of interdisciplinary research and collaboration in addressing public health challenges. The dataset is a valuable resource for researchers and public health professionals seeking to understand and manage Salmonella outbreaks. The study was supported by various funding sources, including the National Program on Key Research Project of China and the European Union's Horizon 2020 Research and Innovation Programme. The authors declare no competing interests. The study is published under a Creative Commons Attribution 4.0 International License.