Philippines' relief ops to get boost with UP transport network model

Scientists from the University of the Philippines (UP) used a 300-year-old math discipline to create a transport network model targeted to improve the country’s typhoon disaster response and relief operations.

In “network science,” lines that connect two points are called edges, while the points at which the lines intersect are called nodes. Edges and nodes create a graph, which can be applied to a variety of modeling applications including disaster relief, according to a press release of the UP College of Science. 

UP scientists Dr. May T. Lim, Dr. Reinabelle C. Reyes, and independent researcher JC Albert Peralta used the concepts to model transport networks, allowing them to calculate the most efficient ways to distribute relief packages in typhoon-stricken areas.

Roads and sea routes were represented as edges in the study while the intersections between roads and sea routes were nodes.

A test of the model in the Visayas Region showed that Northern and Eastern Samar are the most vulnerable provinces to delay, taking as much as 12 hours for relief packages to arrive in the affected areas.

It also showed the extent of the vulnerability of the Visayas transport network, with 30 out of 251 towns adversely impacted after at least 1% of the total nodes became inaccessible. Almost all towns in the region were affected when 5% of the nodes were shut down.

“We emphasize the need for a more decentralized and proactive form of relief logistics such as prepositioning relief goods, especially in or nearer to towns most vulnerable to disconnection,” the UP scientists said.

Further, they launched a prototype app to exhibit the potential of the model for nationwide application.

Only the Visayas network system is currently available in the app but the scientists said more transportation networks are expected to be released soon.

“It is our hope that policymakers will harness this potential for informed decision-making, strategic cost-benefit analysis for infrastructure investments, and effective data-driven transportation planning to enhance resilience in the face of future disasters,” they added.—LDF, GMA Integrated News