Methodology

From wealth to health: modelling the distribution of income per capita at the sub-national level using night-time light imagery

Steeve Ebener^1*†, Christopher Murray^2†, Ajay Tandon^2† and Christopher C Elvidge^3†

• * Corresponding author: Steeve Ebener ebeners@who.int

• † Equal contributors

Author Affiliations

¹ Evidence and Information for Policy, World Health Organization, Av. Appia 20, 1211 Geneva 27, Switzerland

² Global Health Initiative, Harvard University, 104 Mt. Auburn Street, Cambridge, MA 02138, USA

³ NOAA, National Geophysical Data Center, Office of the Director, 325 Broadway Boulder, Colorado 80303, USA

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International Journal of Health Geographics 2005, 4:5 doi:10.1186/1476-072X-4-5

Published: 10 February 2005

Abstract

Background

Sub-national figures providing information about the wealth of the population are useful in defining the spatial distribution of both economic activity and poverty within any given country. Furthermore, since several health indicators such as life expectancy are highly correlated with household welfare, sub-national figures allow for the estimation of the distribution of these health indicators within countries when direct measurement is difficult.

We have developed methods that utilize spatially distributed information, including night-time light imagery and population to model the distribution of income per capita, as a proxy for wealth, at the country and sub-national level to support the estimation of the distribution of correlated health indicators.

Results

A first set of analysis are performed in order to propose a new global model for the prediction of income per capita at the country level. A second set of analysis is then confirming the possibility to transfer the country level approach to the sub-national level on a country by country basis before underlining the difficulties to create a global or regional models for the extrapolation of sub-national figures when no country data set exists.

Conclusions

The methods described provide promising results for the extrapolation of national and sub-national income per capita figures. These results are then discussed in order to evaluate if the proposed methods could not represent an alternative approach for the generation of consistent country specific and/or global poverty maps disaggregated to some sub-national level.