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GUIDANCE NOTE Household and Building Damage Assessment December 2019

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Page 1: Household and Building Damage Assessment

GUIDANCE NOTE

Household and Building Damage Assessment

December 2019

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Table of Contents _Toc28010279

Table of Contents ................................................................................................................................................. 1

1. HBDA Key Actions and Relevant Sections to Read .................................................................................... 3

2. What is the Household and Building Damage Assessment (HBDA)? ........................................................ 5

A. What is the HBDA? ................................................................................................................................... 5

B. The HBDA Toolkit ..................................................................................................................................... 5

C. The HBDA in the Assessment Cycle & Decision-Making............................................................................. 6

D. Limitations: Potential Issues to Bear in Mind .............................................................................................. 7

3. Preparation for the HBDA .......................................................................................................................... 10

A. Rapid Context Evaluation ........................................................................................................................ 10

B. Assessment Working Group, Core Team, & Coordination ......................................................................... 10

C. HBDA Core Team & Resources ............................................................................................................... 11

D. Model Work Plan ..................................................................................................................................... 13

4. Secondary Data Review ............................................................................................................................. 15

A. Objectives ............................................................................................................................................... 15

B. Conducting the SDR ............................................................................................................................... 15

C. Type of Information and Sources for the HBDA ........................................................................................ 16

5. Methodology & Assessment Design ......................................................................................................... 19

A. Methodology and Data Analysis Plan ....................................................................................................... 19

B. Sampling Strategy ................................................................................................................................... 21

C. Adaptation of the Data Collection Tool ..................................................................................................... 24

6. Data Collection .......................................................................................................................................... 26

A. Preparation for Data Collection & Enumerators’ Training .......................................................................... 26

B. Day-to-Day Management ........................................................................................................................ 27

C. Mobile Data Collection and Kobo Toolbox ................................................................................................ 28

7. Data Analysis ............................................................................................................................................. 29

A. Data Cleaning and Processing ................................................................................................................ 29

B. Data Analysis ......................................................................................................................................... 30

C. Analysis Tools for Visualization................................................................................................................ 32

D. Information Products, Target Audience, & Dissemination ......................................................................... 33

Annex 1: Definitions ........................................................................................................................................... 35

Annex 2: Reference Documents ......................................................................................................................... 37

Annex 3: Information Management, Visualization, Mapping and Navigation Tools .......................................... 38

Annex 4: Terms of References (ToR) of the HBDA Team .................................................................................. 39

ToR, Program Lead/ Assessment Coordinator ................................................................................................... 39

ToR, Assessment Officer .................................................................................................................................. 39

ToR, Information Management/ GIS Officer/ Remote Sensing Analyst ................................................................ 39

Annex 5: Templates ............................................................................................................................................ 40

Data Cleaning Logbook .................................................................................................................................... 40

Data Management Plan .................................................................................................................................... 40

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Methodology Note ............................................................................................................................................ 42

Annex 6: HBDA Hardware and Software Requirements .................................................................................... 45

Annex 7: UNDP-UNOSAT Standard Operating Procedures ............................................................................... 48

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1. HBDA Key Actions and Relevant Sections to Read

This summary outlines key actions to be undertaken in the Household Building Damage Assessment (HBDA). It can serve as a checklist for steps and considerations for conducting a HBDA, as well as direct readers to the appropriate sections of the handbook for each action. The full handbook provides theoretical foundation as well as practical guidance, tools and resources for practitioners.

Action Handbook Section

1. Decide whether a HBDA may be appropriate

Understand what the HBDA can do and what is available in the HBDA toolkit.

1A. What is the HBDA? 1B. The HBDA Toolkit 1D. Limitations: Things to Bear in Mind

Decide whether it is appropriate to launch a HBDA, based on information needs, resources, and how it fits within the humanitarian response.

1C. The HBDA in the Assessment Cycle and Decision-Making 1D. Limitations: Things to Bear in Mind

Conduct an initial review of basic information about the crisis, to help determine scope and feasibility of the HBDA.

2A. Rapid Context Evaluation

Advocate with the government and international actors for a HBDA, which should be conducted upon the request of the government.

2A. Rapid Context Evaluation

2. Prepare to conduct a HBDA

Establish the HBDA Core Team (with full involvement of relevant UNDP country office colleagues), which will run the HBDA on a day-to-day basis.

2C. HBDA Core Team & Resources 2B. Assessment Working Group, Core Team & Coordination Annex 4: Terms of References for the HBDA Team

Work with relevant stakeholders through an Assessment Working Group (AWG). Ensure all AWG members are trained on the HBDA toolkit.

2B. Assessment Working Group, Core Team & Coordination

Organize the stakeholders to contribute to the HBDA with human, data, and financial resources.

2B. Assessment Working Group, Core Team & Coordination

Create a workplan to estimate timeframe of the HBDA from inception to dissemination of findings, as well as assign tasks.

2D. Model Work Plan

Conduct an in-depth Secondary Data Review (SDR), including collating and analyzing information on pre-existing damage as well as already collected in-crisis data. This should clearly identify information gaps and provide a baseline of information for comparison with HBDA data.

3A. SDR Objectives 3B. Conducting the SDR 3C. Type of Information and Sources for the HBDA Annex 7: UNDP-UNOSAT SOPs

Clarify and agree the final HBDA objectives and use of its data for humanitarian and recovery, including the relationship with other assessment processes (e.g. MIRA, PDNA etc.), and how it contributes to recovery frameworks, donor requirements, strategic planning.

3A. SDR Objectives 1C. The HBDA in the Assessment Cycle and Decision-Making

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3. Design the HBDA

Decide on the HBDA coverage and methodology (including sampling strategy and research questions). The scope and sampling strategy can be selected based on the four scenarios developed for the HBDA which depend on available resources and objective of the assessment.

4A. Methodology and Data Analysis Plan 4B. Sampling strategy Annex 5: Templates

Select appropriate indicators and questions from the HBDA library of questions. Adapt any context-specific indicators.

C. Adaptation of the Data Collection Tool HBDA library of questions

Adapt and test the questionnaire using Kobo Toolbox and the HBDA templates, including selecting a server and setting up a dedicated account. Ensure the questionnaire if reviewed by stakeholders.

5C. Mobile Data Collection and Kobo Toolbox

Make sure the above are outlined in the following documents: (1) Methodology, (2) Data Analysis Plan, and (3) Data Management Plan.

4A. Methodology and Data Analysis Plan

4. Collect HBDA data

Complete any HR, administrative, logistical and related tasks for data collection (e.g. hiring enumerators, preparing equipment and training venues).

5A. Preparation for Data Collection & Enumerators’ Training

Ensure that Assessment Officers, GIS Officers are proficient in the use of Kobo Toolbox and are able to train enumerators.

5C. Mobile Data Collection and Kobo Toolbox

Train enumerators on mobile data collection, including general principles, practical aspects of the HBDA and the data collection questionnaire.

5A. Preparation for Data Collection & Enumerators’ Training

Launch data collection and manage this on a day-to-day basis, keeping track of progress on an ongoing basis.

5B. Day-to-Day Management

5. Analyze HBDA data and share findings

Clean data on a daily basis according to defined cleaning protocols. At the end of data collection, conduct a comprehensive final review of the dataset.

6A. Data Cleaning and Processing

Conduct the four phases of data analysis: description, explanation, interpretation / operationalization, and early warning & preparedness.

6B. Data Analysis

Visualize findings using Microsoft Power BI, and adapt existing dashboard templates. Consider other conventional GIS platforms to further analysis.

6C. Analysis Tools for Visualization

Compile findings into other information products as requested / relevant. This may include a final report, datasets, factsheets and profiles, dashboards, infographics and maps.

6B. Data Analysis 6D. Information Products, Target Audience & Dissemination Annex 3: IM, Visualization, Mapping and Navigation Tools

Share and disseminate findings and information products in collaboration with the government.

6D. Information Products, Target Audience & Dissemination

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2. What is the Household and Building Damage Assessment (HBDA)?

A. What is the HBDA?

Natural disasters and conflicts affect buildings and infrastructures, e.g. residential houses, schools, hospitals, police

stations, and businesses, which in turn has an impact on local communities. In this context, one of the most challenging

and crucial components of the recovery process is the rehabilitation of these structures based on reliable data on the

level of damage. In addition, humanitarian crises result in significant needs among affected populations in others

humanitarian sectors, including Health, Food Security, Education, and Water, Sanitation, and Hygiene (WASH).

The United Nations Development Programme (UNDP) with the support of IMPACT Initiatives has developed

this Household and Building Damage Assessment (HBDA) toolkit to facilitate the assessment of buildings and

infrastructure affected by crises (http://www.undp.org/content/buildingdamageassessment/en/home.html), as well

as assess a series of basic socio-economic indicators in Health, Food Security, Education, and WASH at the

household level. The HBDA allows prompt collection of digital and georeferenced data on damage to infrastructures

and residential and commercial buildings, household vulnerabilities, utility services, and needed materials for repairs.

The toolkit is designed to be flexible and if started early, can produce valuable information for the Post Disaster Needs

Assessment (PDNA)12, especially for the housing, community infrastructure and social sectors.

The HBDA is a comprehensive and multiphase process that involves mobile data collection through enumerators,

followed by data analysis, visualization and dissemination for use by national and local authorities, humanitarian and

development partners. The library of questions within the HBDA is designed to be adaptable to different contexts. It

includes a priority rating per indicator that enables flexible management of the length of the data collection tool,

depending on available resources and government priorities. The analysis produced by the HBDA aims to inform

government prioritization of relief and recovery resources, serve for strategic and operational humanitarian and

recovery planning, as well as produce evidence for raising awareness and advocacy (see Part 6).

This Guidance Note presents the tools necessary for the implementation of the HBDA, including the HBDA

toolkit, the Kobo Toolbox (https://www.kobotoolbox.org/), and the analysis and visualization application

Microsoft Power BI (https://powerbi.microsoft.com/fr-fr/). Additional applications to potentially enhance HBDA

capabilities and/or allow greater flexibility are listed in Annex 3.

B. The HBDA Toolkit

The HBDA relies on mobile data collection, using the Kobo Toolbox – an open-source platform that allows rapid

information gathering using smartphones or tablets and facilitates the post-collection data analysis. Once data

collection is complete, the data is cleaned, analyzed, and deployed to Microsoft Power BI, an intelligence platform for

data analysis and visualization. Data and associated analysis from the HBDA are also exportable to other platforms.

The HBDA data collection tool relies on a library of questions with seven modular sections: A – Building Location

(15 questions), B – Building Use and Household Information (138), C – Building Size (7), D – Building Materials (20),

E – Building Damage and Repairs (24), F – Building Services and Debris (30), and G – Building Preparedness (9). The

full library of questions has over 240 questions.

1 2 For more information on the PDNA, see UNDP, 2014

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It should be noted that not all questions will be asked in each HBDA. The length of the data collection tool will

vary depending on available resources within the assessment team, the information needs, and the access situation

in the particular context. The core of the HBDA includes sections A, C, D, E, and F, which will likely be part of all

HBDAs.

Section B is a standalone household and infrastructure assessment that allows collection of granular indicators at the

household and individual infrastructure (e.g. hospital, school) level. It is therefore by far the largest section. Section G

is the preparedness section, which may not be relevant in every context.

To simplify indicator selection, the library of questions includes a priority column that ranks each indicator on

a 1 to 3 scale. The indicators ranked 1 are considered the most vital while the indicators ranked 3 may be omitted if a

lighter assessment is conducted. It should be noted that this ranking is indicative and may change depending on

context. Specific ways in which the data collection tool may be adapted are explained in Part 4.C but may for instance

include expanding the data collection tool with more sectoral questions.

C. The HBDA in the Assessment Cycle & Decision-Making

The HBDA should fit within the larger framework of the humanitarian response, deployed when:

• a new crisis emerges and results in building damage, or

• there is a sudden or substantial change in an existing crisis which leads to building damage.

Conducting the HBDA will help inform the response to a crisis if:

• additional information on damage to buildings is required for operational or strategic decision-making, or

• contingency planning is undertaken

The HBDA may vary in depth, research method, time frame, and cost. It is thus a flexible and adaptable assessment

that can be deployed at different moments in a crisis (see Figure 1).

Figure 1: HBDA Timing

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The assessment team should keep this distinction in mind when launching the HBDA, as the phase of deployment of

the HBDA will impact on its objectives, length, and the indicators selected from the library of questions for the data

collection tool (see Part 4).

Table 1: Rapid and In-Depth HBDAs

Rapid HBDA In-Depth HBDA

Timing of launch

• Rapid assessment phase (1-3 weeks) of a sudden onset disaster.

• Ideally by the end of the search and rescue phase.

• In-depth assessment phase (>one month) of a sudden onset disaster.

• Depending on context as necessary in conflict and complex crises, for example after a flare-up in conflict intensity leading to significant damage.

Aims • Immediately build a robust evidence base to inform decision making.

• Collect data on the most affected populations and areas to inform the immediate response in shelter, livelihoods, access to basic services, rehabilitation of community infrastructure, etc.

• Inform the housing and infrastructure sections of Post-Disaster Needs Assessments that would normally start 2 weeks after a disaster (see for on the assessment cycle, UNHCR, 2017).

• In conflict and complex crises, collect data geared towards recovery and durable solutions to the crisis, developing a joint understanding with affected populations on long-term recovery needs.

• In later stages of a sudden onset disaster, collect granular data on affected populations and areas to inform response strategy and coordination.

• If conducted at regular intervals, the HBDA may become a monitoring tool for reconstruction, recovery and even preparedness.

Tools • Exclusive building damage assessment, omitting Section B from the library of questions. It may only focus on identifying shelter needs soon after a disaster.

• Comprehensive set of indicators from the library of questions, likely to result in a longer questionnaire, data collection period and resources required.

1Finally, the HBDA will always be deployed by UNDP in coordination with the national and local governments

as well as international and local humanitarian partners. In various cases, the HBDA may rely on resources

provided by partners, including enumerators and support on analysis to make it a joint needs assessment. In this

regard, the HBDA’s library of questions and methodology use agreed standards, including geographic tagging and

harmonized sectoral indicators, to allow for cross-analysis with other data collection exercises (see Annex 1 for

definitions and see for reference on types of needs assessments, UNHCR, 2017; and on coordinated and joint

assessment, Inter-Agency Standing Committee, 2012).

D. Limitations: Potential Issues to Bear in Mind

• Enumerators/ Data Collection Tool: A typical challenge in damage assessments is the need to ensure

appropriate, comprehensive, and standardized training for enumerators, in order to mitigate biases related to the

subjective perception of damage.

o It is important to make all possible efforts to have structural engineers join as enumerators, otherwise the

findings of the HBDA cannot be taken as a technical evaluation of the buildings’ structural integrity.

o Though it integrates some key sectoral indicators, the HBDA is not a true multi-sectoral assessment and

can only provide an overview of needs at the household level. It is recommended that people with

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expertise on the sectors covered by the HBDA are enrolled as enumerators and participate in designing

the methodology.

o It is important to enroll the appropriate number of enumerators. If there is a lack of enumerators, the

HBDA will take a longer time to complete.

• GPS Accuracy: The highest level of accuracy using mobile phones is at best 5m. However, this might not be

possible to obtain if the GPS signal is weak or interfered with (for example, if signal is obstructed by buildings).

This makes it nearly impossible to assign the collected GPS points for structures to their precise location on the

map in GIS, either using satellite imagery or Open Street Map. A unique ID is hence required.

o The issue of GPS readings registering with a delay and leading to incorrect detections may be mitigated

by setting a required GPS accuracy threshold or adding the obligation for the enumerator to register a

second GPS reading at the end of the assessment. If the enumerator’s phone is online, the accuracy of

the GPS reading improves.

o Note: It is possible to include a metadata field for the accuracy of each recorded GPS point.

• Mobile Data Collection: Kobo Toolbox allows for online and offline data collection on both the smartphones’

browser and the Kobo Collect Android application. Despite this, the HBDA suffers from the traditional limitations

of mobile data collection, including difficulty to manage qualitative data, possible stress for respondents in

answering through a mobile device, security risk for enumerator and respondent due to being seen with a mobile

device in some contexts, risk of the device being rendered inoperable (lost, stolen, out of battery), cost of procuring

and deploying the devices, and need for procurement of power banks.

o Ideally, the questionnaire should be fully finalized and approved by all stakeholders before starting data

collection with the Kobo platform. If changes to wording or options are made once data collection has

started, this can cause difficulties with the live dashboard feature within the Kobo platform.

• Connectivity: In some contexts, there may be extremely low bandwidth, or even worse, none. In such cases, it

may be worth considering using the raw suite of Open Data Kit (ODK) applications which Kobo it built on. ODK

Collect, an alternative Android data collection application, and ODK Briefcase, an offline data aggregator, can be

used in tandem in such cases with minimal changes to the HBDA workflow. These allow upload and download of

survey forms to mobile phones or tablets without requiring internet connection.

• Mapping: By default, Kobo Toolbox uses Open Street Map as an embedded base map. However, Open Street

Map is not up to date in every context.

o In order to capture every building and facilitate the work of enumerators, it may be possible to have Open

Street Map updated based on recent satellite or drone imagery. It is also possible to customize map data,

which can also work offline, depending on project needs.

o Further, there are additional ODK-based data collection applications geared specifically toward spatial

data collection, for instance GeoODK and Open Map Kit, which may present further opportunities for the

HBDA.

• Navigation: Navigation in some contexts can be difficult. There is no native navigation component to the Kobo

Toolbox. Therefore, it is often useful to use a separate application to navigate the areas to be assessed, as well

as organize enumeration teams and distribute work assignments.

o There are multiple applications that can support this, including Maps.me, SW Maps, MAPinr, which should

be evaluated further for their suitability for the HBDA.

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• Unique Identification Numbers: Although during the pilot exercise Kobo Toolbox generated unique identification

(UID) numbers for buildings and households, further research is needed to develop the logic for HBDA UIDs.

These UIDs should allow for identification of different members of the same household living in different buildings,

as well as capturing information about multiple-household buildings.

• Data Rich vs. Data Poor Environments: The core HBDA methodology is adapted more toward data poor

environments, in which relatively little spatial data related to infrastructure exist, and GPS data must be collected.

However, in data rich environments, it may be possible to obtain detailed building information, including digitized

footprints and address registries. In such cases, attempts should be made to collect building damage data against

these datasets or databases using either existing unique building identifiers or new unique IDs that can allow the

datasets to be joined together reliably.

• Needs Assessments: Challenges in needs assessments include the need to ensure adequate sampling

strategies, train enumerators on avoiding leading questions, the risk of respondents consciously manipulating the

answers to orient the type and scale of aid, and the need to recruit specialized enumerators and have a gender

balance among them (see for reference on challenges in needs assessment, UNHCR, 2017).

Key Takeaways

• HBDA’s seven sections: A – Building Location (15 questions), B – Building Use and Household Information

(138), C – Building Size (7), D – Building Materials (20), E – Building Damage and Repairs (24), F – Building

Services and Debris (30 questions), and G – Building Preparedness (9).

• The Library of questions includes a priority column that ranks each indicator on a 1 to 3 scale, giving

an indication of its importance.

• HBDA’s data collection normally starts 1-4 weeks after a sudden-onset disaster during the rapid

assessment phase but can also be deployed later as an in-depth assessment and at regular intervals for

monitoring,

• Two major limitations to the HBDA to bear in mind:

o GPS accuracy using Kobo Toolbox is a problem

o Need for specialized enumerators e.g. structural engineers in assessment teams, to ensure that

findings can be used as technical evaluations of the buildings’ structural integrity

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3. Preparation for the HBDA

A. Rapid Context Evaluation

In the HBDA, as in any assessment, there is a two-step secondary data review (SDR) – all the data that is

exterior to the HBDA – that needs to be conducted. The first step should be done quickly (1-2 days) at the

onset of the assessment process to determine the feasibility of the HBDA. Conversely, the second part of the

SDR is done during the data collection phase (see Part 3 and see for reference on context overview, UNHCR, 2017).

The first step of the SDR comes in parallel to reaching out to the government and other stakeholders, which is crucial

for obtaining data and information related to the context as well as ensuring buy-in of the process. This also forms the

first step of organizing stakeholders to contribute to the HBDA with human and financial resources. Advocacy with the

government and international actors can be facilitated through using the following tools from the HBDA toolkit: two-

pager on the HBDA, HBDA website, examples from previous assessments to demonstrate the added value provided

(including screenshots of Power BI dashboards, powerpoint presentations, factsheets etc).

The first part of the SDR is a review of basic information about the crisis. It involves quickly analyzing the existing

pre-crisis and in-crisis data collected by other actors, including humanitarian NGO and UN agencies, national or local

governments, civil society, faith-based organizations, satellite imagery (e.g. UNOSAT, Copernicus), crowdsourcing,

social media (e.g. QCRI social media analysis). The aim is to build an understanding of the context, of the crisis drivers,

and of the main information gaps. It is hence possible to determine whether the HBDA is needed given information

already available, as well as whether it is feasible given access constraints. It also helps identify which methodology is

possible, which HBDA components will be utilized to best address the information needs with the available time and

resources. It is important to conduct this process before launching the HBDA as it may well be that there is

either no need for a damage assessment, or that the situation is such that the HBDA is not possible due to

access constraints.

Checklist for the HBDA’s Feasibility in the Rapid Context Evaluation

For the HBDA to be relevant, timely, and needed after/ in a crisis, the following conditions need to be met:

✓ Access is possible to affected areas with regard to security and local authorities’ support for the HBDA

✓ The crisis has resulted in damage to buildings i.e. collecting information on shelter is a priority

✓ No other damage assessment is ongoing or has been completed in the last month/ since the outbreak of

the crisis. If so, evaluate the extent to which the HBDA would be able to collect relevant additional

information.

✓ Enough enumerators and resources (expert staff, funding, equipment for mobile data collection, etc.) is

available in UNDP to conduct the HBDA. If this is not the case, consider pooling resources with partners.

B. Assessment Working Group, Core Team, & Coordination

If the HBDA is both relevant and feasible, the next step is to

1. Establish the HBDA Core Team with full involvement of relevant UNDP country office colleagues (see

section C for details);

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2. Work with relevant stakeholders through an existing Assessment Working Group (AWG) or by

establishing one.

The AWG usually includes technical experts seconded from partner humanitarian organizations (UN agencies, ECHO,

INGOs, LNGOs, etc.) and local authorities (ministries, disaster management agencies, institute of statistics, structural

engineers, etc.). UNDP may co-lead the AWG with the relevant government counterpart.

Ideally, all AWG members should receive a training on the HBDA and familiarize themselves with the HBDA toolkit.

They should all be linked up through a WhatsApp group and other potential coordination channels (mailing list, Skype

group, Microsoft Teams, etc.).

The AWG should not duplicate existing assessment working groups and, to the extent possible, integrate into them in

order to pool resources for the HBDA and build synergies with other sectoral and multi-sectoral assessments, e.g.

MIRA and PDNA.

The AWG should prompt discussions with partners on methodologies and data collection tools and the development

of a joint analysis framework for the interpretation of findings.

Finally, the AWG should ensure that the HBDA Core Team, which runs the HBDA on a day-to-day basis, is regularly

liaising with relevant counterparts from other agencies, humanitarian clusters or sectors, and the local authorities.

The HBDA Core Team should engage with the AWG at all key stages of the HBDA process. At minimum, the

following points should be discussed with the AWG:

✓ Clear objectives on information needs, keeping in mind the purpose of the needs assessment

✓ Coverage (populations, sectors, and geographic areas)

✓ Type of decision-making that needs to be informed

✓ Timeframe for the start and end of data collection

✓ Methodology, including for data collection and analysis, data collection tools, analysis plan

✓ Coordination and division of responsibilities shown in an organigram

✓ List and mapping to engage stakeholders among national and local authorities

✓ Communication to all stakeholders, particularly the authorities, about the objectives and limitations of the

HBDA

✓ Ensure the link with PDNA and other relevant needs assessments with appropriate data, indicators and

timeframe

C. HBDA Core Team & Resources

The HBDA Core Team is part of the AWG and is in charge of carrying out the HBDA. Tasks include to set

objectives, identify necessary technical expertise, design the questionnaire, the data collection and visualization

platform, coordinate data collection and analysis activities, share findings to inform response planning and

programming, and report back to persons of concern.

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The Core Team is a gender-balanced multifunctional team with sector experts and relevant technical specialists who

understand the local context. The HBDA Core Team Leader may also co-lead the AWG. The composition of the HBDA

Core Team may also change from one context to another depending on specific needs to be assessed. Team roles

can be filled by either national or international staff, with representation of national experts strongly encouraged to

ensure ownership and context sensitivity, among others. Aspects to be considered for team composition include

diversity (ethnical, gender) understanding of local political economy and stakeholders, local language and technical

expertise (e.g. fluency in the languages of the assessed areas, data literacy, understanding of technical indicators).

Table 2 below provides a list of the main roles in the HBDA Core Team. Team members may also fill more than one

role. Annex 4 provides the Terms of References (ToR).

Table 2: Description of Roles in the HBDA Core Team

Team Lead/

Assessment

Coordinator (AC)

o Lead and coordinate assessment teams

o Liaise with external actors/ stakeholders to manage expectations around the HBDA

o Build consensus on the goals, information gaps, methodology and data analysis plan

o Plan/ mobilize financial, logistics and human resources

o See Team Leader TOR in the annexes for more details

Assessment Officer(s)

(AO)

o Coordinate steps in the HBDA (methodology, SDR, data collection/ cleaning, analysis)

o Conduct access and context analysis, and integrate SDR information into the HBDA

o Develop the data collection tools/ briefing and de-briefing enumerators

o Coordinate the data collection process, including progress tracking and troubleshooting

o See Assessment Officer TOR in the annexes for more details

Information

Management (IMO)/

GIS Officer(s) (GISO)/

Remote Sensing

Analyst (GISO)

o Perform GIS/ Satellite imagery analysis

o Support design of data collection tools, especially for mobile data collection, sampling

frameworks, data storage systems, and analytical products

o Support analysis/ generating data visualization products, including dashboards, infographics,

and maps, especially using Power BI

o See IM / GIS Officer TOR in the annexes for more details

Cluster Technical

Expert(s)/ Advisor(s)

(CA)

o Provide sector expertise for the indicators and analytical framework

o Conduct sectoral needs analysis and contribute to multi-sectoral analysis

o Check the collected data on damage by structural engineers and shelter experts

o Brief/ de-brief with enumerators on technical indicators, including damages coding

Admin (A)/ Finance

(F)/ Logistics (L) Staff

In close collaboration with the AOs and UNDP CO management and operations manager

o Set in place and coordinate the assessment logistics

o Establish required human resources, ICT and other elements to carry out the HBDA

Liaison(s) (national

staff) and Team

Leader(s) for

Enumerators’/

o Conduct translations when needed for the data collection tools

o Support on context and access analysis, using local sources, social media, etc.

o Coordinate the work of enumerators in the field

o Facilitate contacts with local and national authorities

Enumerators (national

staff) (E)

o Collect data in the field

o Support on context and access analysis

Table 3 below now provides a repartition of the main responsibilities in the HBDA Core Team.

Table 3: Responsibility Assignment Matrix of the HBDA Core Team for Key Tasks in the HBDA (A –

Accountable; R – Responsible; C – Consulted; I – Informed)

AC AO(s) CA

IMO/

GSO A/L/A ETL E

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Context Evaluation A/R C C C I C I

AWG/ Stakeholders A/R C C C C I I

SDR C A/R C R I C I

Methodology A R C R I I I

Enumerators'

Training C A/R C R C I I

Data Collection A R C C C I I

Data Cleaning C A/R C R I I I

Data Analysis C A/R C R I I I

Information Products A R C R I I I

Dissemination A/R R C R I I I

Deciding to conduct the HBDA has budgetary implications. Any HBDA budget should include an estimate of

supplies, personnel, training, transportation, communications, and security requirements. The cost of the HBDA should

be proportionate to the scale and scope of the crisis and expected benefits for the population of concern. If the HBDA

involves resources provided by partners, decisions have to be taken on how to pool and utilize them. Due consideration

should be given to the use of existing resources within communities of concern and ensuring whenever possible that

persons of concern are engaged in planning and implementing assessments.

Since the HBDA involves mobile data collection, attention should be given to the equipment for enumerators, including

in providing smartphones/ tablets, GPS devices, power banks and identifying t-shirts, vests, and caps. In damage

assessments, enumerators may need to be provided with measuring tapes/ meters.

Enumerators may be employees from UNDP, UN, national and international organizations and government. These

institutions can also recruit enumerators to carry out the assessment and mobilize volunteers (e.g. university students,

private citizens, etc.).

D. Model Work Plan

Table 4 provides an estimated number of days for the steps of the HBDA from inception to dissemination of findings.

Some of these steps are likely to be conducted in parallel by different members of the HBDA Core Team. Overall, the

HBDA should take between 3 and 6 weeks depending on its scale and methodology.

o Context evaluation: 1-2 days

o AWG Set-up and Stakeholder Engagement: 2-4 days

o SDR: 3 days and then monitoring until then end of the HBDA

o Methodology Development: 2 days

o Enumerators training: 1-3 days

o Data Collection: 1-2 weeks

o Data Cleaning: 1-2 days at the start of data collection, ongoing throughout the data collection process, and 2

days at the end

o Data Analysis: 4 days-1 week

o Report, Maps, and Other Information Products Production: 4 days-1 week

o Findings Dissemination: 1-3 days after end of data analysis but is likely to start earlier

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Table 4: Indicative Work Plan for the HBDA (dark grey: minimum time; light gray: maximum time)

HBDA Weeks 1st 2nd 3rd 4th 5th -

6th

(days) 1 2 3 4 5 6 7 1 2 3 4 5 6 7 1 2 3 4 5 6 7 1 2 3 4-

7

Context

Evaluation

AWG Set Up

SDR Ongoing

Methodology

Training

Data Collection

Data Cleaning

Data Analysis

Information

Products

Dissemination

Key Takeaways

• Conduct a rapid context evaluation to assess the feasibility of the HBDA

• Establish the Assessment Working Group (AWG) that develops the plan for the HBDA, liaises with

stakeholders, and coordinates the assessment team

• The assessment team includes a Program/ Assessment Lead; Assessment Officer(s); Cluster Technical

Expert(s); Information Management/GIS Officer(s); Admin/Logistics/Finance Staff; Team Leaders for

Enumerators; Enumerators

• The completion of HBDA should take between 3 and 6 weeks

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4. Secondary Data Review

A. Objectives

The secondary data review (SDR) is a rigorous process of collating existing data and information on the

affected population and areas of focus of the HBDA synthesizing this information, and conducting analysis

(see Tables 4 & 5). In line with the HBDA design and methodology, the SDR establishes what is known and unknown

about the situation and its impact. It is then possible to identify information gaps by comparing the existing consolidated

data to the information needs that were agreed in the data analysis plan (see Part 4.A). For more information on the

SDR process see DEEP Secondary Data Review Basics.

For damage assessments in natural disasters, the SDR includes the aim to collect information on the

magnitude of the phenomenon, including wind speed, path, and level of precipitation for cyclones, epicenter location

and depth, aftershocks, and potential for tsunami, landslides, for earthquakes, speed of the lava flow and level of

airborne ash in volcanic eruptions, and other information in other natural disasters. In armed conflicts, the SDR aims

to gather information on the intensity of the fighting, especially of indirect and aerial fire.

For the HBDA, it is particularly important to have in-crisis information available through satellite imagery. Thus,

specific techniques may be used to assess damages in hard-to-reach areas or immediately after the crisis before the

HBDA is deployed, including remote sensing for in-depth damage assessment and determination of other visual

characteristics of geographical areas of interests. Remote sensing requires appropriate satellite imagery and/ or aerial

photographs, combined with expertise in imagery analysis and knowledge of the ground situation (see for reference

on remote sensing and satellite imagery best practices, UN-Spider Portal, 2019; CIEDRS, 2003; Copernicus, 2019).

UNDP relies on support from the UNOSAT for immediate crisis response (see Annex 7).

The SDR is therefore a key component of the HBDA. It ensures that all available secondary data, including on pre-

existing damages to buildings and already collected in-crisis data, is used before investments are made to collect

primary data. It moreover contextualizes the HBDA primary data by providing a baseline.

An SDR should be updated throughout the humanitarian crisis as more information about the crisis becomes available,

strengthening situation awareness among humanitarian actors. It is recommended that the AWG maintain an updated

secondary data review throughout the HBDA and a registry of completed and ongoing data collection exercises

(sometimes called a survey of surveys (SOS)) (see for reference on assessment registry, ACAPS, 2011).

B. Conducting the SDR

To undertake an SDR in a coordinated manner, a best practice is to form an analysis team involving agencies

and stakeholders with sectoral expertise and knowledge of the local context. The analysis team will support joint

analysis with an agreement on the findings and output of the analysis.

The SDR has two main stages, which are broken down further into sub-stages:

• Gathering the Data

✓ Identifying relevant sources

✓ Reading through the sources and extracting information

✓ Storing and organizing this information per topic

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• Analyzing the Data

✓ Trimming the text by checking the information for reliability and credibility, selecting the most

important information, and the most relevant one for the HBDA

✓ Analyzing the information to identify cross-sectoral priorities, areas and sectors to focus for the

HBDA, especially looking at baseline and preparedness information relating to Shelter

✓ Identifying information gaps, non-assessed areas and sectors

✓ Developing scenarios on the crisis’ evolution, assessing the humanitarian caseload, finding

cross-sector priorities, identifying main assessment needs for the HBDA, including in terms of

coverage and sectors

An SDR is usually structured to present: (1) comparison of pre and post-disaster situations, (2) evaluation of the

quality of the information available, (3) sectoral sheets (relevant sectors should be selected based on the scope of the

HBDA), (4) humanitarian and displacement profiles as relevant, (5) lessons learned from previous similar disasters, (6)

country profile, (7) stakeholder profiles, (8) timeline of events, and (9) discussion of operational and access constraints.

Once information gaps have been identified in the SDR, discussion can begin on what primary data should be collected

in the HBDA, how, and by whom. In the HBDA, it would likely come down to deciding how the data collection tool needs

to be adjusted, in particular with regard to including or not Section B on sectoral needs, and what sampling strategy

needs to be selected (see Part 4.C and see for reference on how to conduct an SDR, ACAPS, 2014).

C. Type of Information and Sources for the HBDA

For the HBDA, the SDR is particularly important as it not only helps collect contextual information on the

disaster or conflict, but also on the pre-crisis situation of residential building and infrastructure. This may

include updated lists of public infrastructure and building locations (schools, hospitals, etc.), as well as on their status

and level of maintenance before the crisis. The goal is to assess if buildings were already showing damage before the

crisis, as well as understand the most common construction materials used in this context, their resilience to the crisis,

the impact of previous disasters on the infrastructure and buildings, and the potential type of disaster waste that may

be present. The SDR also collects information on any initial damage assessments already conducted through remote

sensing.

Common sources of secondary information include other humanitarian and development actors, as well as

government, civil society organizations, and educational and research institutes. Tables 5 & 6 below provide a

list of sources of information for pre-crisis and in-crisis data and GIS. In all cases, it is always important to assess

the secondary sources’ reliability, credibility, and confidentiality (information can be used publicly) before

integrating them into the SDR for the HBDA.

Online resources for SDR and SDR methodology include ACAPS.org, DEEP (deephelp.zendesk.com/hc/en-us),

Humanitarianresponse.info, Humanitarian Data Exchange (HDX, data.humdata.org), Reachresourcecentre.info,

Reliefweb.int, and various cluster-specific websites.

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Table 5: Sources of Information for the Secondary Data Review (Qualitative and quantitative)

Pre-Crisis Sources of Information In-Crisis Sources of Information

Population-related information (demographics and needs)

o National institutions (ministries, academia, national

statistics bureau)

o Large surveys (DHS, MICS, census)

o International development institutions

o National or municipal contingency plans

o UN, local/ international NGOs reports and datasets

o Previous Flash appeals, HNOs/HRPs

o Assessments conducted before the disaster by REACH

Initiative available at reachresourcecentre.info

o Analysis, economic or intelligence reports (e.g.

cia.gov/library/publications/the-world-factbook)

Building and infrastructure-related information

o National or municipal housing bureaus

o Shelter assessments conducted before the disaster by

REACH Initiative (reachresourcecentre.info) or other

agencies

Crisis-related information

o Online databases, the international disasters database

(emdat.be), preventionweb.net, Centre for Research on

the Epidemiology of Disasters (cred.be)

o After Action Reviews

o DevInfo, world development indicators, MDGs

o Monitoring, Early warning and Surveillance systems, e.g.

on unisdr.org, wmo.int, fewsnet.org

Population-related information (demographics and needs)

o Media reports, social media

o National institutions, ministries, Local Emergency

Management Agency (LEMA), chamber of commerce

o Assessment reports from local/ international NGOs,

including MIRA, DTMs,

o Funding Appeals, Strategic Response Plans

o Situation reports (OCHA, clusters, government)

o Assessments after the disaster by REACH Initiative

available at reachresourcecentre.info

o Humanitarian profiles, 3Ws/4Ws/5Ws

o EU Civil Protection Unit

Building and infrastructure-related information

o National institutions, ministries, Local Emergency

Management Agency (LEMA), chamber of commerce

o UNDSS, logistic cluster

o EU Civil Protection Unit

Crisis-related information

o Global Disaster Alerting Coordination Systems/ Virtual

On-Site Operations Coordination Centre (GDACs.org)

o Copernicus EMS (copernicus.eu/en/services/emergency)

o Media reports, social media

o Crisis mappers (crisismapping.ning.com), Standby Task

Force (standbytaskforce.org), Qatar computing Research

Institute (QCRI)

Table 6: Sources of Information for the Secondary Data Review (GIS)

Pre-Crisis Sources of Geodata In-Crisis Sources of Geodata

o Common operational datasets (COD), which are primarily

composed of administrative boundaries and populated

places, available through the Humanitarian Data

Exchange (HDX). Note: In some contexts, the national

authorities will be the best source for this information.

o Infrastructure data from Open Street Map (OSM)

including buildings, roads, and places of interest (e.g.

hospitals, schools, shops, etc.) Note: In some contexts,

the national authorities will be the best source for this

information.

o Gridded population datasets from WorldPop, the High-

Resolution Settlement Layer (HRSL) from

Facebook/Columbia University or the Global Human

Settlement Layer (GHSL) from the European

Commission Joint Research Centre (JRC).

o Exposure datasets from UNISDR GAR19

o Humanitarian OpenStreetMap Team (HOT) tasking

(updates to OpenStreetMap data)

o Event related geodata from the Global Disaster Alert and

Coordination System (GDACS), often courtesy of the

JRC, including storm tracks and shake maps.

o Post-event or in-crisis satellite imagery from Google

Earth, ESRI, Maxar, Airbus, Planet or others.

o Post event or in-crisis aerial imagery from OpenArialMap

o Imagery analysis from Copernicus EMS, UNOSAT or

private providers (e.g. Orbital Insights)

o Geodata related to crisis-related data collection exercises

conducted by other actors (EU Civil Protection, UNDAC,

national authorities)

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o Pre-crisis satellite imagery from Google Earth, ESRI,

Maxar, Airbus, Planet or others.

o Pre-crisis aerial imagery from OpenArialMap

Key Takeaways

• Conduct a Secondary Data Review (SDR) to establish what is known and unknown about the situation and

its impact and ensure that available data is factored in the HBDA design, the methodology note and data

analysis plan (see chapter 4)

• Specifically collect information on the magnitude of the event – notably for sudden-onset disaster – and

identify what estimations on the impact are already available through satellite imagery

• Note that there are two types of SDR information: pre-crisis (baseline) and in-crisis (already conducted

assessments and information reports about the crisis) – look at Tables 4 & 5 for sources of information

• Based on the SDR, identify information gaps and keep them in mind when selecting the questions for

the data collection tool from the library of questions

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5. Methodology & Assessment Design

A. Methodology and Data Analysis Plan

Each HBDA should have (1) a Methodology Note, (2) a Data Analysis Plan (DAP), and (3) a Data Management Plan

that outlines how data will be handled and by whom during and after the assessment (see Annex 5 for templates). The

Methodology Note and the Data Analysis Plan should also be part of the ToR for the HBDA.

The Methodology Note provides a roadmap for the HBDA, explaining the context and rationale as well as

specifying the final outputs and how they will be achieved. It informs decision-making around methodology and

outputs ensuring a common understanding amongst internal and external stakeholders. It also provides a record of the

agreed objectives of the research, the rationale of the research, the methodology intended to implement it, and the

rationale for choosing the methodology, in particular with regard to the sampling strategy.

A standard set of research questions for the HBDA would include:

o What level of damage on buildings and infrastructure have resulted from the crisis?

o What have been the most affected areas in terms of damage?

o What has been the impact on service provision, e.g. water and electricity, in the affected areas?

o Are there severe needs in Shelter, WASH, Food Security, Nutrition, Education, Protection and Health that warrant

an immediate response and/ or a sector specific assessment?

o What are the prospects for early recovery? In particular, what construction materials are prevalent in the destroyed

buildings?

o What key indicators may inform a PDNA, a Recovery and Peacebuilding Assessment (RPBA), and other similar

assessments?

These questions speak to the main indicators in the HBDA. At the same time, Section B – Building Use and Household

Information would have more granular questions and often information disaggregated by age and gender that would

be needed to be analyzed differently as compared to sections C-G. The strands of information from the different parts

of the HBDA would also need to be cross-analyzed.

The objective of this DAP is to ensure that all research questions are sufficiently addressed through indicators and that

the data collection tool questions/ responses are adequately designed to enable measurement of indicators.

Additionally, the DAP serves as a record of which research questions were supposed to be addressed by which

indicators, thereby helping to focus the interpretation of results during the analysis stage. It is recommended to have a

DAP at least for the main indicators in the HBDA.

The HBDA’s library of questions is structured and is meant to be administered at household level. Table 7

below provides an example of a DAP for the level of damage indicators in the HBDA, showing how they link to

other indicators that can be used to aggregate/ disaggregate the data on the level of damage.

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Table 7: Example of Data Analysis Plan for Selected Indicators for Most Disasters

Research

questions

No.

# Indicator

Question in Data

Collection Tool

Response in Data Collection

Tool

Data

Collection

Level/

Method

What is the level

of damages of

residential

buildings?

What is the level

of damages of

different

components of

buildings?

E5,

E6,

E8,

E9,

E11

Estimate level

of damages

Have the walls, roof,

ceiling, floor, foundations,

of the building suffered

any damage?

No damage

Minor damage (0-24%)

Moderate damage (25-49%)

Severe damage (50-74%)

Completely destroyed (>75%)

Not possible to assess

Household

(HH), Direct

Observation

Have some

buildings been

more affected

than others?

What factors

may explain that

some buildings

have been more

affected than

others?

(Disaggregation/

Aggregation

Variables)

A1-5 Location

Where is the building

located? (Country,

Region, State, City,

Neighborhood)

List of countries, regions,

states, cities, neighborhoods

HH, Direct

Observation

B1 Type of building What is the type of the

building?

Residential/ Dwelling

Commercial/ Business

Residential & Commercial

Hospital/ Health Clinic

School/ Education Facility

Police/ Fire Department

Religious/ Faith

Town hall/ Municipality

Other

HH, Direct

Observation

D1,

D3,

D5,

D13,

D15,

D19

Building

materials

What material is the

building frame, exterior

walls, roof, ceiling finish,

floor, foundation?

Brick

Timber

Stone

Tin/ Zinc sheeting

Concrete (column/beam)

Steel (column/beam)

Concrete plates

Concrete blocks

Unbaked brick, adobe

Wood, logs

Flattened tin cans

Etc.

HH, Direct

Observation

C1-

4 Building Size

What are the building’s

width, length, height,

number of stories?

Enter Number HH, Direct

Observation

C6

Disposition

compared to

other buildings

What is the building's

proximity to other

structures?

Detached house/stand alone

Adjoining house on one side

Adjoining house on two sides

Adjoining houses on three sides

HH, Direct

Observation

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B. Sampling Strategy

Sampling is the process of selecting a number of elements from a larger, defined group. In most assessments,

a sample of population or sites needs to be created because time, resources, and other constraints make it

impossible to assess all populations and sites. The sample selection is informed by the SDR based on resources,

urgency and type of information needs, access, and various other constraints including concern with assessment

fatigue among affected populations and a cost-benefit calculation between the need for information and the potential

protection risks for assessment teams and affected populations. An alternative to sampling is a census that covers

the entire population and/or in the case of a damage assessment all the buildings in the assessed areas (see

for reference on methodology and sampling, CIEDRS, 2003; UNHCR, 2017; and see Annex 1 for definitions).

The HBDA may be implemented using different approaches i.e. census, stratified random sampling, or a

combination between purposive sampling (non-probability method where objects are selected based on pre-defined

criteria, see for reference ACAPS, 2011), snowballing (respondent-driven sampling), and stratified-random

sampling. That choice depends on the objectives of the HBDA, the availability of resources and the type of targeted

buildings (infrastructure vs residential).

It should be noted that the AWG may decide to have a dual approach to the HBDA. This would involve firstly

initiating an assessment during the rapid phase, with a shorter data collection tool using a sample of the population

(e.g. stratified sampling) in order to provide rapid actionable information for the humanitarian response in shelter and

inform other tools such as the PDNA. This would be followed by launching a full-scale more thorough assessment later

during the in-depth phase, which would cover all buildings in the assessed areas (census) in order to inform safe

returns, reconstruction and recovery (see Part 1.C). The approach selected may affect the sampling strategy used, as

a longer survey will require more resources to carry out.

For the HBDA, four scenarios were developed based on resources (personnel, expertise, funding, equipment,

etc.) available to the AWG as well as objective and timing of the assessment, assuming access to the affected

areas and populations. Note that the first scenario is also broken down to allow for the possibility of census as

explained above.

It is ultimately up to the AWG’s judgment call to decide which resources are considered enough for the different

scenarios depending on the scale of the disaster and the qualifications of its’ staff, especially enumerators.

In the first three scenarios, the rationale is the same but the granularity changes. Hence, the scenarios positing

(1) maximum – initial phase only, (2) high, and (3) medium resources assume the use of stratified random

sampling to select buildings to assess across affected areas. As explained above, scenario 1 maximum resources

– in-depth phase is a special case that assumes that instead of relying on a sample, the HBDA covers all buildings in

the assessed affected areas. In scenario 4, the areas to assess are selected using purposive sampling, and only

within these most affected areas, stratified random sampling is used to select buildings.

Table 8 summarizes the scenarios and presents an additional disaggregation between residential buildings and

infrastructure. If there is no access, the HBDA cannot be administered.

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Table 8: Scenarios for Sampling Depending on Resources Available

Residential Buildings/ Small Businesses Infrastructure (schools, hospitals, police stations,

etc.)

1. Maximum

Resources

(personnel,

training,

funding,

equipment)

Initial Phase

o Coverage across all affected areas

o Stratified random sampling at admin. level 3

o Additional stratification by setting (camp-like,

urban, rural)

o Random GPS points are generated on a map

and weighted based on population density

o Nearest building unit to each point is targeted

for the survey

o Coverage across all affected areas

o Census of all infrastructure

o Three options by level of preference:

• Based on an accurate, up-to-date list

• Based on OSM, Google, other census (see

UNICEF AI project)

• Based on snowballing until saturation

In-Depth Phase

o On the authorities’ request and depending on

information needs (e.g. informing return to

safe buildings), census for residential buildings

and small businesses across affected areas

o As above

2. High

Resources

o Stratified random sampling as above, but no

stratification by type of settings o As above

3. Medium

Resources

o Stratified random sampling as above, but

stratification at administrative level 2 only

o As above, but key infrastructure only, e.g. health

centers and schools

4. Limited

Resources

o First (purposive) sampling to select most

affected areas (based on remote sensing/ sat

analysis, based on wind speed, distance from

epicenter, etc.)

o Coverage across most affected areas only

o Then stratified random sampling as above

o First (purposive) sampling to select most

affected areas (based on remote sensing / sat

analysis, wind speed, distance from epicenter)

o Coverage across most affected areas only

o Stratified random sampling of key infrastructure

only based on an up-to-date list if available

o If no list is available, snowball sampling until

target is met (i.e. no saturation)

No access

o HBDA does not work in those circumstances

o Exploit secondary data, including remote

sensing/ sat analysis, wind speed, etc.

o Support other assessments

o Execute HBDA once access is restored

o HBDA does not work in those circumstances

o Exploit secondary data, including remote

sensing / sat analysis, wind speed, etc.

o Support other assessments

o Execute HBDA once access is restored

The following section discusses scenarios that require stratified random sampling. When stratified random

sampling is used, the findings can be extrapolated from the study population to a broader population (see

Annex 1 for definitions). Thus, the population is split into non-overlapping groups or strata, and then randomly sampled

within each strata. The purpose is to ensure adequate representation of subjects in each stratum. The strata may be

admin units (sub-district (administrative level 3), district (administrative level 2), cities), settings (camp, urban, rural),

population groups (displaced, non-displaced), building typologies, etc.

By using stratified random sampling, the information gathered from the small number of units visited can be generalized

to the entire population. The more granular the stratification, the better generalizations can be obtained. The sample is

drawn from the sampling frame, a master list of the population or elements to be assessed. Formulas establish a

statistically significant sample size.

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A calculator for sample size is available here (http://www.surveysystem.com/sscalc.htm). Note that when defining a

sample size, it is important to be mindful of the confidence interval (margin of error) and confidence level (see

definitions).

Scenarios 1-3

o Stratification of Residential Buildings: Scenario 1 allows for the most granular coverage by stratifying the

population by both setting and density at the lowest possible administrative unit. Scenario 2 does the same

but without the added stratification by setting. Scenario 3 gives a less precise picture as it stratifies by population

density only at the second administrative level. If resources are available, it is recommended to go with

scenario 1.

o In the case of the HBDA, the selection of points would normally be done by generating random GPS points

on a map covering the population of interest. The distribution of GPS points would be weighted based on

population density should it vary across the targeted area. The building located nearest to each point (within a pre-

defined buffer as relevant to context) is then targeted for the HBDA. If this building cannot for some reason be

assessed, the nearest building to that building is targeted for the HBDA (see box below).

o Assessing Infrastructure: In scenarios 1-2, the objective is to assess all available infrastructure relying on the

list collected through the SDR, and/ or through partners, and/ or generated from asking assessed populations. In

Scenario 3, the objective is to assess only key infrastructure relying on the same methods to identify them. If

resources are available, it is recommended to go with scenarios 1-2.

Scenario 4

o Scenario 4 presupposes that the AWG has severely constrained resources. It relies on non-probability

sampling to select the areas to assess. Since purposive sampling is used, the findings cannot be extrapolated

statistically out of these areas. These areas are selected because they are considered most vulnerable based on

the already known or expected through the SDR analysis on severity of needs, pre-existing vulnerabilities, security

and access, gender, and ethnic diversity.

o Stratification of Residential Buildings: Once the areas for the HBDA are identified through purposive sampling,

the same strategy of stratified random sampling is applied. This would make the findings generalizable across

these areas.

o Assessing Infrastructure: Once the areas of the HBDA are identified through purposive sampling, the key

infrastructure to assess is selected using stratified random sampling as explained above. If no list is available, the

infrastructure is selected by relying on respondents’ responses (snowballing).

No Access

o As noted above, the HDBA cannot be implemented if there is no access to affected areas.

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Note: Assessing Multi-Household Buildings

If section B (Building Use and Household Information) is deployed as part of the HBDA’s data collection tool,

a further on-site randomization may be needed to select households to assess in multi-apartment or multi-

household buildings. This would be done using systematic sampling, given that the sampling frame is known and a

sample size may be agreed in advance. In a ten household or ten apartment residential building, the objective for the

enumerator may be to randomly assess two households (sample of 2). To do so, the enumerator would assess every

10/2= 5th household in the building. To select the first household to assess, the enumerator would use a random number

table or random number generator. The enumerator would then proceed to assess the 5th household in order after the

first household assessed.

Note: GIS–Based Sampling Techniques

Depending on the availability of geospatial secondary data, there are multiple options for utilizing GIS to generate

predefined sample locations based on desired parameters. For instance, it is possible to make either a random

selection of existing spatial data if a building or address registry exists, or generate a new set of random points, in lieu

of having any list to sample from. There are functions in mainstream desktop GIS platforms, including ArcGIS and

Qgis, which facilitate this. Additionally, off the shelf plugins have been developed to make this even easier, notably the

Sampling Design Tool for ArcGIS developed by NOAA, which is available here.

GIS-based sampling offers considerable operational benefits through the predetermination of sample locations and

removal of potential uncertainties that could present significant logistical constraints, including unnecessarily long

distances traveled and time spent on data collection.

C. Adaptation of the Data Collection Tool

The library of questions may need to be adapted in different assessments. There are two main aspects that can

be adapted in the library of questions: the number of indicators and the context-specific indicators.

During that process, the AWG would typically review the information needs; the sectors to be prioritized in the HBDA’s

Section B (Building Use and Household Information); the extent of the geographic areas and populations to be covered;

the capacity and resources of the AWG and of the local authorities; the type of decision-making the HBDA should be

informing; and the type of operational context and disaster (see Parts 2.A, B & 3).

Operational Context

These following sections may need to be especially adjusted based on the operational context.

o Section B: Indicator B52 may need to be adapted to reflect other types of sectors of employment.

o Section D: Indicators D1 to D20 may need to be adapted to reflect other types of building material for buildings in

other contexts.

o Section F: Indicator F22 may need to be adapted to reflect other debris/ disaster waste that could be present in

other contexts; indicator F29 may need to be adapted to reflect other type of hazards common for other contexts.

o Section G: Indicators G1 to G8 may not be relevant for every context and hence may need to be simply removed.

o Across the data collection tool, the assessment team needs to ensure that a common measurement system is

used: either the metric system (i.e. meters, kilometers) or the US customary system (i.e. feet, inches). Depending

on the context, this means adapting the measuring tools and other equipment distributed to the enumerators (see

Part 2.C).

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Depending on the type of disaster, the AWG may discuss the possibility of extensively reviewing the library of questions

to introduce disaster-specific questions for earthquakes, flash floods, etc. As the HBDA toolkit is refined, an additional

library of such questions will be developed.

Number of Indicators

The full library of questions has 243 questions. If all questions are included in the HBDA questionnaire, it will

lead to considerable time spent by enumerators with each building and household. In most cases, it may be

relevant to select certain questions from the library to save time and resources, based on information priorities. This

means removing the indicators that do not cover priority information needs when running a lighter assessment. Across

the library of questions, the priority rating from 1 to 3 for each question gives an indication of the indicator’s importance.

This is nonetheless indicative and may vary based on context and information needs.

Teams interested in running a lighter assessment may typically consider removing parts of or the entire

Section B (Building Use and Household Information), which is the longest part of the library of questions.

Section B is especially time-consuming because it is not observation driven and needs the enumerator to question

individual respondents to collect the information. Additionally, removing parts of or the entire Section G on

preparedness may be another relatively easy way to decrease the length of the questionnaire (see Part 1.B).

As explained in Parts 1.C & 4.B, the AWG may also decide to explore the possibility of having a lighter HBDA rapidly

after the disaster and a more thorough assessment some time afterward. The two assessments would then work in

conjunction to inform different priorities as well as track the evolution of the situation in the affected areas.

Key Takeaways

• The HBDA Core Team produces and the AWG validates a Methodology Note, a Data Analysis Plan, and a Data

Management Plan.

• Key overall questions for the HBDA include: What level of damage to buildings and infrastructure have

resulted from the crisis? What have been the most affected areas in terms of damage? What has been the

impact on service provision in the affected areas? Are there severe needs in WASH, Education, Food Security,

and Health that warrant an immediate response and/ or a sector specific assessment? What are the prospects

for early recovery? In particular, what construction materials were the most used in the destroyed buildings?

What key indicators may inform a PDNA, a RPBA, and other similar assessments?

• Depending on critical data to be collected and available resources, the sampling strategy for the HBDA

changes, leading to changes in the techniques used to select areas to assess. In the majority of cases,

the HBDA relies on stratified random sampling in the areas where it is administered. The HBDA cannot be

administered if there is no access.

• The HBDA’s library of questions should be adapted based on (1) operational context to reflect differences

in construction materials, type of infrastructure, etc.; (2) available resources, timeliness, and information needs

by reducing or increasing the number of indicators used. Note that it is not advisable to use all 240 questions

from the library of questions, due to the time that will be needed to conduct the surveys as well as analyze and

effectively use the results. This will likely only be relevant in exceptional cases.

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6. Data Collection

A. Preparation for Data Collection & Enumerators’ Training

The preparation for data collection includes the HBDA Core Team completing any outstanding HR, administrative,

logistics and related tasks. The HBDA Core Team has also already allocated Assessment Officer(s) to review the early

data coming from the HBDA.

The final preparations to start data collection should also include the HBDA Core Team conducting a final and

detailed review of the access situation specifically in the sites that were selected for assessment. At this

moment, as during the entire process, it is important to remain in liaison with local stakeholders, including authorities if

relevant, NGOs and civil society partners, and community leaders from affected populations.

It is important to have as clear as possible an idea of the day-to-day access constraints in these areas, especially with

regard to security and physical access constraints that can be very dynamic. The enumerators must be made aware

of these constraints, and written consent needs to be obtained from them before they are deployed to these areas (see

for reference on access, ACAPS, 2019).The final and most important stage in preparation for data collection is to

conduct the training of enumerators. The details of using mobile data collection are addressed in Part 3.C. Enumerators

must also to be made aware of general principles of how to collect data in humanitarian assessments, including (see

on accountability to affected populations, Inter-Agency Standing Committee, 2015):

o Confidentiality: Enumerators collecting personal data should handle it with care and not share outside of selected

people in the AWG unless written consent is obtained from the respondents. Personal information can never be

transferred for purposes other than those for which it was collected and for which consent was given. Enumerators

must also be sensitive as to who may overhear interviews.

o Sensitivity: Enumerators should be mindful of potential trauma experienced by respondents, an especially

important aspect in household damage assessments.

o Integrity: Enumerators must treat respondents with decency and respect. They should introduce themselves

respectfully to respondents and be transparent about the goals of the HBDA, its possible outcomes, and how the

data may be used.

o Informed Consent: Enumerators should ask respondents about their consent to use any information they provide.

As part of the HBDA, the enumerators would not be interviewing children. Respondents can always decline to

answer specific question.

o Safeguarding Information: The data and information management activities must adhere to international

standards of data protection. Enumerators should be mindful to not collect more information than is needed for

analytical purposes.

o Participation/ Inclusion: The HBDA Core Team should explain to enumerators the importance of the HBDA

capturing diversity and how this has been incorporated into the sampling strategy if relevant, including with regard

to women, men, girls, boys, persons with disabilities, older persons, and LGBTQ persons.

Besides these principles, enumerators must be explained their role in the HBDA. The length of the enumerator

training depends on the number of enumerators and the length of the data collection tool. In general, it will

vary from one to three days. The HBDA Core Team needs to budget for the logistics of organizing such a training,

including for venue, security, meals, trainers and enumerator salaries. Equipment should be provided and prepared

prior to the training, for example ensuring sufficient numbers of phones and tablets with the appropriate software are

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available, as well as power banks if relevant.As the HBDA toolkit is refined, training modules will be developed on these

aspects.

During the training the enumerators, must be at minimum clear about (see Table 2 in Part 2.C):

✓ HBDA’s context, objectives, time frame, geographical scope, methodology and sampling

✓ Team structure, responsibilities, and reporting lines. This includes assigning team leaders among

enumerators

✓ Techniques and tools to be used, especially the data collection tool and mobile data collection

✓ Techniques on how to implement an ethical and protection-focused approach, including age, gender, and

diversity awareness, including signing a code of conduct and a confidentiality agreement (see principles

above in this section)

✓ Instructions on referral mechanisms for any persons identified as needing urgent attention (e.g.

unaccompanied children, medical cases, survivors of sexual and gender-based violence)

✓ Strategies to enhance data quality and reduce bias when estimating damages, color coding, asking

questions from the preparedness section (G) of the data collection tool

✓ Security protocols and emergency procedures for enumerators’ safety

✓ Administrative and logistics arrangements, such as transport and accommodation

Note: Data Protection and Confidentiality

The Kobo Toolbox team employs industry standard best practices (both technical and administrative) to protect

against unauthorized access of data. Personal information is never shared or sold to third parties. However,

registered users of Kobo are the data controllers of the data they collect using Kobo Toolbox and are responsible

for the safe management of personal information, including compliance with the General Data Protection Regulation

(GDPR). Kobo Toolbox allows users to share application data publicly or with selected users. Information shared

publicly is visible to anyone and can be indexed by search engines. Kobo Toolbox is not responsible for how

registered users handle survey participants’ personal information (see for reference, Humanitarian Response,

2018). If preferred, it is also possible to install an instance of Kobo Toolbox on a privately owned and managed

server. For example, UNHCR currently have their own server, and some governments may prefer data to be stored

on their own servers.

B. Day-to-Day Management

The HBDA is managed on a day-to-day basis as any other humanitarian assessment/ project (see for reference on

assessment management, UNHCR, 2017). The best practices in the field include:

✓ Keeping track of the data collection process, including in terms of areas coverage and number of surveys

completed, with AWG staying in contact with enumerators in the field through their team leaders if such

were assigned

✓ Monitoring the local context to be aware of any changes in security and access conditions

✓ Keeping in daily contact with local counterparts among local NGOs, local and national authorities

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✓ Keeping an updated registry of progress and encountered challenges, including logistics, costs (e.g. salary,

per diem, procurement of equipment, vehicles, etc.)

✓ Starting cleaning and processing the early collected data to catch mistakes, misunderstandings, lapses in

coherence/ debriefing part of the enumerators to be sure indicators are understood by everyone

✓ If issues are identified, update the data collection tool and re-train enumerators or circulate guidelines

C. Mobile Data Collection and Kobo Toolbox

Data in the HBDA is collected in the field through an online questionnaire using Kobo Toolbox (an open source

data collection platform on electronic devices that allows rapid information gathering and facilitates the post-collection

data analysis). The data collected is then later visualized in Microsoft Power BI (an intelligence platform used for the

analysis and visualization of data). Other information management and visualization tools, including Microsoft Excel,

Tableau, ArcGIS, and Adobe Illustrator may also typically be used (see Part 6.C and Annex 3).

Assessment and GIS Officers must be proficient in the use of the Kobo Toolbox in order to train enumerators on mobile

data collection. During the training, enumerators must be shown how the Kobo Toolbox and mobile data collection

work in the Kobo application as well as the phone’s internet browser. The following link (XX) gives access to the HBDA

data collection tool.

During the training, enumerators should be made aware of the limitations associated with the HBDA, in particular

regarding GPS localization during mobile data collection using the Kobo Toolbox (see Part 1.D). Two additional points

warrant special attention:

✓ Enumerators need to know that once the data collection tool is open, no internet connection is needed to

register the information. However, for better GPS accuracy, it is recommended to always have internet

access. If there is no internet access, the information collected is stored on the phone and uploaded once

there is access to internet. To upload the information, the phone needs to be connected to the internet with

the link open for at least 10-15 min. Time varies depending on internet speed and size of the pictures.

✓ The HBDA data collection tool in the Kobo Toolbox uses a color coding for damage which it assigns based

on the information entered. The enumerator is asked to confirm the suggested color tagging such as: Green:

Minimal damage; Yellow: Medium damage; Orange: Major damage, significant repairs required; and Red:

Destroyed structure, probably requiring complete rebuilding. It is important that if the enumerator disagrees

with the tagging, they return back in the data collection tool and change the information for damage questions

instead of simply overriding the color coding suggested.

As the HBDA toolkit is refined, a specific guideline will be developed for the training of enumerators in the HBDA.

Key Takeaways

• The training of enumerators ensures the accuracy of the HBDA. Enumerators have to be briefed on:

o General principles (confidentiality, sensitivity, integrity, informed consent, safeguarding information,

inclusion) on how to collect data in humanitarian assessments

o Practical aspects of the HBDA, e.g. objectives, security, techniques, the data collection tool, color

coding, etc.

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o The use of the Kobo Toolbox in mobile data collection

• The HBDA Core Team, part of the AWG, handles the day-to-day management of the HBDA, including

keeping track of data collection, checking the quality of the early data, monitoring the context for changes in

access, keeping in touch with local authorities and other stakeholders.

7. Data Analysis

A. Data Cleaning and Processing

The AWG set procedures for collation, quality control, and processing of data. It establishes protocols among partners

for the sharing of different types of information. The protocols on data cleaning and processing need to at minimum

define:

✓ Type of metadata to describe the dataset (date of collection, geographic coverage, methodology)

✓ Geographical units (use of country P-codes and/or agreed administrative place names, disaggregation levels,

and other technical standards)

✓ Ownership the data, staff’s rights to change and/ or modify the data

✓ Determination of whether datasets should be cleared or anonymized prior to sharing, and by whom

✓ Rights to access the data at each level of aggregation and sensitivity

✓ Details on data confidentiality and safeguarding of information

After these protocols are agreed and implemented, members of the HBDA Core Team, usually Assessment

and Information Management Officers, clean the data. The objectives of data cleaning are multiple, including:

✓ Checking for data consistency, including that there are no significant gaps or logical inconsistencies in the data,

and checking the use of the “other” and “specify” options across the data collection tool

✓ Checking for data coherence and plausibility, e.g. comparing collected data to baseline pre-crisis information,

and/ or findings from similar contexts especially for harmonized sectoral indicators, and/ or existing humanitarian

standards

✓ Pre-identifying the most useful indicators and ensuring that data for these indicators is present

✓ Ensuring that data is geographically tagged, including that GPS readings are coherent

✓ Ensuring that data collection standards were respected, including metadata, names of enumerators, dates, and

unique identifying numbers are present

✓ Ensuring that methodology and sampling choice were respected

✓ Anonymizing the data by removing personal information on respondents if need be before sharing

As a rule, the Assessment and Information Management/GIS Officer(s) in charge of cleaning the data will maintain a

data cleaning log, and consult with the Needs Assessment Coordinator before altering the data. The data cleaning

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needs to be done daily, with a full comprehensive final review of the whole dataset after data collection has finished

(see for reference on data cleaning, ACAPS, 2016 and Annex 5 for templates).

B. Data Analysis

The analysis part is one of the most challenging and crucial parts of any HBDA. The quality and the relevance of the

findings depend on the quality of the data collected but also on the ability of the Assessment and Information

Management Officer(s) conducting the data analysis.

The analysis aims to make sense of the information collected and to draw conclusions about the severity of

conditions and humanitarian needs priorities. There are four different phases of analysis (see for reference on

analysis, UNHCR, 2017):

o Description: Grouping, summarizing, and comparing data to identify trends, patterns, and outliers. Comparison

of the following type are most commonly used in humanitarian data analysis to describe the data:

➢ To existing common conventions and/ or standards (e.g. SPHERE minimum standards, pre-crisis

standards, standards in neighboring countries with similar conditions)

➢ Across geographical units (provinces, districts, sub-districts, neighborhoods, villages), areas of high/

limited conflict-intensity, urban/ rural areas, camps and other settings

➢ Across socio-economic and ethnic/ national groups (e.g. agro-pastoralists vs. farmers, hosts vs.

IDPs, ethnic group A vs. ethnic group B)

➢ Based on sex and age, and other potential factors of marginalization and accrued need, including

persons with disabilities, LGBTQ, minorities, and indigenous people

➢ Based on evolutions in time (from the previous crisis to this one, from pre-crisis to the moment of the

HBDA, from the last HBDA to the current HBDA)

o Explanation: Determining the underlying factors and processes behind certain trends and patterns. The aim is to

identify associations, correlations, causations, and any types of connections in the data of specific indicators and

across indicators. Data analysts may develop different hypotheses to explain the data that need to be discussed

collectively within the AWG afterward.

o Interpretation/ Operationalization: Drawing conclusions on severity and priorities based on available evidence,

and estimating the extent to which the findings can apply to others settings. The aim is also to start preparing

operational recommendations as part of the decision-making based on the HBDA.

➢ Since the HBDA usually relies on stratified random sampling, the HBDA Core Team needs also to identify

the extent to which and how the findings may apply to non-assessed areas and populations. This involves

a review of the methodology and a debriefing of the enumerators to capture qualitative information based

on direct observation.

➢ The team needs to identify remaining information gaps and the limitations of the data.

o Early Warning & Preparedness: Predicting or forecasting the crisis’ likely evolutions based on past and present

data. The aim is to anticipate potential future events and their consequences, and help identify new and emerging

risks. This may include developing scenarios to estimate future the evolutions of the crisis and future humanitarian

caseloads. In the HBDA, this step is also about preparing early recovery and conducting preparedness efforts for

upcoming crises (see for reference on scenarios building, ACAPS, 2013).

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The interpretation and early warning phases are often conducted jointly by the AWG, possibly as part of a workshop

with additional key stakeholders. Afterward, the main findings of the data analysis are compiled in information products

that are shared, which may include reports and/or factsheets (see Part 6.D). They are the basis for subsequent

response analysis that draws strategic, programmatic, and/ or operational conclusions based on current and forecasted

severity and priorities.

The following section discusses some basic analysis of key indicators in the HBDA across the data collection tool. Most

of them would be presented as percentage of the assessed population.

B – Building Use and Household Information

Check the ratio of residential to non-residential buildings in the HBDA (B1), and evaluate if non-residential buildings are over-

assessed. If they are, propose possible explanations

Household Information – Identify the male/female ratio among respondents (B8); the age distribution of the respondents (B10);

the average household size (B12/13); the number of IDP (B14-16)

Household Health and Safety – Identify people with acute or special needs (B17-36)

Employment, Income, and Food Security Situation of Household – Identify needs in food security, including needs that may

pre-date the crisis (B37-44), and the potential for cash-based programing based on the availability of markets (B43-44). Identify

the impact of the crisis on livelihoods (B45-53) and the support received (B54-57) and the potential to be engaged in work as part

of recovery activities (B58). Calculate variations in food security needs as compared to the pre-crisis baseline; identify areas with

acute needs (see “Description” in Part 6.B)

Household relationship to building – Identify if people may receive insurance to recover from the crisis (B59-62)

Commercial or Mixed Use – Check that no category is over-represented among assessed buildings (B63), and if is, think of

explanations. Estimate percentages of business that stopped operations following the crisis, the impact it had on local

employment, and treat this as an indication of the economic health in the assessed areas (B69-76)

Non-Residential – Check that no category is over-represented among assessed buildings (B77), and if it is, think of

explanations; assess especially if non-residential buildings are being used to host IDP (B91-93)

Education Facility – Check that no category is over-represented among assessed buildings (B94), lack of secondary and higher

education facilities in assessed areas gives information on the socio-economical, situation of the population in that area; assess

needs in education as shown by lack of teachers (B96-97), damages to premises (B98-99), and furniture (B100-103); assess the

catchment population of the education facility (B104-123). Calculate ratios of teacher per student; identify areas with lack of

education coverage (see “Description” in Part 6.B)

Health Facility – Check that no category is over-represented among assessed buildings (B124), lack of hospitals/ health clinics

suggests pre-existing needs in health. Health facilities may lack the needed number of beds (B133-134) and/ or personnel

(B131-132), a situation that may have also pre-dated the crisis. Pre-existing needs may have been exacerbated by the crisis due

to damages (B126-128, B137), and/ or important caseload in health (B136). Calculate ratios of doctors/ nurses per patient;

identify geographical areas with limited health coverage/ most acute needs (see “Description” in Part 6.B)

D – Building Materials

Calculate the materials most needed for repairs for the different parts of the building across all households but also

disaggregating by different parameters (see “Description” in Part 6.B)

E – Building Damage and Repairs

Damage – Identify the ratio of buildings showing signs of damage before the crisis (E1); ratios on the levels of damage and

geographical repartition, and disaggregation by other factors (E5-14) (see “Description” in Part 6.B); assess the situation with

potential flooding in case of certain sudden-onset disaster and ensure the data is consistent across enumerators (E10)

Building Repairs – Evaluate the state of early recovery (E18-24), evaluate especially the ratio of houses unable to do repairs

due to either lack of financial support and/ or materials (E19)

F – Building Services and Debris

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Building Services – Evaluate the situation with power and electricity availability during the day especially in public buildings,

e.g. schools and hospitals (F1-6); evaluate the situation with WASH in households and especially in public buildings (F9-18),

compare to SPHERE standards; evaluate use of unsafe water sources; (see “Description” in Part 6.B) for disaggregation options

Debris Management – Estimate the amount of debris that needs to be collected; estimate the extent to which recovery and

debris/ disaster waste cleaning activities may be challengingt; evaluate the coherence of the information in F21 on amounts of

debris, and disaggregate by geographical area; evaluate the risks for debris cleaning activities (F30) (see for reference on debris

management, UNDP, 2015)

G – Building Preparedness

Information is partly subjective since it is based on respondents’ perception; it needs to be triangulated against SDR information.

C. Analysis Tools for Visualization

Microsoft Power BI

Microsoft Power BI is an industry standard business intelligence platform which, due to its ease of use, offers a lower

entry point for data visualization and analysis. As such, it has been identified as the preferred platform for HBDA

analysis and visualization. Learning materials are readily available for both the web and desktop applications. Data can

be easily sorted, filtered, analyzed, mapped and arranged. The example below presents a dashboard for Hurricane

Dorian in the Bahamas in August 2019.

As the HBDA is rolled-out, Power BI dashboard templates will be adapted to each context and improved upon as

lessons learned are incorporated. The HBDA toolkit will also be refined and specific guidelines on the use of Power BI

will be produced.

Geographic Information Systems (GIS)

While Microsoft Power BI is the preferred platform for analyzing and visualizing HBDA data, conventional GIS platforms,

including ArcGIS or Qgis, can help further analysis and fully leverage the spatial element of the data collected.

Typical analyses aggregate collected data to desired boundaries (e.g. neighborhood), identify linkages to other spatial

datasets, or calculate density of data points creating a “heatmap”. Geographic information products themselves can

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range from stand-alone “static” maps to interactive web maps to embedded maps in other applications, including Power

BI.

While not overly complicated, inclusion of this type of analysis would generally necessitate the incorporation of GIS

staff in the HBDA team (see Annex 4 for the ToR of a GIS Officer). Having trained GIS staff would also be beneficial

for developing standalone or other map templates in advance to facilitate rapid dissemination of GIS analytical products

(see Annex 3 for a list of GIS applications and links to related resources).

D. Information Products, Target Audience, & Dissemination

After analysis is completed, the AWG needs to establish a list of envisioned outputs for the HBDA, from the

final comprehensive report, to factsheets and profiles, dashboards, infographics, maps, the methodology, and

the dataset itself. The process of disseminating the findings is key to translating the HBDA into decision-making in

the humanitarian field. Different products would be targeted at different audiences and may be disseminated in different

ways. Protocols for data sharing and confidentiality may be needed to regulate the sharing of the HBDA’s dataset.

Since data in humanitarian assessments becomes obsolete quickly, it may be worth sharing preliminary

findings with partners and stakeholders before the final report and other information products are released. It

is also important that channels of communication remain open to the assessed populations.

The HBDA comprehensive report is usually drafted by the Assessment Officer(s) under the supervision and

with the review of the Assessment Coordinator. It needs to include the following information and components:

✓ Objectives and scope of the HBDA

✓ Description of the populations and areas covered in a map, and the dates of data collection

✓ Description of the methodologies and sampling strategy, including their limitations

✓ Context description including the scale of the crisis and the socio-political context

✓ Findings of the HBDA and AWG’s conclusions and recommendations

✓ Appropriate visualization showing at least the geographic repartition of buildings based on levels of damages

✓ Indication of needs, priorities, and challenges disaggregated by different factors (see Part 6.B)

✓ Note on gaps and challenges in specific sectors, geographic areas, and population sub-sets based on analysis

of the severity, depth, and estimated prevalence of the problem; and a comparison of current living standards

with a baseline or established benchmarks based on the SDR

✓ Acknowledgement of all the international, national, and local stakeholders who participated in the HBDA

The AWG then decides on the appropriate channels to disseminate the final comprehensive reports and the

other different information products of the HBDA. To facilitate this, the AWG should consider working with country-

level UNDP or other relevant agency Communications Officers to ensure appropriate external communication. It should

be noted that as the HBDA is conducted upon request, data is usually collected on behalf of and for governments.

Governments should be involved in dissemination decisions, and the AWG can assist with identifying relevant

humanitarian partners and dissemination channels. Specific channels for dissemination include:

✓ UNDP colleagues from country office and headquarters

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✓ Local and national authorities depending on the context

✓ Humanitarian partners among UN agencies, clusters, local and international NGOs depending on context

✓ Humanitarian partners in headquarters, including people in advocacy and communication

✓ Humanitarian websites such as HDX, Humanitarian Response, Refworld, and Reliefweb

✓ Cluster-specific websites (e.g. sheltercluster.org, globalprotectioncluster.org, globalcccmcluster.org)

✓ Social media such as Facebook, Instagram, Twitter, LinkedIn, Yammer

✓ File synchronization services such as SharePoint, Dropbox, and the Humanitarian Kiosk

Key Takeaways

• Data cleaning is an important step that needs to be conducted before analysis can start. The main objectives

of data cleaning are to check for consistency, plausibility, and appropriate geographical tagging.

• High quality data analysis is one of the most challenging parts of the HBDA. It helps draw conclusions about

the severity of crisis and humanitarian needs priorities. There are four phases of analysis:

o Description – Comparing the HBDA data to other datasets (pre-crisis baseline in SDR, humanitarian

standards, and across geographical units, population groups, and over time)

o Explanation – Postulating hypotheses to explain the data, identifying causes, and connecting

indicators among themselves.

o Interpretation – Drawing conclusions about severity of the crisis, most affected groups, identifying

priorities in affected areas, and preparing operational recommendations.

o Early Warning – Predicting the evolution of the crisis, planning for early recovery, and anticipating

future crises by setting-up early warning and monitoring systems.

• Microsoft Power BI is a unique tool to visualize the data from the HBDA that is easy to use; there are

dashboard templates for the HBDA using Power BI.

• Multiple outputs are possible based on the HBDA, including reports, factsheets, dashboards infographics,

and maps. Different products are targeted at different audiences, taking into account protocols for data sharing

and confidentiality limitations with regard to the data collected during the HBDA.

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Annex 1: Definitions

o Census: While sample surveys result in information obtained from only a subset of a population, a census results

in every person being counted and registered individually (MSF 1997, MSF 2006). A census covers the entire

population of a country; in addition to individual data, a set of relevant socioeconomic information is gathered for

every household (IDMC/OCHA 2008). (ACAPS, 2012; UNHCR, 2017).

o Common Operational Dataset (COD): Critical datasets that are used to support the work of humanitarian actors

across multiple sectors. CODs contain important geographic data like administrative boundaries, populated places

(settlements), transportation networks, and information about water bodies and terrain. Population statistics and

humanitarian profile data are also included. CODs are considered a standard for the humanitarian community and

should represent the best available datasets for each topic. (UNHCR, 2017)

o Confidence Interval (Margin of Error): The plus-or-minus figure that bracket results. For example, if you use a

confidence interval of 4 and 47% percent of your assessed population picks an answer you can be "sure" (See

confidence level) that if you had asked the question of the entire relevant population between 43% (47-4) and 51%

(47+4) would have picked that answer. (Surveysystem.com, 2019)

o Confidence Level: It is the percentage number that tells you how sure you can be in your findings. It represents

how often the true percentage of the population who would pick an answer lies within the confidence interval. The

95% confidence level means you can be 95% certain; the 99% confidence level means you can be 99% certain.

Most humanitarian researchers use the 95% confidence level. (Surveysystem.com, 2019)

o Coordinated Needs Assessment: Assessments that are planned and carried out in partnership with other

humanitarian actors, with the results shared for the benefit of the broader humanitarian community to identify the

needs of the affected population of a humanitarian crisis. Coordinated assessment is a broad term that includes

several different types of assessments, ranging from inter- and intra-cluster/sector joint assessments to single

agency assessment that are harmonized. (IASC, 2012)

o Data Analysis Plan: The tool operationalizing the analytical framework providing sources, methods, and data

collection techniques for each information element sought, as well as how the information will be analyzed.

(UNHCR, 2017)

o Debris: Mixture of building waste and rubble typically arising from damaged buildings and their demolition. This

waste stream can include natural materials such as clay and mud, trees, branches, bushes, etc.

o Disaster Waste: Solid and liquid waste generated from a disaster, not limited to debris. It includes concrete, steel,

wood, clay, tar elements from damaged buildings, infrastructure, household furnishings, parts from power and

telephone grids such as electrical poles, wire, electronic equipment, transformers, parts from water and sewerage

distribution centers, natural debris such as trees, mud and plants, chemicals, dyes and other raw materials from

industries and workshops, waste from relief operations, damaged cars, bicycles, unexploded ordnances,

packaging materials, pesticides, paint, varnish, solvents, and healthcare waste. (UNDP, 2015)

o Disaggregation, includes SADD (Sex and Age Disaggregated Data): Date is separated along specific sets of

variables or criteria (e.g. age, sex or economic status). (UNHCR, 2017)

o Emergency Employment: Job opportunities generated by national governments, international organizations and

NGOs for the affected populations in response to arising humanitarian crises. (ILO, 2019)

o Enumerator: Person in charge of administering the HBDA to the affected populations, and conducting the direct

observation of damages to buildings and infrastructure.

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o Fundamental Operational Dataset (FOD): Datasets that are relevant to a humanitarian operation whose content

is not covered by CODs. FODs often contain data that is specific to a particular sector, such as schools, wells, or

security incidents. (UNHCR, 2017)

o Geographic Information System (GIS): An organized collection of tools (computer hardware and software),

information, and professional/ technical knowledge used to input, store, retrieve, utilize, analyze, and output

geographically referenced data. GIS uses geography as its organizing principle. GIS is useful in situations with a

spatial dimension, such as knowing the locations of refugees and mapping damages to buildings. (UNHCR, 2017)

o Harmonized Needs Assessment: A needs assessment in which data collection processing and analysis is

undertaken separately from other needs assessments, however the data is sufficiently comparable (because of

the use of Common Operational Datasets, key indicators, and geographical and temporal synchronization) to be

compiled into a single database and to serve as the subject of a shared analysis. (IASC, 2012)

o Household: A household is defined as a housekeeping unit or, operationally, as a social unit that has a (1)

common arrangements for food; (2) shares household expenses or daily needs; and (3) lives in a shared dwelling.

A household includes either one person or a group of people, not necessarily related, living at the same address

with common housekeeping i.e. sharing at least one meal per day or sharing a living room.

o Household Membership: In the context of the HBDA, households are classified according to: (1) Main household

members i.e. persons in the dwelling who are its long-term permanent occupants and (2) Temporary household

members: persons who have gotten temporary shelter after being displaced by the crisis. Following on the above,

the unique household ID number relates to the main household members.

o Main Income Earner: The main income earner is the person who contributes the largest portion of household

income, covering most household expenses and financially supporting other household members.

o Main Respondent: The main respondent is an adult in the household who makes decisions about the household

and can be contacted for follow up. The main respondent has knowledge about the household and/ or is the

responsible adult in the household when the enumerator comes to administer the survey. During the HBDA, the

adults in the household may not be the main decision makers. In that case, the most knowledgeable about

household affairs should be interviewed as the main respondent.

o P-Code: Short for ‘place code.’ P-codes provide unique reference codes to geographic locations and are important

identifiers in data management systems. (UNHCR, 2017)

o Purposive Sampling: A non-probabilistic sampling method in which target subjects with different characteristics

are selected to fit a particular purpose. Results based on purposive sampling cannot be generalized to cover an

entire population. (UNHCR, 2017)

o Random Sampling, including stratified and systematic: This is a method to draw a representative sample by

means of selecting households or individuals randomly from the whole population of households or individuals

surveyed. (UNHCR, 2017) (see Stratification)

o Secondary Data Review (SDR) (or Desk Review): Review of information already available. A desk review is

always an advisable first step to understand the information needs in a particular context. (UNHCR, 2017)

o Snowball Sampling: Households and individuals are selected according to recommendations from other

informants, with each informant recommending the next set of informants. (WFP, UNHCR, 2017)

o Stratification: Dividing the assessed population into several sub-groups that share common characteristics, in a

way that each individual only belongs to one sub-group (with no overlap among them). For example, different age

brackets can be used to divide the population into sub-groups of children, teenagers, adults, and elderly. (UNHCR,

2017)

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Annex 2: Reference Documents

ACAPS, Data Cleaning, April 2016.

(https://www.acaps.org/sites/acaps/files/resources/files/acaps_technical_brief_data_cleaning_april_2016_0.pdf).

ACAPS, Humanitarian Access, Methodology Note, September 2019.

(https://www.acaps.org/sites/acaps/files/resources/files/20190910_acaps_access_technical_brief_september_20

19_update_v2.pdf).

ACAPS, Purposive sampling and site selection in Phase 2, October 2011. (http://www.coordinationtoolkit.org/wp-

content/uploads/ACAPS-Purposive-Sampling-and-Site-Selection.pdf).

ACAPS, Scenario Development, Summary Brief, 2013.

(https://www.acaps.org/sites/acaps/files/resources/files/scenario_building-pocket_version.pdf).

ACAPS, Secondary Data Review, Technical Brief, May 2014.

(https://www.acaps.org/sites/acaps/files/resources/files/secondary_data_review-

sudden_onset_natural_disasters_may_2014.pdf).

ACAPS, Survey of Surveys, Technical Note, July 2011.

(https://www.acaps.org/sites/acaps/files/resources/files/technical_note-survey_of_surveys_july_2011.pdf).

Center for International Emergency, Disaster and Refugee Studies, and Hopkins Population Center, Demographic

Methods in Emergency Assessment, A Guide for Practitioners, 2003. (http://www.coordinationtoolkit.org/wp-

content/uploads/CIEDRS-Demographic-Methods-in-Emergency-Assessment.pdf).

Inter-Agency Standing Committee, Multi-Sector Initial Rapid Assessment Guidance, July 2015.

(https://www.humanitarianresponse.info/en/programme-cycle/space/document/multi-sector-initial-rapid-

assessment-guidance-revision-july-2015).

Inter-Agency Standing Committee, Operational Guidance for Coordinated Assessments, March 2012.

(https://www.humanitarianresponse.info/sites/www.humanitarianresponse.info/files/documents/files/ops_guidance

_finalversion2012_1.pdf).

Inter-Agency Standing Committee, Protection and Accountability to Affected Populations in the HRP, 2015.

(http://www.globalprotectioncluster.org/_assets/files/tools_and_guidance/protection_of_civilians/edg-

aap_protection_guidance_note_2016.pdf).

Kobo Toolbox, Help Center, 2019. (http://support.kobotoolbox.org/en/).

UN-Spider, Knowledge Portal, 2019. (http://www.un-spider.org).

UNDP, Guidance Note on Debris Management, November 2015.

(https://www.undp.org/content/undp/en/home/librarypage/crisis-prevention-and-recovery/signature-product--

guidance-note-on-debris-management.html).

UNDP, Post-Disaster Needs Assessment, September 2014.

(http://www.undp.org/content/undp/en/home/librarypage/crisis-prevention-and-recovery/pdna.html).

UNHCR, Needs Assessment Handbook, June 2017. (http://needsassessment.unhcr.org/media/downloads/2017-

05_NAH_BOOK_NEW.pdf).

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Annex 3: Information Management, Visualization, Mapping and Navigation Tools

o Microsoft Excel: An indispensable tool for data/ information management. While not listed in the Analysis tools

section explicitly, this software is generally expected to be part of the HBDA process/ workflow.

o ESRI ArcGIS: ArcGIS is the industry standard desktop GIS application. There are now two versions available,

Desktop and Pro. Both offer similar features that can be used to enhance the HBDA with additional mapping

products. There is also a plug in available for Power BI which enables the incorporation of custom maps. Further

a number of applications have been developed by ESRI that could be useful for HBDAs:

o Survey 123 for ArcGIS: Survey 123 is a custom data collection application, built with integration with

GIS in mind and supports the XLSForm specification.

o Workforce for ArcGIS: Workforce is an application designed for managing enumeration teams and can

more effectively distribute work through the creation of discrete assignments.

o Operations Dashboard for ArcGIS: Operations Dashboard a configurable web app that provides

location-aware data visualization and analytics for a real-time operational view of people, services,

assets, and events.

o QGIS: Quantum GIS or QGIS is a free and open source desktop GIS application. It has a wide following and

functionality has increased in recent years to make it largely comparable with ArcGIS. QGIS is still a powerful tool,

particularly for projects/ missions with smaller budgets. The only downside is limited documentation in comparison

to ArcGIS and some bugs which take longer to resolve as it is an open source application.

o Adobe Illustrator: Adobe Illustrator is a premier vector design program that can facilitate the production of high-

end graphic visualizations.

o Adobe InDesign: InDesign is Adobe’s desktop publishing application with allows for the production of rich graphic

documents.

o ODK Collect: ODK Collect is the original Android application created for OpenDataKit data collection. ODK collect

can be linked to a Kobo Toolbox server and it is possible to customize offline maps for the application.

o ODK Briefcase: ODK Briefcase is an offline data aggregation application, very useful in low or no bandwidth

environment.

o GeoODK: GeoODK is an ODK based data collection application geared towards collection of geospatial

information and integration with GIS applications.

o Open Map Kit: OpenMapKit is an ODK based data collection application built with OpenStreetMap in mind and

offers the possibility to create an OpenStreetMap question which launches the OMK app to enable OpenStreetMap

editing.

o Android Mapping and Navigation Applications: There are many applications, notably Maps.me, SW Maps,

MAPinr, which offer the ability to load a geodata related to data collection (e.g. affected area, daily assignment,

etc.) on offline extracts of resources like OpenStreetMap.

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Annex 4: Terms of References (ToR) of the HBDA Team

ToR, Program Lead/ Assessment Coordinator

ToR, Assessment Officer

ToR, Information Management/ GIS Officer/ Remote Sensing Analyst

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Annex 5: Templates

Data Cleaning Logbook

UID Question

Name Issue Feedback Changed Old Value New Value

XXXX1 B.1.

Type_Buil

ding

Enumerator reports

"Other-

Supermarket”

Recode to “Commercial/

Business”

Yes Other-

Supermarke

t

“Commercial/

Business”

XXXX2 F.14

Functionin

g_Latrines

Enumerator reports

60

Reviewed with enumerator,

input error

Yes 60 6

XXXX3 E.6

Roof_Da

mage

Enumerator reports

over 75% for almost

all buildings he

assessed despite

his assessment

area not being one

of the most affected

Reviewed with enumerator,

damages is under-estimated

in that area and enumerator

over-estimates damages,

need to review his answers

and triangulate with other

enumerators from that area

Yes Completely

destroyed

(>75%)

(collapsed)

Severe

damage (50-

74%) (partly

collapsed, not

structurally

sound and not

livable)

XXXX4

Data Management Plan

Documentation and Metadata

What documentation and

metadata will accompany

the data?

Select all that apply

□ Data analysis plan □

Data Cleaning Log, including:

□ Deletion Log

□ Value Change Log

□ Code book □ Data Dictionary

□ Metadata based on HDX

Standards □ [Other, Specify]

Ethics and Legal Compliance

Which ethical and legal

measures will be taken?

□ Consent of participants to participate □ Consent of participants to share personal information with other agencies

□ No collection of personally identifiable

data will take place □

Gender, child protection and other

protection issues are taken into account

□ All participants reached age of

majority [Other, Specify]

Who will own the

copyright and Intellectual

Property Rights for the

data that is collected?

[Specify]

Storage and Backup

Where will data be

stored and backed up

during the research?

□ HBDA/ AWG Kobo Server □ Other Kobo Server: [specify]

□ Government Server □ Physical location [specify]

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□ On devices held by UNDP Staff □ [Other, Specify]

Which data access and

security measures have

been taken?

Password protection on devices/

servers □

Data access is limited to [Specify,

e.g. UNDP staff, HBDA Core Team,

AWG]

Form and data encryption on

data collection server □

Partners signed an MoU if

accessing raw data

□ [Other, Specify]

Kobo Access Rights

Kobo Access Person Account Name

View Form [Insert name] [Insert account name]

View and Edit Form [Insert name] [Insert account name]

View Form and Submit

Data [Insert name] [Insert account name]

Download Data [Insert name]

[Insert account name] [Download data

access to a deployed form can only be

awarded to one single individual.]

Raw Data Access Rights

Raw Data Access Reason Person

Accountable Accountable [Insert name] [must be the same person as

the one who has “download data” rights in

the Kobo Access Rights table]

Access

[Explain why this person needs to

access to raw data, e.g. GIS:

choropleth maps using GPS points]

[Insert name]

[Add relevant number of rows

for access rights]

[Explain why this person needs to

access to raw data, e.g. GIS:

choropleth maps using GPS points]

[Insert name]

Preservation

Where will data be

stored for long-term

preservation?

□ Government Server □ OCHA HDX

□ UNDP Country Server □ [Other, Specify]

Data Sharing

Will data be shared

publicly? □ Yes □ No

If yes, will all data be

shared?

□ Yes □

Only anonymized/ cleaned/

consolidated [delete what does not

apply] data will be shared

□ Other [Specify]

Where will you share the

data? □ Government □ OCHA HDX

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Methodology Note

Country

Type of Emergency □ Natural disaster □ Conflict

Type of Crisis □ Sudden onset □ Slow onset □ Protracted

Research Timeframe 1. Start collect data: _ _/_ _/_ _ _ _ 5. Preliminary presentation: _ _/_ _/_ _ _ _

2. Data collected: _ _/_ _/_ _ _ _ 6. Outputs sent for validation: _ _/_ _/_ _ _ _

3. Data analysed: _ _/_ _/_ _ _ _ 7. Outputs published: _ _/_ _/_ _ _ _

4. Data sent for validation: _ _/_ _/_ _ _ _ 8. Final presentation: _ _/_ _/_ _ _ _

Number of HBDAS □ Single assessment

□ Multi assessment (Rapid + In-Depth, Monitoring)

[Describe here the frequency of the cycle]

Humanitarian

milestones

Specify what will the

HBDA inform and when

Milestone Deadline

□ Donor plan/strategy _ _/_ _/_ _ _ _

□ Inter-cluster plan/strategy _ _/_ _/_ _ _ _

□ Cluster plan/strategy _ _/_ _/_ _ _ _

□ NGO platform plan/strategy _ _/_ _/_ _ _ _

□ Other (Specify): _ _/_ _/_ _ _ _

Audience type Dissemination

□ Humanitarian Response □ [Other, Specify]

Data Protection Risk Assessment

Have you completed the

Indicators Risk Assessment

table below?

□ Yes □ No, no information that allows

identification of individuals is collected

[Complete the first 4 columns in the Indicators Risk Assessment table below]

Risk Indicator Type of

Identification Risk

Disclosure

Implications Benefits Class

Required

Mitigation

[Specify indicator,

e.g. HH_phone

number]

[Specify identification

risk, e.g. Direct

contact/identification

of HH]

[Specify implications,

e.g. loss of privacy/

potential target of

armed actors]

[Specify

benefits, e.g.

follow up for

authorities]

[To be

completed by

AWG]

[To be specified

by AWG]

[Add relevant

number of rows

for risk indicators]

Responsibilities

Data collection [Insert name, function, email]

Data cleaning [Insert name, function, email]

Data analysis [Insert name, function, email]

Data sharing/uploading [Insert name, function, email]

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Audience Type &

Dissemination Specify

who will the assessment

inform and how you will

disseminate to inform the

audience

□ Strategic

□ Programmatic

□ Operational

□ [Other, Specify]

□ General Product Mailing (e.g. mail to NGO consortium; HCT participants; Donors)

□ Cluster Mailing (Education, Shelter and WASH) and presentation of findings at cluster meeting

□ Presentation of findings (e.g. at HCT meeting; Cluster meeting)

□ Website Dissemination (Relief Web, etc.)

□ [Other, Specify]

General Objective [Describe here what the HBDA aims to inform]

Specific Objective(s) [List here what the HBDA aims to identify to facilitate the general objective]

Research Questions [List here the research questions that will need to be answered to meet the objectives]

Geographic Coverage [Describe here the geographic area that the HBDA aims to provide findings about]

Secondary data sources [List here the key secondary data sources that will be included in the research]

Population(s) □ IDPs in camp □ IDPs in informal sites

Select all that apply □ IDPs in host communities □ IDPs [Other, Specify]

□ Refugees in camp □ Refugees in informal sites

□ Refugees in host communities □ Refugees [Other, Specify]

□ Host communities □ [Other, Specify]

Stratification

Select type(s) and enter

number of strata

Geographical #:_ _ _

Population size per strata is

known? □ Yes □ No

Group #: _ _ _

Population size per

strata is known?

□ Yes □ No

[Other Specify] #: _ _

Population size per

strata is known?

□ Yes □ No

Data collection tool(s) □ Structured (Quantitative)

Sampling method Data Collection Method

Structured data

collection tool # 1

Select sampling and data

collection method and

specify target # interviews

□ Purposive

□ Probability / Simple random

□ Probability / Stratified simple random

□ Census

□ [Other, Specify]

□ Household interview (Target #):_ _ _ _ _

□ Individual interview (Target #):_ _ _ _ _

□ Direct observations (Target #):_ _ _ _ _

□ [Other, Specify] (Target #):_ _ _ _ _

Target level of precision _ _% level of confidence _ _+/- % margin of error

Expected ouput type(s) □ Situation overview #: _ _ □ Report #: _ _ □ Profile #: _ _

□ Presentation (Preliminary

findings) #: _ _ □

Presentation (Final)

#: _ _ □ Factsheet #: _ _

□ Interactive dashboard #:_ □ Webmap #: _ _ □ Map #: _ _

□ [Other, Specify] #: _ _

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Access

□ Public (available on humanitarian platforms)

□ Restricted (bilateral dissemination only upon agreed dissemination list, no publication on other platforms)

Rationale [One paragraph]

• Context

• Information gap

Methodology Overview [One paragraph]

• Summarise each step in the methodology

• Outline any key definitions relevant to the research

Population of Interest [One paragraph]

Explain the rationale for the:

• Geographical area assessed

• Population assessed

• Unit of measurement

Secondary Data Review (outline key bibliography/sources you will use and for what). [One to two paragraphs]

Consider secondary data that will:

• Aid understanding of context

• Identify information gaps – mark the indicators in your data analysis plan that will be addressed through secondary data!

• Key definitions

• Inform assessment methodology including sampling design

• Inform questionnaire design

• Verify/triangulate primary data and findings

Primary Data Collection [Detailed information]

• Method – summarise who is collecting the data, how, when, where, from who and the rationale for this.

• Sampling – summarise your sample for all strata in a table and explain how you will implement the sampling i.e. how you will select your respondents / participants.

• Tools – explain what tools you will use and how they will be designed and built.

• Triangulation / briefing and debriefing of enumerators – explain how incoming data will be monitored / triangulated and enumerators briefed/ debriefed.

Data Processing & Analysis [One paragraph]

• Data entry and cleaning process

• Data analysis process – how will you produce the analysis in your Data Analysis Plan

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Annex 6: HBDA Hardware and Software Requirements

A. Hardware

A.1 Laptop computers

A.1.1 Standard laptop package for Assessment Officers

Laptop specifications:

• Processor: i7 quad core (7xxx) or (8xxx), i5 quad core (7xxx) or (8xxx)

• RAM: 8GB - 16GB

• Storage: 256GB - 512GB (must be a solid-state drive)

• Graphics card: Intel HD Graphics 620 or similar

• Display: 14’’-15” (in specific cases and if justification is provided, 13’’ models can also be considered)

• Minimum 1-year manufacturer’s warranty

• Laptop battery life: > 4h

• Laptop battery life (countries with serious electricity supply problems): > 8h

• Processor cores: 4

Accessories:

• Laptop bag

• Wired mouse

• USB-Hub 4 ports (if less than 3 ports on the device)

• Ethernet adapter (if not present on the device)

• Extra charger (countries with serious electricity supply problems)

Potential models:

• Lenovo ThinkPad T4xx (480, 480s, 480p, 470,…) • Dell Latitude 7xxx (7490)

A.1.2 Standard laptop package for GIS Officers

Laptop specifications:

• Processor: i7 quad core (7xxx) or (8xxx)

• RAM: 16GB - 32GB

• Storage: 512GB to 1TB (must be a solid-state drive)

• Graphics card: Nvidia GeForce GTX 1050 or similar

• Display: 15’’ (in specific cases and if justification is provided, 13’’ models can also be considered)

• Minimum 1-year manufacturer’s warranty

• Laptop battery life: > 4h

• Laptop battery life (countries with serious electricity supply problems): > 8h

• Processor cores: 4-6

Accessories:

• Laptop bag

• Wired mouse

• USB-Hub 4 ports (if less than 3 ports on the device)

• Ethernet adapter (if not present on the device)

• Extra charger (countries with serious electricity supply problems)

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Potential models:

• Dell XPS 15 (indicative public price: 1900-2000 CHF)

• Lenovo ThinkPad Pxxx (indicative public price: 2100 CHF);

• Dell Precision Mobile Workstation (indicative public price: 2200-2500 CHF);

A.2 Mobile Devices

There are many options available for suitable mobile devices. Originally, OpenDataKit, and later KoboToolbox,

applications were designed for use only on Android devices. However, it is now possible to collect data on iOS devices

through web forms. The KoboCollect app can run on any device with Android 2.1 (which was released on January

2010) or above. Note: For Survey 123, the Android version needs to be more recent, 5.0 Lollipop or later (for ARMv7

32 bit) or 6.0 Marshmallow or later (for ARMv8 64 bit).

When selecting a device you need to consider a number of factors:

• Cost • Durability • Battery life • GPS accuracy • Screen quality • Connectivity options • Phone vs. Tablet

In practice, it is good to try to achieve a balance between acceptable pricing (this generally rules out Apple devices) and choosing devices that can be re-used in the field for multiple deployments. Phones that are unlocked and that use multiple frequencies (quad band) are ideal. Mid-range devices make the most sense, as you can avoid the pitfalls of the lowest tier devices as well as the unnecessary and costly features of the higher end devices.

More information from the KoboToolbox team can be found here and regarding Survey 123, here.

A.3 Supplemental GPS/GNSS receiver (optional)

In cases where the GPS accuracy of mobile devices is not good enough, there are options to provide real-time submeter

GPS corrections in the field. GPS/GNSS receivers are able to work with any mobile device via Bluetooth connection

and can work with any third-party or in-house data-collection app.

The Arrow 100 from EOS Positioning Systems represents one of the best options on the market.

B. Software

B.1 Essential Software

B.1.1 Data Collection

• Option1: KoboToolbox – recommend as the default option, ideally using the KoboCollect app installed on

Android devices.

• Option2: OpenDataKit (ODK) – recommended for situations when there will be little to no connectivity in

country, the fully offline workflow combining ODK Collect and ODK Briefcase has proved reliable.

• Option3: Survey 123 for ArcGIS – recommended for situations where additional functionality provided by the

ESRI suite of ArcGIS field applications justify the cost for ArcGIS Online subscriptions. The combination of

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Workforce, Navigator and Survey 123 appears promising. Further the integration with Operations Dashboard

could add significant value as well.

B.1.2 Data Visualization and Analysis and Reporting

• Microsoft PowerBI – proven to be a useful tool for visualizing and analyzing HBDA datasets

• Microsoft Office – Excel and Word are industry standard

B.1.3 Antivirus

• Bitdefender or similar

B.2 Optional Software

• ArcGIS Desktop or Pro – for more advanced geospatial applications / analysis

• Adobe Creative Cloud – for enhanced graphic document production / desktop publishing

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Annex 7: UNDP-UNOSAT Standard Operating Procedures

UNDP’s engagement in crisis preparedness and response can be supported by satellite-based analysis and geoinformation, crucial for timely decision-making on the allocation of resources and prioritization of activities.

In October 2017, UNDP and the Operational Satellite Application Programme (UNOSAT) of the United Nations Institute for Training and Research (UNITAR) signed a Standard Operating Procedure (SOP) to streamline the use of geospatial technologies for UNDP Country Offices and Regional Hubs for emergency and crisis response, early warning and preparedness, risk assessments and recovery planning at country and regional level.

HOW TO ACCESS UNOSAT SERVICES

UNOSAT products and services include satellite imagery, maps, geospatial analysis, deployment of experts and training, and can be accessed through two modalities:

RAPID MAPPING

During humanitarian emergencies – both natural disasters and conflicts – UNDP can activate at no cost UNOSAT Rapid Mapping Service, and can access directly from its website products/analyses relevant by area and by crisis, unless restricted by copyright or other limitations.

See this short introductory video and UNOSAT Geospatial Catalogue for examples of satellite-imagery-derived products that the Country Office can request to support immediate crisis response.

PAYING SERVICES

UNDP will pay for the following UNOSAT services:

• In-country support, including training and deployement of GIS experts and/or geospatial coordinators at

short notice.

• Support on risk assessments and recovery planning at country level.

• Other kinds of technical support involving assessments, monitoring over time of recovery and development

projects, and the development of Post Disaster Needs Assessments (PDNA) and Recovery and

Peacebuilding Assessments (RPBA).

EXAMPLES OF UNOSAT – UNDP COOPERATION

The satellite-based damage assessment in Gaza - OPT has determined the location of the most affected communities, provided a preliminary infrastructure damage assessment, and supported planning of a detailed ground-based damage assessment.

UNDP activated UNOSAT Rapid Mapping Service for achieving situational awareness and assessing the impact of floods in Vietnam, Uganda, and Guatemala in 2017.

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HOW TO REQUEST UNOSAT SERVICES – NO COST AND PAYING OPTIONS

1. Contact the Regional Bureau desk and the Crisis Bureau Country Support Management Team (CSMT) for immediate support on mapping and other key information needs. Based on the initial discussion with the Country Office, CSMT submits an immediate request to UNOSAT with copy to the relevant Country Office and Regional Bureau counterpart, and Crisis Bureau in Geneva. UNOSAT evaluates the feasibility of the request and reverts to UNDP within 24 hours with a delivery time for the product/service.

2. In case the Country Office does not have the capacity to make an immediate request, CSMT in consultation with the Regional Bureau desk, sends an initial request to UNOSAT and copies the relevant Country Office counterpart and Crisis Bureau in Geneva.

3. No specific format is required for submitting requests, but the following information should be included:

a. Type of information needed – for example impact of tropical storm, extent of flood, assessment of

damages to infrastructure, estimation of population exposed to a disaster, etcetera.

b. Area of interest/location – ideally sent as KML file or latitude/longitude coordinates, however location

names are also acceptable.

4. UNOSAT makes available satellite-imagery-derived products for digital download in different formats: PDF,

GIS-ready data, Maps - Live Maps, Reports & Statistics.

In the case in which paying services are requested UNOSAT provides a cost estimation. Procurement of paying services will be arranged through a UN to UN agreement. Funding options include payment from the requesting entity, Crisis Bureau seed funding and joint project development/resource mobilization with UNOSAT.

WHY UNOSAT SERVICES ARE STRATEGIC TO UNDP’S COUNTRY OFFICES

Satellite based analysis and geospatial information are key to complement rapid assessments carried out by the Humanitarian Country Team on the ground with concrete figures of damages that are often not available in the first days, particularly when access to some areas is difficult or not possible.

FOCAL POINTS

Crisis Bureau – Country Support Management Team, New York

Africa :

• Aboubacar Koulibaly: [email protected];

Asia and Pacific, Europe and CIS: • Rebecca Reynolds: [email protected];

Arab States: • Aurelie Boukobza: [email protected]

Crisis Bureau - Geneva

Roberto Paganini: [email protected];

• UNOSAT – Geneva

Olivier Van Damme: [email protected]; ; [email protected].