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-30∞ -20∞ 60° -10∞ 0∞ 10∞ 60∞ 20∞ 30∞ 40∞ HISTORY OF POVERTY MAPPING (from the February 2003 Mali report)

The collection of poverty data and its cartographic expression and use to identify the poorest populations is equivalent to the creation and application of the map Dr. John Snow made of the Broad Street Pump cholera epidemic in 1854. Dr. Snow mapped all the cases of cholera during the epidemic and found that over 97% of the cases were located near the local public pump that he found not only to have been shared by all of the deceased and but also to have been infected with cholera.

Dr. Snow’s observations and deductions provided him with the solution to the problem: removing the handle to the pump. As a result no more cases occurred in this part of London. The deductive reasoning followed by Dr. Snow, in this first and most famous epidemiological study provided him with a prescriptive solution to the problem and a means to arrest the progress of an epidemic which had the problem gone unresolved, might well have caused many more deaths.

This is the first documented case of socio-economic data being merged cartographically with resource information. The map derived from this work defined the critical indicators and clearly provided evidence of the utility of spatial data analysis for problem solving. It should also be noted that Dr. Snow used a participatory process in that the families, friends and acquaintances of the deceased were interviewed to define the indicators and the limits of the study.

Another important early study directly related to the work done by Stone in Niger and in Mali was the work of Charles Booth who in 1889 mapped Poverty in London England by using social conditions as indicators and mapping for every individual by street and tenement. True-to-scale maps showing the individual buildings on the streets of our cities are a fairly recent innovation, and thematic maps displaying selected characteristics of city life are relatively rare. Considering this, the colored maps created by Charles Booth to depict the social condition of every London Street in 1889 were a startling innovation. Those maps, like the innovative village multi-indicator Atlas approach clearly show the advantage that such an Atlas would have over other “poverty mapping” efforts. This point has been demonstrated by Stone’s work in Niger and Mali in 2001-2003.

Most discussion to date has defined poverty mapping in western terms and using western symbols for poverty. The poverty maps created to the present also typically present data and information aggregated to the political units that paint too broad a brush and miss the differences made obvious by Charles Booth in his study of London. Geographical mapping on the basis of the criteria and variables used in Niger or proposed for the Atlas’ of Poverty/Vulnerability will provide a view of the country that permits one to understand why one village is very poor while the village next to it is inexplicably well off. This approach also and more importantly allows one to question and so seek the answers to why such differences exist.

Sonia Rocha (1998) of IPEA, Brazil supports such contentions. She implies that most poverty mapping efforts are contextually not relevant. She defines poverty on the basis of needs and not technological change? What are the main features of this “condition de vie” approach? The outstanding features are – “under-nutrition, low schooling, and lack of access to public services or unemployment and marginality.” She adds that: “This overall information on the poverty syndrome is the key element for conceiving a framework in which poverty analysis and anti-poverty policies are to evolve. Specifically it means adopting concepts and measurement instruments (indicators) that seem the most appropriate to a specific context in terms of social reality and data gathering capabilities.”

We believe that an additional and equally important set of factors should be included in the “condition de vie” or living condition analysis. These factors relate to the environmental status of populations. Environmental factors or indicators affecting poverty in Mali and Niger include: annual rainfall, availability of land, soil quality, the number of stakeholders using the land and the degradation processes and trends affecting a particular area, town or village. Poverty has a dynamic profile, a profile that must be redrawn periodically and whose lines must be reassessed with the impact of events that bring on social, economic and environmental change such as that affecting the West African region due to recent events in Cotês d’Ivoire.

Mapping the elements of poverty and food security can provide Malian and Nigerian decision makers with a completely new view of the problem they are trying to solve. Providing a geospatial dimension to poverty helps to find solutions to problems that seem to defy solutions. Dr. John Snow resolved a very complex, if localized, medical problem by using this technique. Charles Booth spatialized poverty in London and influenced the understanding of 19th Century London and defined the process for attacking poverty through the spatial dimension.

Present methods for poverty or deprivation mapping used in the West are not contextual with Mali’s or Niger’s problems. For example the State of Illinois maps list among other factors, recreational and crime statistics. In the State of Guanajuato, Mexico, the mapping of poverty considered, among other issues, marginalization, income and the quality of the dwellings. The latter is very important in Mexico but much less so in rural Mali or Niger. In Dorset, England, < www.dorset-cc.gov.uk > housing, disability and employment are important factors used as indicators. It is interesting to note that in the case of the Dorset study poverty is measured using an index of deprivation with six indicators that are weighed based on an established calculation.

Poverty mapping and the capacity to understand the geography of poverty will provide both Malians and Nigerians with new information and therefore, a new outlook on the origins and causes of the problem. Once the origins and cause are better known, ideas and innovative approaches derived from this knowledge will become more common. During the mapping process it will be necessary to improve the assessment of poverty. This may be done by adding or deleting indicators based on developing these with the rural poor. It may also be necessary to define indicators of poverty/ vulnerability/deprivation/food security by establishing a weighted system that more correctly reflects the level of poverty of the individuals and villages concerned. The development of tools to increase and communicate our knowledge with respect to poverty is the only way to find solutions to deprivation and poverty in Mali and Niger.

PROJECT OBJECTIVES

In the Niger, The World Bank funded a three-phase project included a comprehensive assessment of need, data collection, indicator development, atlas development, institutional analysis, evaluation of capability, and data use for investment. For Mali, US AID Mali funded an initial assessment of need for poverty/mapping vulnerability was conducted and identification of resources for implementing a system.

PROCESS

Information is an essential ingredient for of sustainable development throughout the world. Whether it is investment in poverty reduction, sustainable agriculture or forestry, education or health care there is need for useable information systems that can integrate data from multiple sources. Accessible high quality can allow for an informed basis for planning, making decisions and the monitoring and evaluation of progress to program objectives. Assembling this system involves compiling the available databases at all levels from diverse sources and building local capacity for its sustainability. Listed below are four aspects of information management essential to sustainable development: 1. Assessment of the available information, its source, history and validity. 2. Collection, organization, assimilation and synthesis of the available information. This is the baseline for future analyses. 3. Validation of our knowledge base and is provided through an organized monitoring and evaluation process and a distributive process involving multiple shareholders in an interoperable framework. 4. Assurance that local experts are receiving training that will insure the continuation of the system.

Assessment of available information allows decision makers to evaluate the needs of a country or region with respect to developmental, social and environmental parameters. This step is often referred to as a needs analysis study. During this step the team visited as many data and information repositories in Mali (20) and Niger (25) as possible, evaluated the data, review the sources and assessed the data gaps within the context of each country’s needs. The data reviewed and assessed included but is not limited to: census, socio-economic, health, agricultural as well as climate, environmental and other natural resources. This was also the initial opportunity to enlist these data gatherers as stakeholders in a future integrated information system.

The creation of a good information baseline is imperative as the foundation for a sustainable approach to economic development. To make rational decisions and to plot progress and growth or change of any kind it is vital to have a clear understanding of the basic elements that make up a country’s human and environmental resource base.

The third aspect of information management in support of sustainable development includes the establishment of a post-baseline monitoring and evaluation system.

The fourth area is in local capacity. Training is specifically tailored to meet the local capacity and programs in need.

These four information management processes form the basis for a credible institutional framework in support of sustainable development. Healthy, long term development cannot be achieved without information on the society in question and the social, economic and environmental building blocks that underpin sustainability. Stone has conducted a number of needs assessments to evaluate the potential of a country or area in order to create national, regional or local information systems. Stone has also assessed the institutional, human, and technological requirements of such systems and proposes the practical long-term solutions for the creation of sustainable systems. Stone and its African associates have made it the rule to assess local capacity and then focus on its use and development. The development of local capacity extends to the support of communities and the use of indigenous expertise. Finally Stone has developed the tools, has the expertise and the venues to permit and support information system interoperability. Such an approach allows for the integration and sharing of information and data inter- and intra-nationally and is a sine qua non of sustainable development.

PROCESS INTERVIEW/LEARNING THE LANDSCAPE

A key aspect of both projects involved interviewing key players and stakeholders in the poverty reduction efforts and the data store keepers. This effort involved setting up interviews and mobilizing to reach offices that were sometimes not

DATA GATHERING Our data gathering technique involved first conducting ministry or organization interviews to help with the needs assessment part of the project. This included questions on the availability of data and whether they would be willing to share it with us. In most cases this was not a problem and a second meeting was set up. A second meeting was arranged to collect the data. This was easier said than done. In some cases the only source of data was what was contained on the hard drive of 8086 computers with only one floppy disk that did not have “PKZip” software installed. The tools of our work included having copies of PKZip, a portable CDR writer, a memory stick reader (requiring windows 98 or newer versions of the operating system). All these techniques turned out to be relatively effective.

DATA QUALITY

In most cases the data retrieved did not contain any documentation as to its origin or quality. Attempts were made to document what was found. A database of databases was completed in Niger using MS Access. In the case of the Niger’s Preliminary Census, we discovered by mapping the latitude and longitudes that 1000 villages were located outside the country. During examination, about 600 of the village coordinates were transposed. The remaining errors were unknown. On investigating the cause of the transposition, it turned out the coordinates were manually entered onto the census form from a GPS unit and the enumerator did not know the latitude from the longitude.

Boundary differences are fairly common. The need for harmonization is real. Based on our work we believe that such efforts will not be too burdensome, but without a standards authority and coordinating body, it might be a futile effort. In Mali, they have recently adopted new/revamped boundaries for communes as part of their decentralization of government efforts. These 696 entities do not have accurate demarcated boundaries, yet they are the new focus of all investment and democratization efforts.

IDENTIFYING REPRESENTATIVE INDICATORS BASED ON AVAILABLE DATA

The current poverty reduction operational framework in both countries initially lacked an effective tool for identifying, measuring and monitoring poverty at the village level. Such a tool is needed to prepare a baseline for all the other related work including: monitoring and evaluation of poverty through time as well as for measuring the impact of government and partnership programs and investments and monitoring and evaluating the performance of poverty reduction efforts and policies.

After reviewing a number of local poverty reduction reports on available information on poverty indicators, the consultant team developed a partial schematic of indicators. These indicators were considered as being critical to the development of a poverty assessment. These have been further defined as indicators within a hierarchical structure in two broad categories: social indicators of poverty and environmental/resource indicators of poverty.

It is clear that both countries require a poverty assessment methodology based on the creation of a multi- indicator baseline, but also requires long-term monitoring of poverty by village and commune as well as effective impact and performance monitoring and evaluation tools. The most effective way of providing for this multiple objective is the creation of a national information system (Système National d’Information du Mali, SNIM). This system would support not only the objectives described above but also provide the means for assessment of the food security situation, monitor disaster assistance requirements and provides the basis for conflict prediction and environmental/degradation/desertification monitoring.

The following tables were developed as part of the Mali project work (February 2003) and provide the initial outlines for two important support systems for poverty reduction and the creation of a national information system. Table 1 provides a clarifying perspective on the three levels of indicator development and reporting required for effective poverty reduction. This table was developed to provide a guideline for effective M&E. This table was also created because of the confusion evident at the two- day workshop.

Because our initial focus was on creating a poverty baseline we developed Table 2: Baseline and Monitoring Framework for Poverty Assessment. This table provides an illustration of the framework hierarchy of the proposed indicators required to systematically evaluation poverty and prepares a national poverty/vulnerability information system.

Table 3: Example Framework Matrix for Creating First Order Indicators offers an initial method to describe the technical method by example for characterizing village level in condition of poverty. This was developed to assist in Phase II work in Mali that the CSLP and the ministries involved would use their hand at sculpting the final approach to creating the Baseline of Poverty/Vulnerability and creation of the Atlas.

TABLE 1: 3 LEVELS OF MONITORING & EVALUATION

Performance: Indicators Government Policies Governance/Elections Development of local governing structures Increased development and use of a justice system Investments & Budgeting Procedures, etc. Impact: Indicators Income/Consumption Unemployment Taxes collected New Infrastructure, etc. Poverty: Indicators (see Table 2) By Village By Communes By Urban Areas By Area (Aires de Sante) TABLE 2: BASELINE AND MONITORING FRAMEWORK FOR VILLAGE/URBAN POVERTY ASSESSMENT Illustrative Schematic INDICATORS st nd rd SECTOR 1 Order 2 Order 3 Order SOCIAL Education Access to Schools: Government, Enrollments Matriculation Community, & Madersas Health Access to Health/Medicine Number/type of Practitioners Cases of Primary Diseases Life Expectancy Birth Rate Infant Mortality Economics Access to Transport Roads Paved, Laterite & Paths Railroads Air Water Means of Transport Means – Private Cars, Bicycles, Donkey, etc. Means – Public Buses, Trains

Access to Communications Telephone Radio Internet Access to Markets Local, National, International Cattle, Agricultural, Consumer Access to Tools Urban Service Tools Rural Farm Tools

Access to Jobs Business Formation Access to Goods Access to Credit/Investment Institutions Central Regional Communal NGOs Private Donor ENVIRONMENTAL/ RESOURCES Resource Access to Water Fluvial Precipitation Groundwater Access to Food Access to Arable Land Capacity- rain /soil Capability - to produce Amount of Land Access to Energy Wood/Charcoal Bottled Gas Environment Parks Biodiversity Carbon Sequestration First Order Database Field Item Technique Access to Schools Decentralization-Village Total Primary Schools 1. Select all villages with schools 2. Buffer selected schools with selected distance, e.g., 5 km. 3. Reverse the selection and code as not having access to school Access to Irrigation Hydrology-IGM Location of Rivers and streams. 1. Buffer all hydrography by appropriate Topography. distances, e.g. .5, .75, 1 km. Soil types 2. Select all villages in buffered area 3. Reverse selection & code as not having access to water with different value based on distance. Access to Drinking Water Decentralization-Village Total Drinking Fountains and 1.Select all villages with drinking Wells water/wells 2. Buffer selected villages by selected distance, e.g., 5 km. 3. Reverse the selection and code as not having access to drinking water.

TRANSFORMING DATA INTO INDICATORS

Once the indicator schema was developed, how the data that is available would fit the indicators. In Niger we were fortunate to have census data of recent vintage that had many of the factors of interest so that worked out nicely.

#

# Villages < 500 Population #

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#

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Villages > 500 Population #

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Figure 2: Level of Vulnerability by Village and Cantons

CREATING THE PRELIMINARY ATLAS OF POVERTY/VULNERABILITY The construction of the Niger Atlas required the compilation and preparation of ten databases selected from the many collected. This task was straight forward following agreement on indicators. The resolution of the data makes a large difference on its utility. The Atlas was produced in English and in French. The primary goal of the consultant’s mission was to create a Preliminary Atlas of Poverty and Vulnerability of Niger in support of the GON and the World Bank supported CAP and PRSP programs. The ultimate goal was to create a map of Niger that identifies villages suffering from the effects of poverty. The objective was to create a series of visual representation in the form of an Atlas that portray human deprivation in the socioeconomic and natural resources or environmental context. Once the individual maps were prepared to show the various parameters of poverty, another map was prepared combining or superimposing these indices. This map constitutes a summary of poverty or a multiple deprivation index map. (MDI)

The Atlas was created at a national scale because of the availability of national level data sets. However all the data sets can be disaggregated to the Arrondissement or Canton level if more detail is needed. Furthermore the data can be analyzed spatially in terms of the number of villages per unit area or in terms of population by village or population per unit area or by political or administrative entity. It is also important to note that the summarized statistics for each map are only for villages for which a preliminary census was taken. The Atlas and the four related reports from these projects are available by on the web. Figure 3 provides a view of how the use of this kind of representation can assist in improved investment decisions. $$ $ $ $ $ #S $$ $ $ $ $ $ $ $$ $ $ $ $ #S $ #S $ $ #S $ $ $$ $ #S $ $ $ $$ $ $$ $ $ $ $ $ $ $ $ $$ $$ $ $ $ LÉGENDE$ $ $$ $ $ $ $ $ $ Region de Maradi #S $ $$ $ $ $ $ $ $ $$ $ #S $$ $ $ $ $ Vill ag es > 500 $ $ $ $ $ #S $ #S $$$ $ $ 0 - 2 in dic at eu rs de p auv ret é/ vul né rab ili t é $ $ $ $ $ $ $ #S 3 - 4 in dic at eu rs de p auv ret é/ vul né rab ili t é $ $ $ $ $ $ #S $ #S #S 5 - 6 in dic at eu rs de p auv ret é/ vul né rab ili t é $ $ #S #S $ $Vill ag es < 500 $ $ $ $ $ $ $ $ $ $ 0 - 2 in dic at eu rs de p auv ret é/ vul né rab ili t é #S $$ $$ $ $ $$ $ $$ $ 3 - 4 in dic at eu rs de p auv ret é/ vul né rab ili t é $$ $ $ $ $ $ $ $$ $ $ $ $ 5 - 6 in dic at eu rs de p auv ret é/ vul né rab ili t é $$$$ $$ $ #S $$ $ $ $ $ $ $$ #S $ $ Can t on Bo un dar y $ #S$ $$ #S$ $ $$ PGRN -Si tes $$ $ $ $$ $$ $ #S$ $ $$ $$ $$ $$ $ $ $$$ PDLTZ -Sites $$$$ $ $ $ $$$$$$ $ $$ $ $$ 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Figure 3: Spatial Integration of Project Investment Data with Village/ Canton Poverty/Vulnerability Data LESSONS

• There is a large quantity of lot of local data available to develop village level poverty/vulnerability assessments. Finding, collating, assessing it is a large but doable task. • There is need for education in the value and purpose of separating baseline from ongoing data collection. There is confusion over what is being measured for what purpose. • One should never underestimate the value of demonstrating the power of maps. It is not a well established medium for a message in these countries. The power of the story portrayed in a map is awesome. • Sharing of data between local organizations is a very valuable. Many organizations are enough separated from each that they do not have an opportunity to exchange. Facilitating a collaborative model of GIS will go a long way toward empowering local talent. • Using “living condition” type indicators is a far more realistic approach to understanding poverty/vulnerability. Standard economic methods for characterizations are woefully inadequate to understand sub national poverty. Multilevel indicators provide a much improved tool for targeting investments. • There are many talented and skilled local resources. • These efforts will not be successful without the creation/sanctioning of formal coordinating/integrating body. • Adopting data standards, particularly coding schemes, is a critical upfront requirement. • There needs to be established a formal data repository/clearinghouse for a multilevel information system to work. • There is a high need for a high speed network to be established between the primary users. • Our efforts have pointed out the need for considerable more coordination between donors. This can take the form of monthly meetings among the interested donor and national organizations. • Clearly there is not enough special purpose poverty mapping dollars available to build the national information infrastructure. The integration and development of the national information infrastructure should include investment from sectoral investments from health care, education, infrastructure and democracy building investments. • There is a large need for setting up a long term training program. Ideally this should be situated at the university. Exchange programs for local technicians and faculty with donor countries would also expand technical and analytical capability. • Long investments in the university laboratories would further advance the development of the national information infrastructure. • A collaborative effort is needed in building “Poverty/Vulnerably Reduction Data Model.”

ACKNOWLEDGEMENTS

Andrew Stancioff, my project team member and co-author of the multiple project reports.

In addition the other people who have helped in supporting these projects and/or in forming some of the ideas contained in these reports and paper: Daniel Sellen and Jeff Bergen, The World Bank Dennis Bilodeau and Pamela White, US AID Mali Issa Garba & Ari Arimi, our colleagues in Niger Moise Ballo, Ph.D., our associate in Mali And all the wonderful people interviewed and assisted us in the Republics of Mali and Niger

REFERENCES Healy, D.J., and Stancioff, A., Stone Environmental Inc., March 2001, Phase I: Preliminary Atlas of Poverty /Vulnerability of Niger, Project Report, The World Bank #7113660, Montpelier, VT USA

Healy, D.J., and Stancioff, A., Stone Environmental Inc., July 2001, Phase II: Identification of an Institutional Framework For a Data And Information Support System For Poverty Reduction In Niger, The World Bank #7113660, Montpelier, VT USA

Healy, D.J., and Stancioff, A., Stone Environmental Inc., July 2002, Phase III: Development of a Geographic Information System in Support of Poverty Reduction, The World Bank #7113660, Montpelier, VT USA

Healy, D.J., and Stancioff, A., Stone Environmental Inc., February 2003, Phase I: Needs Assessment: Creation of a Preliminary Atlas of Poverty/ Vulnerability & Assistance in Building an Information System for Mali, US AID Mali # 688-G-00-02-00069-00, Montpelier, VT USA

These reports can be found at: http://www.stone-env.com/services/aim-projects.html

AUTHOR INFORMATION

David J. Healy, Vice President Stone Evironmental, Inc. 535 Stone Cutters Way Montpelier, VT 05602 USA Phone / 802. 229.4541 Fax / 802. 229.5417 Email / [email protected] Web Site / www.stone-env.com