Using remotely sensed night-time light as a proxy for poverty in Africa

Abdisalan M Noor,Andrew J Tatem,Victor A Alegana,Peter W Gething,Robert W Snow

doi:10.1186/1478-7954-6-5

Abstract

BackgroundPopulation health is linked closely to poverty. To assess the effectiveness of health interventions it is critical to monitor the spatial and temporal changes in the health indicators of populations and outcomes across varying levels of poverty. Existing measures of poverty based on income, consumption or assets are difficult to compare across geographic settings and are expensive to construct. Remotely sensed data on artificial night time lights (NTL) have been shown to correlate with gross domestic product in developed countries.MethodsUsing national household survey data, principal component analysis was used to compute asset-based poverty indices from aggregated household asset variables at the Administrative 1 level (n = 338) in 37 countries in Africa. Using geographical information systems, mean brightness of and distance to NTL pixels and proportion of area covered by NTL were computed for each Administrative1 polygon. Correlations and agreement of asset-based indices and the three NTL metrics were then examined in both continuous and ordinal forms.ResultsAt the Administrative 1 level all the NTL metrics distinguished between the most poor and least poor quintiles with greater precision compared to intermediate quintiles. The mean brightness of NTL, however, had the highest correlation coefficient with the asset-based wealth index in continuous (Pearson correlation = 0.64, p < 0.01) and ordinal (Spearman correlation = 0.79, p < 0.01; Kappa = 0.64) forms.ConclusionMetrics of the brightness of NTL data offer a robust and inexpensive alternative to asset-based poverty indices derived from survey data at the Administrative 1 level in Africa. These could be used to explore economic inequity in health outcomes and access to health interventions at sub-national levels where household assets data are not available at the required resolution.

Highlights

Population health is linked closely to poverty
Comparable household assets data were available for 338 Administrative 1 units in 37 out of 56 African countries (Figure 1 & Table 1)
2.2% of the total area of the 37 countries was covered by night time lights (NTL), ranging from 0.07% in Chad to 17.28% in Swaziland while Egypt had 12.18% of area covered by NTL

Summary

Introduction

Population health is linked closely to poverty. To assess the effectiveness of health interventions it is critical to monitor the spatial and temporal changes in the health indicators of populations and outcomes across varying levels of poverty. Measures of poverty at household level are often computed from complex survey data on income, consumption or expenditure [5] These data are difficult to reliably collect at regular intervals nationally; are subject to significant reporting bias; show large fluctuations over time; or are seen as indicative only of the short term economic status of the sampled households [6,7]. In sub-Saharan Africa (SSA), most national household surveys have a standardized welfare module that routinely collects information on household assets and are used to report the socio-economic patterns in health outcomes [9,10] Several of these common asset variables have been shown to be associated with income and consumption [11,12] and this relationship is the basis of poverty mapping using small-area estimation methods [13,14]

Methods

Results

Discussion

Conclusion