DLSU researchers develop distribution support model to optimally allocate drugs and COVID vaccine once available

Published October 22, 2020, 4:21 PM

by Dhel Nazario

A decision support model that aims to provide an analytical and systematic approach in the allocation of COVID-19 drugs and hopefully vaccines once it becomes available was presented in a webinar led by the Dela Salle University Data Science Institute on Thursday, Oct. 22. 

Project Lead Dr. Charlle Sy of the Industrial Engineering Department of the DLSU, said that she along with her team during the onset of the pandemic, witnessed how the current healthcare system got overwhelmed with the surge of COVID-19 cases.

“News outlets were reporting how hospitals have started to turn away patients and patients had to go from one hospital to another, just to look for empty spaces or empty beds,” Sy said.

“And during that time. People were hoping that a vaccine would soon be developed… I guess we’ve come to realize that vaccines are a long way to go. And when that vaccine becomes available. The actual distribution is an entirely different problem,” she added.

Sy mentioned that during that scenario, medical practitioners, pharmaceutical companies turned to repurposing commercially-available drugs like Remdesivir, to treat COVID patients which are only limited.

“Everything that we have is limited in quantity, even if we want to distribute these drugs, even if we want to accommodate all patients, there’s simply enough or not enough supply to go around,” she said.

Sy recalled that this became a topic of their group when the entirety of Luzon was placed under an enhanced community quarantine (ECQ).

“One of the questions was that: How do we actually allocate these resources, do we give them to the most vulnerable? Those that probably would be under the senior age category? Or do we give them to those that would have the highest chance of surviving the disease?” she said. 

Being in the field of engineering, Sy and her team thought that there must be an analytical approach that will allow them to address the issue in a more systematic manner. They then decided to formulate a model that would address the questions while also considering multiple factors such as patient fatalities, drug efficiency, and hospital capacity.

According to them, simulations show that using an optimal allocation plan was found to be better than simply allocating the drugs for a particular purpose when necessary.

“We want to get the word out there that we’re doing something like this, because we believe that other people could help us enrich this by giving their own ideas and their own insights,” Sy said.

She added that the logical next step now is to translate their present findings to vaccine allocations as it is anticipated to be developed in the future and that the allocation is a huge problem that needs to be tackled in an analytical way.

They also aim to engage potential stakeholders in the industry.

“This work couldn’t be done by a single group. If more groups are working on it, then there’s a better chance that it gets the objective that it wants to achieve,” Sy said.

In August, the country reserved three million vaccines worth at least P1.5 billion through the Gavi COVID-19 Vaccines Global Access (COVAX) facility, a mechanism designed to guarantee rapid, fair, and equitable access to COVID-19 vaccines worldwide.

COVAX requires that the country commits to a minimum of three percent of the population but assured that up to 20 percent can be procured once the vaccine becomes available.

Department of Science and Technology – Philippine Council for Health Research and Development Executive Director Dr. Jaime Montoya said three percent will be used for healthcare workers, frontliners, while the remaining 17 percent will be for high risk people like the elderly. The remaining 80 percent will then be negotiated.  

The webinar was presented together with Animo Labs Foundations Inc., a DLSU technology business incubator for the commercialization of research projects, inventions, and creative ideas.