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A proposal for a computer-based framework of support for public health in the management of biological incidents: the Czech Republic experience
V. Bures, T. Otcenásková, P. Cech, K. Antos,
Language English Country United States
Document type Journal Article, Research Support, Non-U.S. Gov't
NLK
ProQuest Central
from 2009-01-01 to 2018-11-30
SAGE Publications Journals
from 1999-01-01 to 2015-12-31
Nursing & Allied Health Database (ProQuest)
from 2009-01-01 to 2018-11-30
Health & Medicine (ProQuest)
from 2009-01-01 to 2018-11-30
Health Management Database (ProQuest)
from 2009-01-01 to 2018-11-30
Public Health Database (ProQuest)
from 2009-01-01 to 2018-11-30
SAGE Journals
from 2012-01-01 to 2012-05-31
- MeSH
- Disease Outbreaks statistics & numerical data MeSH
- Disasters * MeSH
- Food Contamination analysis MeSH
- Humans MeSH
- Decision Support Techniques * MeSH
- Biohazard Release * MeSH
- Public Health Informatics methods standards MeSH
- Public Health methods standards MeSH
- Water Pollution analysis MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Geographicals
- Czech Republic MeSH
AIMS: Biological incidents jeopardising public health require decision-making that consists of one dominant feature: complexity. Therefore, public health decision-makers necessitate appropriate support. METHODS: Based on the analogy with business intelligence (BI) principles, the contextual analysis of the environment and available data resources, and conceptual modelling within systems and knowledge engineering, this paper proposes a general framework for computer-based decision support in the case of a biological incident. At the outset, the analysis of potential inputs to the framework is conducted and several resources such as demographic information, strategic documents, environmental characteristics, agent descriptors and surveillance systems are considered. RESULTS: Consequently, three prototypes were developed, tested and evaluated by a group of experts. Their selection was based on the overall framework scheme. Subsequently, an ontology prototype linked with an inference engine, multi-agent-based model focusing on the simulation of an environment, and expert-system prototypes were created. CONCLUSIONS: All prototypes proved to be utilisable support tools for decision-making in the field of public health. Nevertheless, the research revealed further issues and challenges that might be investigated by both public health focused researchers and practitioners.
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