An update on avian influenza in poultry

Capua, Ilaria; Alexander, D. J.

doi:10.1016/j.ics.2004.02.012

Cited by 2 publications

(2 citation statements)

References 4 publications

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“…Articles were retrieved from literature searches in PubMed, Biological Abstracts, Agricola, and ScienceDirect [1,3,4,6,9–12,16,18–20,25–66]. The first search strategy in PubMed used the keywords “influenza in birds”, “avian influenza”, and “disease outbreaks”; this resulted in 685 hits, 40 of which were reviewed.…”

Section: Methodsmentioning

confidence: 99%

“…The urgency with which decisions and actions (including resource allocations for response) are required may be influenced by current and predicted local morbidity and mortality [16–17], estimations of current and projected economic losses (due to bird death), and problem scope [18]. Assessments may provide a combination of qualitative (expert opinion) and quantitative (rates and biostatistical) measures that may be of help to decision makers [6, 19–20].…”

Section: Introductionmentioning

confidence: 99%

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A proposed taxonomy for characterization and assessment of avian influenza outbreaks

Mohammed

Lehmann

Kim

2009

International Journal of Medical Informatics

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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 achieve effective collaboration, 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 when possible, using the Unified Medical Language System MetaMap.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.

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