Avian Influenza A virus in ducks migrating through Sweden

Avian influenza virus: of virus and bird ecology

The recent introductions of highly pathogenic avian influenza (HPAI) H5N1 virus in wild birds and its subsequent spread throughout Asia, the Middle East, Africa and Europe has put a focus on the role of wild birds in the geographical spread of HPAI H5N1 virus. Large-scale surveillance programs are ongoing to determine a potential role of wild birds in H5N1 virus spread and to serve as sentinel systems for introductions into new geographical regions. The unprecedented scale and coverage of these surveillance programs offer a unique opportunity to expand our current knowledge on the ecology of LPAI in wild migratory birds. We provide an update on the current knowledge on the relation between host and virus ecology.

A proposed taxonomy for characterization and assessment of avian influenza outbreaks

PURPOSE

The speed and high potential impact of avian influenza's (AI) on local bird populations, poultry economies and human health make timely and coordinated characterization, assessment and response to possible threats essential. To collaborate effectively, stakeholders (public health, medical, veterinary, and agricultural professionals) must be able to communicate and record findings, assessments, and actions in a standard fashion. We seek to discern a taxonomy of concepts and relationships that are important to the stakeholder community when sharing information about the characterization and assessment of an AI outbreak, according to a consistent and common perspective, interpretation, and level of detail.

METHODS

To derive concepts relevant to AI characterization and assessment, we reviewed selected journal articles, reporting and laboratory forms, and public health websites associated with AI case reporting. We mapped concepts to existing medical terminologies within the Unified Medical Language System when possible, using the National Library of Medicine's MetaMap program.

RESULTS

From 54 distinct information sources, we extracted 1113 concepts, of which 533 mapped to 15 medical terminologies; 580 did not map to specific terminologies. Using a combination of semantic type-relationship matching and expert consensus, we constructed the proposed taxonomy, with linkages to existing terminologies where pragmatic.

CONCLUSION

The proposed taxonomy describes core knowledge, data and communication needs for the characterization and assessment of AI outbreaks in the context of existing medical terminologies across different domains. We also describe areas for further work.