regional name. The committee emphasizes that its focus is on pre-event population estimation—having knowledge about who is likely to be at risk when an emergency strikes, so that the size and scope of the response can be estimated properly and mobilized. However, the collection of data in the post-event environment is also discussed, especially in terms of its reliance on pre-event estimations of the population at risk.


The Ideal Census Database for Estimating Populations at Risk

The ideal population database at the subnational level would probably be a population register, with data recorded for every person with respect to residence, place of employment, age, gender, and other relevant sociocultural characteristics, with the requirement that every person has to report each change in status and location. However, the cost and intrusiveness of such a scheme means that it is presently impracticable in all but a few countries. Data from the United Nations Statistics Division (UNSD) show that scarcely more than 70 million people worldwide (about 1 percent of the world’s population) live in a country with a population register, and all of them are in Europe (UNSD, 2005). The closest database that most countries come to this kind of register would be administrative sources for the purpose of voting, taxes, or driver’s licenses, which record age, gender, and residence and are updated routinely. However, such registers generally exclude children and may also exclude the most vulnerable individuals in a population because they do not drive, pay taxes, vote, or otherwise have need of a formal identification card.

Population registers are maintained at the local level, with events being registered by the municipal authorities. From this point the data may be relayed up to regional and national levels, creating a central population register. Data could, of course, remain at the local level and be shared at higher administrative levels only as needed. This would be one of the “bottom-up” approaches that international organizations such as the Asian Disaster Preparedness Center (ADPC) suggest be combined with the more traditional “top-down” approaches to data collection and analysis (ADPC, 2006). The usefulness of local data depends, however, on the ability of relief organizations to access and integrate those data into standard methods of analysis. Thus, an integration of top-down standards and bottom-up data collection would probably yield the most reliable and useful type of population register.

Until resources become available to generate ideal population databases in all countries, the best working set of data by which to estimate populations at risk almost certainly comes close to what is available for countries

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