The integration of multi-source data and the establishment of early warning indicator systems constitute pivotal elements for advancing surveillance and early warning capacities in respiratory infectious diseases. Given the multifaceted transmission mechanisms and complex contributing factors inherent in respiratory infectious diseases, surveillance datasets and associated early warning indicators demonstrate notable heterogeneity and sophisticated interrelationships. Furthermore, as surveillance and early warning requirements significantly vary across diverse epidemiological scenarios, accurate assessment of the value and applicability of distinct data types and indicators is imperative. This paper systematically reviews and synthesizes recent advancements in surveillance data and early warning indicators for respiratory infectious diseases, drawing on both domestic and international research. Particular attention is dedicated to analyzing the applicability and efficacy of various data types and indicators within multiple practical contexts, aiming to provide robust theoretical frameworks and methodological guidance to facilitate the development of resilient and efficient surveillance and early warning systems for respiratory infectious diseases.

The integration of multi-source data and the establishment of early warning indicator systems constitute pivotal elements for advancing surveillance and early warning capacities in respiratory infectious diseases. Given the multifaceted transmission mechanisms and complex contributing factors inherent in respiratory infectious diseases, surveillance datasets and associated early warning indicators demonstrate notable heterogeneity and sophisticated interrelationships. Furthermore, as surveillance and early warning requirements significantly vary across diverse epidemiological scenarios, accurate assessment of the value and applicability of distinct data types and indicators is imperative. This paper systematically reviews and synthesizes recent advancements in surveillance data and early warning indicators for respiratory infectious diseases, drawing on both domestic and international research. Particular attention is dedicated to analyzing the applicability and efficacy of various data types and indicators within multiple practical contexts, aiming to provide robust theoretical frameworks and methodological guidance to facilitate the development of resilient and efficient surveillance and early warning systems for respiratory infectious diseases.

Objective:To establish an indicator system for surveillance of data sources to provide a theoretical basis for respiratory infectious disease surveillance and early warning.Methods:Indicators for data sources in the surveillance of acute respiratory infectious diseases were initially compiled through a literature search. Subsequently, two rounds of expert consultations were conducted with 22 experts using the Delphi method to refine the indicators.Results:The questionnaire recovery rates for the two rounds of expert consultation were 100.00% and 86.36%, respectively. The authority coefficient of the experts was 0.83. The coordination coefficient of the second round of Delphi expert consultation was 0.32, and the coefficient of variation of each indicator was less than 0.25. Finally, the indicators system of data source for the surveillance of acute respiratory infectious diseases includes 4 first-level indicators, 10 second-level indicators, and 26 third-level indicators.Conclusion:The indicator system of data sources for the surveillance of acute respiratory infectious diseases constructed in this study is reasonable and reliable, providing a valuable reference for surveillance, early warning and policy formulation of acute respiratory infectious diseases.