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Disaster-prone Philippines endures an estimated 20 typhoons annually, five of which can cause major damage, floods and landslides. Hence, the Philippines needs to have an efficient, effective and well-coordinated system for disaster preparedness and relief operations.

Unfortunately, its archipelagic landscape complicates the coordination of disaster operations. Of its 7,107 islands, only 2,000 are home to roughly 100 million people. Even with years of experience dealing with natural disasters, the government faces challenges in implementing humanitarian efforts.

The onslaught of Tyhpoon Yolanda in November 2013 caused total economic damage of US $288 million and more than 6,000 deaths. Tacloban Airport was heavily damaged and rendered unusable. For the first four days, relief aid didn’t arrive by air to Tacloban City, the worst hit city.

In any disaster, four days is a long time to take when providing immediate assistance to the affected population. The time required in giving relief to the affected can actually be shortened by pre-positioning relief supplies in strategic locations even before disaster strikes. Pre-positioning can increase the nation’s preparedness to respond to natural disasters, especially typhoons.

With the current boom of IT systems, access to information is not a problem for most humanitarian organizations. The challenge lies on how to intelligently process all this information to devise the best plan for rapid humanitarian response.

The current decision-making process during disasters involves manual processes to collate relevant information on available relief goods and affected populations. Based on the information gathered, a plan can be devised to allocate available supplies. Route maps are manually drawn to deliver goods to municipalities affected by the typhoon.

However, some parts of the transportation network can be disabled, post-disaster, complicating the relief process. Hence, pre-positioning decisions have to take into account the potential unavailability of some transportation routed, as was the case in Typhoon Yolanda.

With relief operations having inherently high uncertainty and complexity, using traditional methods to coordinate disaster operations can lead to an inefficient system, with high costs, duplication of efforts, wastage of resources and ineffective slow response and unsatisfied demand response.

During disasters, there is very little time and increased difficulty in moving relief supplies from the source to the affected population. Strategically pre-positioning goods based on historical, forecasted and up-to-date information would ensure that enough relief goods are delivered to the affected municipalities immediately after the disaster.

The Ateneo de Manila University, the University of Michigan and IBM Philippines have lately collaborated to develop a geographical information system (GIS)-based, decision-support tool that can be used to prepare for and respond to a disaster scenario. The project is titled “Pre-positioning and Allocation of Relief Supplies GIS-Based Support System for Disaster Preparedness and Response.”

Replacing manual methods being used today, the tool that we are developing is based on a mathematical optimization model that can prescribe schemes for pre-positioning and allocation of relief supplies. We hope our tool can facilitate centralized decisions for Philippines disaster response operations.

A fundamental component of this decision support tool is the optimization model that takes in input parameters such as candidate transportation hubs, distances, projection of affected municipalities and populations and warehouse capacities, among others.

Our optimization model is implemented in a computer program that will process the input data and can be configured using various parameters to reflect real world scenario. The model takes only a few seconds to solve and the output is plotted and logged into an output file.

As involved parties, we will partner with both government and private institutions to gather relevant data on weather models, hazard maps and population density to feed in the optimization model.

The optimization models output will be made accessible in a cloud-based decision support tool for use in disaster planning. In this system, the tool will automatically fetch data from the IT database of the Department of Science and Technology and Department of Social Work and Development.

In case live data is unavailable, the tool can still function independently by allowing users to encode data manually, import from available files or even use previous data stored in the cloud.

Reports and results of simulation can be exported and viewed locally without Internet connection, using document viewers and map viewers like Google Earth.

All sensitive data will be encrypted in the database. To preserve data integrity, user access is restricted through authentication.

An efficient humanitarian operations program is a pressing need in disaster-prone Philippines. In humanitarian operations, we face a high degree of uncertainty that can occur during disaster scenarios.

One factor crucial in determining where to pre-position relief goods is demand forecasting. This is a process that basically involved estimating the affected population of a forecasted disaster. Usually, demand forecasting is translated from weather forecasts.

While there are sophisticated weather forecasting models available to predict typhoon tracks, these forecasts are subject to high uncertainty, thus demand forecasting is also highly changeable.

During disasters, providing much-needed supplies is uncertain, due to the intermittent nature of relief goods, such as irregular donations. Many humanitarian organizations move within the same landscape, but each has different advocacies and strategies for delivering aid.

The success of this project will not rely solely on the efficiency of the tool that will be created. Existing challenges need to be addressed to make the tool useful to decision makers.

Many disasters have hit the Philippines and enough historical and practical information have been collected to conduct a more scientific analysis on disaster response. Scientists and researchers can utilize previous information and apply their knowledge to craft solutions to significantly reduce the country’s vulnerability to natural calamities.

The project’s goal is to apply mathematical models to aid the decision-making process in disaster operations. With the new tool the project is creating, decision makers can hopefully come up with intelligent, knowledge-based decisions based on the most up-to-date information.

The project believes that making available relief supplies at the soonest possible time and with the most efficient use of available resources, can contribute greatly to building resiliency during disasters. The project offers a tool that will facilitate achieving this goal.

These projects hope to ensure that in the future, Filipinos can witness less delays and hassles in giving relief to the disaster-afflicted. Filipinos are assured of smooth and proactive response through right positioning and allocation of relief supplies using the process generated by our mathematical model.

Dr. Reinabelle C. Reyes
Ateneo de Manila University

Published by:
Department of Science and Technology-Science and Technology Information Institute (DOST-STII)