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Fostering New Scientific Networks in the COVID Era and Beyond.

Mabruka AlfaidiHanrui ZhangSuellen Darc Oliveira
Published in: Arteriosclerosis, thrombosis, and vascular biology (2022)
Over the last 2 years, the COVID-19 pandemic has stimulated the scientific community by starting a race to develop new vaccines and therapeutic approaches to fight this life-threatening illness. At the same time, the pandemic also evoked an urge for innovative communication strategies to maintain scientific networking and data sharing among investigators. Communication through audiovisual platforms has quickly become a unique tool to sustain scientific interaction, whereas social media has turned into an unmistakable pivotal environment for sharing scientific data and combating misinformation around SARS-CoV-2 infection, prevention, and therapy. Amid this challenging scenario, the scientific community organically established new roles, such as a social media ambassador, a conference-associated role to virtually promote breakthrough science while reconnecting investigators and forging new scientific networks via social media. Moreover, in response to the COVID-19 pandemic, it also became clear the critical need for the scientific community to support efforts to empower flexibility, creativity, and the inclusion of new forms of communication to advance science. Thus, the goal of this brief article is to provide a structured follow-up on the importance for researchers to occupy the internet to promote scientific findings and events, to combat science mistrust by stimulating communication among nonscientists to scientists, and to provide essential strategies for young and senior investigators on how to virtually expand their professional networks within and across research and clinical areas of the cardiovascular field.
Keyphrases
  • social media
  • health information
  • public health
  • healthcare
  • coronavirus disease
  • sars cov
  • mental health
  • electronic health record
  • stem cells
  • machine learning
  • cell therapy
  • respiratory syndrome coronavirus
  • deep learning