Predicting COVID Infectivity
Thursday, February 11, 2021
11:00 am - 12:00 pm
About the Event:
The COVID-19 pandemic has been impacting the United States since the beginning of 2020. In just several months, total confirmed cases have reached 6.3 million, with more than 190,000 deaths across the nation. The numbers are increasing every day.
To tackle this crisis, the priority of the nation is to flatten the curve. There are multiple ways to flatten the curve, including practicing social distance, self-isolation and wearing a mask. However, the number of confirmed cases is still growing every day due to the public’s lack of awareness of the severity of this disease.
People who use PCIC’s dashboard will have more visibility regarding the risk of contracting COVID in their area, and will practice social distancing, self-isolation and wearing a mask compared to people who do not have access to the dashboard.
David S. Buck, M.D., M.P.H., UH College of Medicine
David S. Buck, M.D., M.P.H., is an associate dean for community health at UH’s College of Medicine, adjunct professor at The University of Texas Health Science Center at Houston (UTHealth) School of Public Health: Management, Policy and Community Health Division and Rice University’s department of Sociology.
Li (Betty) Gai, Senior Data Analyst
Li (Betty) Gai is the Sr. Data Analyst at the Patient Care Intervention Center (PCIC) and has been with the organization since August 2015. As part of her graduate course work, she worked on a project to visualize data and build dashboards for data discovery and patient selection. Upon graduation with an advanced degree in Business Analytics at Southern Methodist University, Dallas, she joined the PCIC to pursue her passion in data science and apply her knowledge in public health. Gai is experienced in database design, deployment and ETL process management, dashboard and report design and advanced machine learning.
Jacky Chan, Junior Data Analyst