Emerging data suggest that the effects of infection with SARS-CoV-2 are far-reaching, extending beyond those with severe acute disease. Specifically, the presence of persistent symptoms after apparent resolution from COVID-19 has frequently been reported throughout the pandemic by individuals labeled as long-haulers. Long-haulers represent a very significant public health concern, and there are no guidelines to address their diagnosis and management. The objective of this project is to understand the long-term physical and mental influences of COVID-19 via data science tools. In this project, Using data collected from various sources, including electronic health records, social media posts, we study the differences in COVID-19 manifestation, the associations between long-haul symptoms, and risk factors that may contribute to becoming a COVID-19 long hauler.

Project information

  • Category: Future Healthcare, Population Models, and Translation and Practice
  • Contact Person: Melissa Pinto
  • Partners: UCLA
  • Funding: