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10.3390/ijerph17113973

http://scihub22266oqcxt.onion/10.3390/ijerph17113973
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32503333!7312089!32503333
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suck abstract from ncbi


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pmid32503333      Int+J+Environ+Res+Public+Health 2020 ; 17 (11): ä
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  • A Visual Approach for the SARS (Severe Acute Respiratory Syndrome) Outbreak Data Analysis #MMPMID32503333
  • Hua J; Wang G; Huang M; Hua S; Yang S
  • Int J Environ Res Public Health 2020[Jun]; 17 (11): ä PMID32503333show ga
  • Virus outbreaks are threats to humanity, and coronaviruses are the latest of many epidemics in the last few decades in the world. SARS-CoV (Severe Acute Respiratory Syndrome Associated Coronavirus) is a member of the coronavirus family, so its study is useful for relevant virus data research. In this work, we conduct a proposed approach that is non-medical/clinical, generate graphs from five features of the SARS outbreak data in five countries and regions, and offer insights from a visual analysis perspective. The results show that prevention measures such as quarantine are the most common control policies used, and areas with strict measures did have fewer peak period days; for instance, Hong Kong handled the outbreak better than other areas. Data conflict issues found with this approach are discussed as well. Visual analysis is also proved to be a useful technique to present the SARS outbreak data at this stage; furthermore, we are proceeding to apply a similar methodology with more features to future COVID-19 research from a visual analysis perfective.
  • |*Data Analysis[MESH]
  • |*Internationality[MESH]
  • |Consensus Development Conferences as Topic[MESH]
  • |Disease Outbreaks/*prevention & control/*statistics & numerical data[MESH]
  • |Hong Kong/epidemiology[MESH]
  • |Humans[MESH]
  • |Infection Control[MESH]
  • |Quarantine/*statistics & numerical data[MESH]
  • |Severe Acute Respiratory Syndrome/*epidemiology/*prevention & control/transmission[MESH]
  • |Time Factors[MESH]


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