Establishment of the global infectious disease surveillance and early warning information system based on multi-data fusion and its preliminary application

OBJECTIVE To address bottlenecks in the infectious disease surveillance and early warning system, such as poor information integration and sharing, as well as outdated response mechanisms, this study aims to construct a global infectious disease surveillance and early warning information system, so as to achieve dynamic perception of biosafety events, one-stop access to relevant background information and rapid and accurate assessment of importation risks.

METHODS Multi-source big data on infectious diseases were collected through web crawlers and literature reviews. Information on time, space, hosts, vectors, diseases and pathogens was standardized and unified. Correlations among diseases, pathogens, hosts, vectors, socio-economic factors and the natural environment were established. Automated risk assessment technology for cross-border importation was embedded, and an information system was developed based on five layers: data acquisition, data extraction and processing, data storage, data analysis and application services.

RESULTS This system monitored biosafety events in real time, including human infectious diseases, animal epidemic diseases and alien species invasion, from 76 open-source websites of 34 organizations or institutions. It integrated historical reporting data on 150 major infectious diseases, 15 categories of host animals, 8 categories of vector organisms, 412 pathogens and 86 animal epidemic diseases, along with influencing factors such as air traffic and sanitary conditions. The system visualized the spatiotemporal distribution of infectious diseases and was able to assess the risk of imported overseas epidemics to each province in China within 5 seconds.

CONCLUSIONS This system embodies the "One Health" concept, effectively integrating multi-source heterogeneous data and linking human-animal-environment factors related to infectious diseases. It significantly improves the timeliness and accuracy of surveillance and early warning, enabling multi-dimensional dynamic perception and rapid risk assessment of emerging infectious diseases. This provides a solid data foundation and technical support for precisely formulating prevention and control strategies.