China CDC Conducts Advanced Training Workshop on Mathematical Modeling for Emerging Infectious Diseases

From May 20 to 23, 2025, the Public Health Emergency Center of the Chinese Center for Disease Control and Prevention (China CDC), in collaboration with the National Key Laboratory for Pathogen Traceability, Early Warning and Intelligent Decision-Making, hosted the second session of the Advanced Training ProgramWorkshop on Mathematical Modeling for Emerging and Re-emerging Infectious Diseases in Nanning, Guangxi. More than 50 technical professionals from provincial (including autonomous regions and municipalities) and selected municipal CDCs across the country participated in the program.

 

The opening ceremony was presided over by Deputy Director Xiang Nijuan of the Public Health Emergency Center, who shared feedback received from participants of the first session. The current session was designed in response to that feedback, with a greater emphasis on enhancing modeling skills using R programming. Through guided code interpretation, the training aimed to help participants transition from understanding mathematical formulas to independently building models. The curriculum also featured case-based discussions to explore the essential components and applicability contexts of various models, reinforced by hands-on simulation exercises. This comprehensive approach aimed to systematically strengthen participants’ understanding of model construction and application. Trainees reported that the program successfully integrated theoretical depth with practical utility, with content covering over 90% of their actual work needs. The training received consistently high satisfaction ratings..

 

The training faculty included experts from the China CDC, the London School of Hygiene & Tropical Medicine, Fudan University, the National Centre for Infectious Diseases (Singapore), and New York University. In his closing remarks, Li Qun, Deputy Director of the China CDC, emphasized the importance of leveraging digital and intelligent technologies to strengthen the public health emergency response system. He encouraged participants to align their learning with key challenges in disease prevention and control, and to contribute to a more scientific and precise approach to infectious disease prevention.