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Infoveillance with Dr. Shi Chen

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Manage episode 429131873 series 3569854
Content provided by CIPHER. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by CIPHER or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ro.player.fm/legal.
Episode 7 In this episode, we chat with Dr. Shi Chen, a renowned expert in infectious diseases and health informatics. Dr. Chen shares his fascinating journey from catching bugs in the countryside to tackling global health crises. We dive into his research on big data analytics, epidemic modeling, and the spread of misinformation during the COVID-19 pandemic. Discover how public health communication can improve and the surprising similarities between the spread of diseases and digital misinformation. Tune in for an insightful discussion on the future of health informatics and combating misinformation.

Find out more at cipher.charlotte.edu.

Key Takeaways

  • Shi Chen's interest in science began with his fascination with animals and bugs as a child.
  • He later focused on infectious disease modeling and research in big data analytics, health informatics, and mathematical modeling.
  • Infoveillance is a surveillance method that monitors public opinions and sentiments on the internet to detect potential outbreaks and misinformation.
  • Effective health communication is crucial in addressing public health concerns, and the impact of misinformation on vaccination rates for diseases like COVID-19 and MMR is a lasting concern. The scenario modeling hub is a collaborative effort to standardize data and assumptions for modeling the COVID-19 pandemic.
  • Artificial intelligence has automated data collection and analysis in epidemiology and allows for the integration of high-dimensional datasets.
  • Dealing with social and political aspects of disease outbreaks, such as misinformation and discrimination, is a challenge.
  • Epidemiologists use data mapping to understand spatial and temporal heterogeneities and inform public health decisions.

This podcast was produced and edited by Zack Jackson
CIPHER is a proud part of UNC Charlotte who holds all rights to the content created by this podcast

  continue reading

9 episoade

Artwork
iconDistribuie
 
Manage episode 429131873 series 3569854
Content provided by CIPHER. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by CIPHER or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://ro.player.fm/legal.
Episode 7 In this episode, we chat with Dr. Shi Chen, a renowned expert in infectious diseases and health informatics. Dr. Chen shares his fascinating journey from catching bugs in the countryside to tackling global health crises. We dive into his research on big data analytics, epidemic modeling, and the spread of misinformation during the COVID-19 pandemic. Discover how public health communication can improve and the surprising similarities between the spread of diseases and digital misinformation. Tune in for an insightful discussion on the future of health informatics and combating misinformation.

Find out more at cipher.charlotte.edu.

Key Takeaways

  • Shi Chen's interest in science began with his fascination with animals and bugs as a child.
  • He later focused on infectious disease modeling and research in big data analytics, health informatics, and mathematical modeling.
  • Infoveillance is a surveillance method that monitors public opinions and sentiments on the internet to detect potential outbreaks and misinformation.
  • Effective health communication is crucial in addressing public health concerns, and the impact of misinformation on vaccination rates for diseases like COVID-19 and MMR is a lasting concern. The scenario modeling hub is a collaborative effort to standardize data and assumptions for modeling the COVID-19 pandemic.
  • Artificial intelligence has automated data collection and analysis in epidemiology and allows for the integration of high-dimensional datasets.
  • Dealing with social and political aspects of disease outbreaks, such as misinformation and discrimination, is a challenge.
  • Epidemiologists use data mapping to understand spatial and temporal heterogeneities and inform public health decisions.

This podcast was produced and edited by Zack Jackson
CIPHER is a proud part of UNC Charlotte who holds all rights to the content created by this podcast

  continue reading

9 episoade

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