Long Covid: Research, Treatments, and Recommendations

Part 2 of the Long Covid Series for Mental Health Professionals

Wednesday, May 31st, from 12:30-2:30PM EDT

2 CE Credits

Presented by Hannah Davis, MPS, and Facilitated by Dr. Zach Radcliff

As we exit the third year of the COVID 19 pandemic, it is clear that the challenge to the population has been overwhelming, and has adversely affected mental health at all ages. We know from past disasters and pandemics that this trauma results in the worsening of anxiety and insomnia. A significant number of people will develop post-traumatic stress symptoms as well as depression. 

DPA is offering a number of continuing education workshops through grant funding received from the American Rescue Plan Act. These workshops will initially focus on post-COVID 19 related trauma. There will be universal communication on the needs of the people during the pandemic and post pandemic. Our initial upcoming CE programs will include the background framework on Covid trauma informed care, universal effective self-help strategies for PTSD, anxiety and stress. Our goal is to develop core content on these important topics that can be delivered to healthcare professionals, students, and members of the public.

This program will cover the most up-to-date research on Long Covid as of 2023, its overlaps with similar viral-onset conditions like ME/CFS and dysautonomia, its overlap with mental health, the current available treatments and best practices, and overall recommendations for providing Long Covid care and doing Long Covid research.

Hannah Davis is a co-founder of the Patient-Led Research Collaborative (PLRC), a team of Long Covid patients with research, policy, data, design, and medical backgrounds. PLRC did the first research on Long Covid in April 2020; their second paper on characterizing Long Covid is in the most viewed medical papers and was highlighted in the announcement of the $1.15 billion in Long Covid funding for the NIH. More recently, they awarded $5 million in grants for biomedical research into Long Covid and ME/CFS, launched a publication highlighting patient-generated hypotheses, and created scorecards for researchers to improve their patient engagement. Hannah has a background in data analysis and machine learning, with a focus on tools for countering bias in machine learning datasets and on generative art & music. She has published papers on Long Covid, sanitation systems, patient-led research models, and translating novels into music.