New framework for the surveillance and early warning of influenza: fixed individuals regular reporting mechanism

Influenza is an acute respiratory infection caused by the influenza virus. Influenza is not only a major burden on human health, but also a major public health challenge, so it is very necessary to conduct surveillance and early warning of influenza. However, the existing monitoring system is mainly based on sentinel monitoring, which has some limitations in information feedback and reliability. Other new monitoring systems also have shortcomings such as insufficient representation and comprehensive coverage. Therefore, we propose a regional influenza surveillance method based on fixed individuals. This method refers to the epidemic characteristics of influenza, selects representative fixed monitoring individuals, and makes them directly upload their physical conditions on a regular basis to judge the occurrence or not of influenza, and determines the judgment method of the severity of influenza. Our proposed method can detect influenza timely and accurately and give early warning, and make more effective use of health resources, which is of great significance for the development of influenza surveillance system. In addition, the monitoring of influenza will play an important role in the monitoring and early warning of new infectious diseases. Importantly, the surveillance method based on fixed individuals can provide a theoretical basis for the cross-sectional study of infectious diseases and make up the gap in the cohort study of infectious diseases. Meanwhile, the collection of symptom information mentioned in this method is conducive to updating the etiological information and summarizing the epidemic characteristics of influenza, providing further support for the early warning and prevention of influenza. Significance StatementWe propose a new method for monitoring influenza epidemics by regularly reporting the health status of individuals and propose criteria for different levels of influenza alert severity. Our results validate the feasibility of this method, which can detect influenza timely and accurately and make early warning, and use health resources more effectively. The results of this study provide a new perspective for the surveillance of emerging infectious diseases and provide theoretical support for the cohort study of infectious diseases.