RESPONDING TO COVID-19
BY DR. JORGE RODRÍGUEZ
health authorities: which population groups should be targeted first and what sequence must be followed to achieve the minimum number of fatalities?
Khalifa University Researchers Develop Model to Determine Who to Vaccinate First against COVID-19 to Reduce Total Fatalities THE OUTCOMES OF THE MODEL SUGGEST PRIORITY BE GIVEN TO THOSE WITH THE MOST CONTACT WITH OTHERS.
After months of unprecedented events and uncertainty due to COVID-19, there’s good news: vaccines are just around the corner. The next dilemma, however, involves distribution of the vaccine to the billions of people around the world. These days, it’s not only a question of manufacturing enough doses, or physically shipping the vials, but rather, who’s first in line? The rapid development of vaccines against the SARSCoV-2 virus is an enormous achievement. Effective and safe vaccines that can be mass produced and distributed to almost the entire population could prevent deaths and boost economic recovery. But vaccinating the world population in a short period of time creates a new challenge for governments and KU TIMES 6
To answer this question, I worked with a team of researchers from Khalifa University to create a mathematical model to simulate the impact of vaccination on fatalities and infection spread across different population groups by age and accounting for the different stages of the COVID-19 disease. The team included myself, Dr. Mauricio Patón, Postdoctoral Fellow, and Dr. Juan Acuña, Associate Professor and Chair of the Department of Epidemiology and Public Health. We evaluated and compared different strategies to determine the most effective possible vaccination priority sequence, with the objective to minimize the total fatalities at the end of the vaccination campaign.
Dr. Jorge Rodríguez Associate Professor of Chemical Engineering at Khalifa University
The COVID-19 outbreak has brought unprecedented attention to mathematical modeling, with the development of several epidemic models trying to forecast the extent of the pandemic.
