Tools and Methods for Estimating Populations at Risk from Natural Disasters and Complex Humanitarian Crises (2007) / Chapter Skim
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5 Population Data and Crisis Response in Mali, Mozambique, and Haiti
5 Population Data and Crisis Response in Mali, Mozambique, and Haiti
Pages 126-148
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From page 126... ...
with outdated national population records at the time of the disasters. The comparisons illustrate that good, georeferenced population data exist, as indicated in Chapter 2, but that the presence of good population data sets and the tools and skills to use them does not in itself guarantee effective within-country or international aid response to a subnational population affected by a disaster (see also Chapters 3 and 4)
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To this end, we contacted professionals from these countries with a set of questions regarding this study, together with invitations to our workshop. With direct and very valuable comment and participation received only from Mali, the committee supplemented its factual knowledge regarding population data and its use in emergency and development situations in Mozambique and Haiti by contacting other persons and organizations external to the national offices of these countries.
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Two crises are discussed for Mali in this chapter: a locust infestation and a civil rebellion. These crises became humanitarian disasters affecting vulnerable groups of people and demonstrate how both natural and human-induced events exerted pressure on subnational populations in terms of food security, health, and economic stability.
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12 populatIoN Data & CRISIS ReSpoNSe IN MalI, MozaMbIQue, & haItI contained the locusts (FAO, 2004a)
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, and some of these data are digitally georeferenced to the village level. Existing population data in Mali at the time of the 2004 locust invasion included two National Censuses of Population and Habitat (1976, 1998)
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The committee did not locate published analyses of the use (or lack of use) of previously existing population data in connection with the Touareg rebellion; such data could have been employed for purposes of relief and repatriation of refugees displaced to neighboring countries during the con BOX 5.1 Applications of Population and Demographic Data in Preparedness and Response to Threat of Locusts • To coordinate local communities prevention, surveillance, and control mea sures, mitigating the need to respond to a food security crisis and reducing expenses of air support to conduct intensive crop protection spraying and surveillance activities • To plan food stores (to mitigate effects of future locust invasions)
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The experience gained in collecting and using these data is illustrative of the network of factors involved in estimating and putting to use subnational population data collected during and immediately following a disaster, and is explored briefly here. The refugee and repatriation situation was one focused upon distributing food aid, ensuring access to clean water, and facilitating cross-border registration and peaceful transfer of refugees back to Mali.
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133 populatIoN Data & CRISIS ReSpoNSe IN MalI, MozaMbIQue, & haItI tion from this country compared to repatriation from the other asylum countries (UNHCR, 1998)
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, and the magnitude of the flooding was beyond what the disaster simulations had attempted. The INGC, in conjunction with the Mozambique National Statistical Office, was nonetheless able to use and distribute the 1997 census data, in digital, georeferenced form and make them available to international aid organizations present in the country throughout the emergency response period.
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The digital census data on CD were linked to geographic information systems (GIS) and new local population surveys conducted during and directly after the flood to produce updated population and demographic data in real time to relief agencies for use in aid acquisition and distribution.
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. Further efforts to increase disaster preparedness through better analysis of population data after the floods also emerged through technical cooperation between USAID, INE, and the International Programs Center (IPC)
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FIgURE 5.3 Map of flood-affected populations in Mozambique contains geographically referenced population data from the Mozambique census together with geographically referenced data including the location of the Zambezi River, shelters, cities, potentially affected settlements, primary and secondary roads, and modeled flood areas. Although hand-drawn maps like that shown in Chapter 3, Figure 3.5, are practical and accurate, digital maps that incorporate census data are most desirable because the digitally referenced data can be updated quickly and potentially distributed widely to responders and emergency managers, if the appropriate hardware and power or electrical requirements can be assured.
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. Haiti was near the bottom of the UNDP "Disaster Risk Index" (UNDP, 2004)
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The year 2004 was particularly difficult for Haiti: the coup d'etat in early 2004 was followed by a May 2004 flood and accompanying mudslides that were responsible for more than 2,000 deaths in both Haiti and the Dominican Republic. This background is important in understanding the response to Tropical Storm Jeanne and the use of population data in the disaster relief and recovery period.
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10 FIgURE 5.5 Estimated population distribution for Haiti and the Dominican Republic based on LandScan data. SOURCE: UNOSAT, LandScan 2002, Global Insight Plus / Europa Technologies Ltd.
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. STRENgTHS AND LIMITATIONS OF POPULATION DATA EMPLOyED IN DISASTER RELIEF AND DEvELOPMENT Digitally accessible, current, georeferenced national census data can play an important role as part of a disaster relief effort.
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The national data, with additional information from the new surveys, were then incorporated into contingency plans by the INGC that were put into use when the next year's floods arrived. No relief or preparedness planning effort is based solely on the existence of national, georeferenced census data, but the committee's view is that the effective delivery of relief aid and preparation for subsequent flood events in Mozambique were enhanced by the existence of such data, and by the capacity of the local NSO in conjunction with the INGC and cooperating international agencies to administer them.
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In Haiti, relief and development organizations responded immediately to the disaster produced by Tropical Storm Jeanne, but they did not have access to accurate and recent national census data. Public sources for population figures and estimates, including those from the United Nations, WHO, Save the Children, demographic and health surveys, and databases such as Gridded Population of the World (GPW)
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CONCLUSIONS The examples from these three country analyses reinforce some of the main issues brought forward in the preceding chapters of this report: (1) national census data, available digitally, in georeferenced form, and disaggregated to a subnational level, are of basic importance to efficient aid allocation in large, multi-organizational, international disaster response situations; (2)
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Lacking recent census information, these proxy data ought to be used with the understanding that they likely will not accurately represent the situation on the ground and will incorporate some inherent inefficiencies in delivery of relief or development aid. While the extent or frequency of a disaster should not alter fundamental preparedness schemes to respond to humanitarian crises, clearly the more extensive a disaster, or the higher the frequency of crises in a given region, the more people are affected, and correspondingly, the challenge to humanitarian assistance becomes greater.
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Such a study could include a statistically rigorous set of interviews with relief personnel at the field and central management levels, and in national statistical and emergency coordination offices. If conducted by a large international body with relatively good access to country-level data, results of such a study could serve to leverage the observations in this report which show that access to high-quality, geo-referenced population data can be of assistance in generating more effective disaster response.
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Identify ways in which subnational demographic and geographic data and tools could be used to help decision makers provide useful information to populations at risk. In National Research Council, tools and Methods for estimating populations at Risk from Natural Disasters and Complex humanitarian Crises.
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Foreign Disaster Assistance. Available online at http://cidi.org/disaster/00a/0122.html [accessed October 4, 2006]
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