Haryana

DR.SANJEEV GOYAL OF ARIDABAD DEVELOPED PREDICTIVE MODEL OF DISASTER RESPONSE

November 21, 2017 07:44 PM

Chandigarh (Face2News)

A predictive model of disaster response developed by Dr. Sanjeev Goyal, an Assistant Professor at YMCA University of Science and Technology in Faridabad, has proved to be an effective model in the United States of America for making initial resource requirement estimates needed in the areas affected by river’s flood.

Dr. Goyal has developed this model as a postdoctoral scholar in the University of Pittsburgh, Pennsylvania, United States. The study conducted under the supervision of Dr. Louis Luangkesorn, Assistant Professor (Industrial Engineering) at Pitt’s Swanson School of Engineering, was focused on the use of predictive models in disaster response and proved effective to predict the demands for food and shelter services after the major floods.

Dr. Goyal has developed this model as a postdoctoral scholar in the University of Pittsburgh, Pennsylvania, United States. The study conducted under the supervision of Dr. Louis Luangkesorn, Assistant Professor (Industrial Engineering) at Pitt’s Swanson School of Engineering, was focused on the use of predictive models in disaster response and proved effective to predict the demands for food and shelter services after the major floods.

Initial results of the model have been used to inform response to floods in Oklahoma and Missouri State floods of the summer 2017 in the United States. With the help of this prediction model, American Red Cross was having initial estimate of finances needed, which is the most critical thing for them on day ‘0’ of riverine floods. This model also helped them to plan openings of shelter and food requirements. Further, work is intended to prepare the model for use by disaster response agencies in making initial resource requirement estimates in areas impacted by flooding rivers.

YMCA University Vice Chancellor, Prof. Dinesh Kumar has congratulated Dr. Goyal on the successful completion of his project. He said that model of prior estimation of resources required for disaster response is an important study which can reduce the mortality rate due to floods in the Country.

It may be noted that Dr. Goyal had received support from University Grants Commission for the one-year fellowship, which started in October 2016. The work was done with the advice and assistance of Mr. Michael

Whitehead, Government Operations Manager at American Red Cross.
While detailing about his study, Dr. Goyal said that in the early days of a disaster, the deployment of state and national resources into the disaster area is often delayed pending a request for resources from local agencies.

“The delay can be lengthened because local personnel are conducting response operations for the first time. However, it may be possible to initiate movement of resources into an affected region if an estimate of the needs can be prepared. After that, local agencies make specific requests when preliminary assessments are completed. Predictive models promise to provide these types of estimates”, he added.

To develop a predictive model, Dr. Goyal and Dr. Luangkesorn have used demographic, physical, and historical data that was readily available outside of the disaster area on the first day of a disaster. Demographic data was represented by the Social Vulnerability Index maintained by the U.S. Centers for Disease Control and Prevention. Physical damage impacts were represented by the National Weather Service – Advanced Hydrologic Prediction Service historical and current flood gauge data. Historical data was available from American Red Cross damage assessment and feeding and sheltering operations from past major floods. Dr. Goyal analyzed river flood data from more than 186 counties and 550 rivers gauges.

The model seeks to predict the damage to residences and the resulting needs for food and shelter. This prediction can then be used to initiate the assignment of supplies, personnel, logistics, and financial resources to disaster relief. Efforts can be refined as more information is available. 

If data is available, Dr. Goyal has intensions to develop similar model for India, so that more lives can be saved in a scenario like infamous Chennai floods. Furthermore, work is underway to convert this model into a Mobile App under which the Local Disaster Manager will just have to input the location and he can get prediction in terms of how many people will come to shelter, how many houses will be destroyed and how much food is required. This will help to select the warehouse location as well. This model will not only save lives of people, but also help to manage finances.

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