Georgi D. Gospodinov, PhDSr. Data Scientist, Wal-Mart Stores Inc.

Chris ShannonSr. Data Scientist, Tata Consultancy Services

Aidan McGuireCEO at ScraperWiki Ltd and HDX Product

Manager at UN OCHAJavier Teran

Statistician at United Nations OCHAAndrej Verity

Information Management Officer UN OCHAand

an international group of data science volunteers

Nepal Earthquake AnalysisAid Relief Coverage, Severity

Index, and Aid Capacity Index

September-December, 2015United Nations OCHA

http://www.inform-index.orghttp://www.osgeo.org

http://www.worldpop.org.ukhttps://data.hdx.rwlabs.org

Nepal Earthquake Analysis: Table of Contents

Table of Contents: Introduction and Background

• Humanitarian Data Exchange: Data Collection Process• Humanitarian Systems Interaction • 2015 Nepal Earthquake Disaster at a Glance• Casualties and Injuries in the Nepal Earthquake

Aid Agencies and Disaster Relief for Nepal• Nepal Earthquake Disaster Relief Analysis • Agency-VDC Aid Network Construction• Properties of the Agency-VDC Aid Network

Definition and Estimation of Need for Aid• Definition of Need for Aid and Initial Model• Severity Model Background: Hazard and Exposure• Severity Model Background: Vulnerability

Aid Coverage Analysis• Need for Aid Analysis at VDC Level: Heatmap• Need for Aid Analysis at VDC Level: Coverage

Agency-VDC Aid Capacity Index• Agency-VDC Aid Capacity Index Construction• Agency-VDC Aid Capacity Index Analysis

Conclusions

Introduction and BackgroundHumanitarian Data Exchange: Data Collection Process

https://data.hdx.rwlabs.org

Humanitarian Systems Interaction

http://digitalhumanitarians.com/content/what-we-do-0

Introduction and Background

2015 Nepal Earthquake Disaster at a Glance Introduction and Background

http://www.icimod.org/nepalearthquake2015

Casualties and Injuries in the Nepal Earthquake

http://data.unh cr.org/nepal/

Introduction and Background

Nepal Earthquake Disaster Relief Analysis

UN’s Initial appeal for aid to assist with Nepal disaster: $415 million• The Nepalese government lead the response through the National Emergency

Operations Centre (NEOC) with support from the United Nations and international community

• The $415 million was just for the first three months of operations in Nepal• Food ($128 million), health ($75 million) and shelter ($50 million) would make up the

majority of the spending• The main aims were to combat outbreaks of communicable diseases, to ensure the food

needs were being met and to build basic shelters• This $415 million was to address immediate need and did not include much money for

rebuilding

Aid Agencies and Disaster Relief for Nepal

http://www.un.org/apps/news/story.asp?NewsID=50725#.Vxx6wmPC5GJ

Agency-VDC Aid Network Construction

Overview:• The Nepal disaster prompted

nearly 80 major agencies to send some type of aid (in the form of supplies, food, assistance, money, etc.) to about 800 distinct Village Development Committee (VDC) districts. There were many channels of aid delivery, and the distribution of aid varied in amount, diversity, and number of different contributing agencies.

• We depict the agency providing the aid and the particular VDC district receiving the aid, with the heatmap showing the districts with most aid received

• We used data from all sources on the first page (HDX, WorldPop, and OSGeo/qGIS, see title page) to represent the VDC map accurately

• We used aid data to overlay the abstract aid agency representation

Aid Agencies and Disaster Relief for Nepal

Properties of the Agency-VDC Aid Network Aid Agencies and Disaster Relief for NepalAid Agency Network:• Distinct aid instances: Min. 1st Qu. Median Mean 3rd Qu. Max. 1.00 5.50 18.00 40.64 40.00 256.00 • Distinct targeted VDCs with aid: Min. 1st Qu. Median Mean 3rd Qu. Max. 1.00 4.00 9.00 17.67 22.50 127.00 • Shared VDCs with a given agency: Min. 1st Qu. Median Mean 3rd Qu. Max. 0 5 11 13 20 53• Weighted Shared VDCs:Min. 1st Qu. Median Mean 3rd Qu. Max. 0.00 12.00 32.00 51.89 76.00 364.00

VDC Aid Network:• VDCs with common aid source: Min. 1st Qu. Median Mean 3rd Qu. Max. 0.00 24.00 68.00 75.86 113.00 309.00 • Weighted VDCs with common source: Min. 1st Qu. Median Mean 3rd Qu. Max. 0.0 48.0 136.0 157.5 226.0 662.0

Definition and Estimation of Need for Aid Definition of Need for Aid and Initial Model

Severity = (Hazard x Exposure × Vulnerability)^ (1/3)Assume Need is proportional to SeverityAssume Need is inversely proportional to (Distance to Epicenter) ^(1/3)Assume Need is inversely proportional to (Health Care Facilities) ^(1/3)

Need Stats: Min. : 0.000 1st Qu. : 0.570 Median : 1.860 Mean : 4.197 3rd Qu. : 5.595 Max. : 85.530

• Estimating how well the supplied aid has met the need for each VDC district is a difficult task because it is hard to quantify need. The effort in this work is to outline a measure of relative need for aid among VDC districts and to compare how well aid resources were distributed accordingly.

• We define need using the severity index which incorporates measures such as hazard level, exposure level, and vulnerability: all quantities characterizing the pre-existing conditions for the population, the distance to epicenter, and the weighted density of health centers.

http://www.inform-index.orghttp://www.inform-index.org/InDepth/Methodology

Severity Model Background: Hazard and Exposure

Severity Model Background: Hazard & ExposureThe hazard & exposure dimension reflects the probability of physical exposure associated with specific hazards. There is no risk if there is no physical exposure, no matter how severe the hazard event is. Therefore, the hazard and exposure dimensions are merged into hazard & exposure dimension. As such it represents the load that the community has to deal with when exposed to a hazard event. The dimension comprises two categories: natural hazards and human-induced hazards, aggregated with the geometric mean, where both indexes carry equal weight within the dimension.

Definition and Estimation of Need for Aid

http://www.inform-index.orghttp://www.inform-index.org/InDepth/Methodology

Severity Model Background: Vulnerability

Severity Model Background: VulnerabilityThe impact of disasters on people in terms of number of people killed, injured, and made homeless is predominantly felt in developing countries while the economic costs of disasters are concentrated in the industrialized world. The Vulnerability dimension addresses the intrinsic predispositions of an exposed population to be affected, or to be susceptible to the damaging effects of a hazard, even though the assessment is made through hazard independent indicators. So, the vulnerability dimension represents economic, political and social characteristics of the community that can be destabilized in case of a hazard event. Physical vulnerability, which is a hazard dependent characteristic, is dealt with separately in the hazard & exposure dimension.

Definition and Estimation of Need for Aid

http://www.inform-index.orghttp://www.inform-index.org/InDepth/Methodology

• This model is a measure of relative need as absolute need values are exceedingly challenging to estimate.

• The primary conclusion is that need is in a large part determined by pre-existing conditions and risks and thus can be anticipated and prepared for.

Aid Coverage AnalysisNeed for Aid Analysis at VDC Level: Coverage

% VDCs that Received Aid From Each Group: Low Need, Medium Need, High Need :• Low Need: 64.1%• Medium Need: 33.0%• High Need: 2.9%

Aid Coverage AnalysisNeed for Aid Analysis at VDC Level: Coverage

• Our basic findings are that the distribution of aid agencies shows that some VDCs received aid from as many as 12 agencies, with the average number of agencies supplying aid per VDC equal to 2.

• From the Medium to High Need VDCs, only about 70% received some type of aid, while from the Low Need VDCs, only about 40% received some type of aid, according to the data record.

• This raises the question of coordinating aid distribution and creating a consolidated aid coverage of a region. Especially for areas with high estimated need and a single agency aid source.

• The figure depicts all the VDC regions where aid was not distributed or was distributed in very limited quantities thus creating a deficit of disaster relief.

• Comparison with the available resources reveals opportunities for a more efficient and effective aid delivery, which is a subject of ongoing study.

Agency-VDC Aid Capacity Index Construction

Aid Capacity Index is a function of the weighted sum of the VDC Degree in the Aid-Agency Network, weighted by each Agency’s Hub score

Agency-VDC Aid Capacity Index

Agency-VDC Aid Capacity IndexThe need distribution and aid coverage analysis raise the question of coordinating aid distribution and creating a consolidated aid coverage of a region. Especially for areas with high estimated need and a single agency aid source. The problem is creating adequate aid coverage of a region prior to disaster, using pre-existing conditions to help inform us of the expected level of need in case of a disaster.

Agency-VDC Aid Capacity IndexAgency-VDC Aid Capacity Index Analysis

Agency-VDC Aid Capacity Index Analysis• Near liner distribution agency distribution overlap• Highly non-linear aid distribution density• Pre-existing factors such as vulnerability and severity

index good indicators for aid capacity estimation since they capture secondary effects of infrastructure, access to medical aid, food, and supplies

• Aid capacity can largely be impacted prior to a disaster, with a global map for aid delivery channels

Nepal Earthquake Analysis: Conclusions

Conclusions:• Humanitarian data efforts enable the global impact

of data for humanitarian purposes• Aid agencies and disaster relief coordinators have

many opportunities to improve the process to address need for aid more effectively

• The need for aid distribution is largely dependent on pre-existing conditions

• Aid coverage is a highly complex non-linear process• Agency-VDC Aid Capacity Index is a way to capture

the potential ability for appropriate aid coverage to a region should disaster occur