About: A decision support system for demand management in healthcare supply chains considering the epidemic outbreaks: A case study of coronavirus disease 2019 (COVID-19)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	A decision support system for demand management in healthcare supply chains considering the epidemic outbreaks: A case study of coronavirus disease 2019 (COVID-19)
Creator	Alavi, Behrouz Govindan, Kannan Mina, Hassan
Source	Elsevier; Medline; PMC
abstract	Abstract The disasters caused by epidemic outbreaks is different from other disasters due to two specific features: their long-term disruption and their increasing propagation. Not controlling such disasters brings about severe disruptions in the supply chains and communities and, thereby, irreparable losses will come into play. Coronavirus disease 2019 (COVID-19) is one of these disasters that has caused severe disruptions across the world and in many supply chains, particularly in the healthcare supply chain. Therefore, this paper, for the first time, develops a practical decision support system based on physicians' knowledge and fuzzy inference system (FIS) in order to help with the demand management in the healthcare supply chain, to reduce stress in the community, to break down the COVID-19 propagation chain, and, generally, to mitigate the epidemic outbreaks for healthcare supply chain disruptions. This approach first divides community residents into four groups based on the risk level of their immune system (namely, very sensitive, sensitive, slightly sensitive, and normal) and by two indicators of age and pre-existing diseases (such as diabetes, heart problems, or high blood pressure). Then, these individuals are classified and are required to observe the regulations of their class. Finally, the efficiency of the proposed approach was measured in the real world using the information from four users and the results showed the effectiveness and accuracy of the proposed approach.
has issue date	2020-05-07(xsd:dateTime)
bibo:doi	10.1016/j.tre.2020.101967
bibo:pmid	32382249
has license	els-covid
sha1sum (hex)	70cc908609a00d06d02d5b09b4fac52534488a00
schema:url	https://doi.org/10.1016/j.tre.2020.101967
resource representing a document's title	A decision support system for demand management in healthcare supply chains considering the epidemic outbreaks: A case study of coronavirus disease 2019 (COVID-19)
has PubMed Central identifier	PMC7203053
has PubMed identifier	32382249
schema:publication	Transp Res E Logist Transp Rev
resource representing a document's body	covid:70cc908609a00d06d02d5b09b4fac52534488a00#body_text
is schema:about of	named entity 'COVID-19' named entity 'supply chains' named entity 'OUTBREAKS' named entity 'vomiting' named entity 'COVID-19' named entity 'dry cough' named entity 'fever' named entity 'tiredness' named entity 'infectious disease' named entity 'SARS' named entity 'blockchain' named entity 'Swine flu' named entity 'supply chains' named entity 'sensitivity analysis' named entity 'inference rules' named entity 'inference rules' named entity 'March 2020' named entity 'membership functions' named entity 'pertain' named entity 'membership functions' named entity 'epidemic' named entity 'classes 3' named entity 'membership functions' named entity 'disaster management' named entity 'COVID-19' named entity 'COVID-19' named entity 'outbreaks' named entity 'healthcare' named entity 'COVID' named entity 'supply chain' named entity 'case study' named entity 'COVID' named entity 'epidemic' named entity 'epidemic' named entity 'high blood pressure' named entity 'fever' named entity 'membership functions' named entity 'supply chain' named entity 'WHO' named entity 'United Nations' named entity 'COVID-19' named entity 'Wuhan' named entity 'epidemic' named entity 'high blood pressure' named entity 'tiredness' named entity 'supply chain' named entity 'decision makers' named entity 'membership functions' named entity 'heart problems' named entity 'epidemic' named entity 'heart problems' named entity 'COVID-19' named entity 'viral disease' named entity 'tiredness' named entity 'COVID-19 virus' named entity 'physical condition' named entity 'supply chain' named entity 'membership functions' named entity 'historical data' named entity 'inference rules' named entity 'virus' named entity 'supply chain' named entity 'heart problems' named entity 'human reasoning' named entity 'heart problems' named entity 'inference rules' named entity 'Acar' named entity 'socio-economic' named entity 'heart problems' named entity 'fuzzy logic' named entity 'medical conditions' named entity 'WHO' named entity 'Epidemic' named entity 'neuro-fuzzy' named entity 'dry cough' named entity 'epidemic' named entity 'diarrhea' named entity 'vomiting' named entity 'high blood pressure'

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