I am interested in the application of quantitative methodologies, especially geospatial analysis, to improve livelihoods.  

I am currently based at the International Centre for Insect Physiology and Ecology (icipe) in Nairobi, Kenya working on a project to reduce the negative impact of tsetse flies on livestock and in turn, improve farmer livelihoods.

I recently concluded a 2-year position with USAID-OFDA/Concern Worldwide on a project to develop quantitative indicators for slow onset humanitarian emergencies in urban informal settlements (i.e. slums).  The map below is an example of one of the outcomes from the project.  

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Using household level data on income, food security, and hunger we found that 1) informal settlements are not homogeneous and 2) the poorest and the most food insecure households are located in close proximity of each other.  

The areas in red show where extremely poor and food insecure (i.e. vulnerable) households cluster and the blue represents areas where relatively food secure, higher income households cluster.  

Information from this analysis helped focus a joint intervention effort by Concern Worldwide and World Vision into the areas of most need in 2014.  This is just one example of how quantitative analysis can help speed up and focus response into the most vulnerable areas of need.

Published in Development Southern Africa (January 2016).