1. It would be interesting to hear what approaches and geo data could be used to measure the potential spatial access to urban facilities (health services for instance).
Answer: Service area analysis is a standard spatial analysis method to estimate the potential access to facilities. This method uses network analysis to estimate the distance and time taken to access facilities.
2. Pre-post datasets do not necessarily allow for making attribution/causal claims. How are you dealing with this?
Answer: The data itself doesn’t lend to attribution. There are two ways we have been dealing with it. One is to consider all the confounding factors that could affect the results. The other way we deal with it is by using other evaluative evidence in a mixed-method framework. For instance, combining the satellite data results with the qualitative methods.
3. Are there examples for collecting qualitative information or analysis, and if so – how?
Answer: Geospatial data could be qualitative as well as quantitative. One example of Qualitative geospatial data can be collected using a smartphone using Open Data Kit. The use of such tools allows integrating interviews with spatial locations.
4. Geospatial data is indeed interesting – but often times the data is hard to find or is private – Are there open data sources that you can recommend?
Answer: The choice of data would depend on the evaluation questions. However, we would like to point out that more and more of the geospatial and remote sensing data are becoming freely available. For GIS, you can check The Humanitarian Data Exchange, and for satellite data, NASA and ESA would be a good start.
5. Do these methods lend themselves well to the work of small NGOs who work on behaviour change at a much smaller scale? For example, personal hygiene, sexual and reproductive health, civic participation?
Answer: Geospatial data and its mapping is hugely powerful for any context but can be expensive. If a small NGO has resources, it can be conducive to use such methods for gathering evidence at the grassroots level, especially in some of the contexts stricken by conflict and fragility, whether the states are affected by an ongoing crisis or not. For example, the social media data (e.g., people complaining about cold) can be taken as an example and develop a geographical framework on it, representing a visualization of personal hygiene vs. the outbreak of diseases such as flu. Relevant stakeholders and donors can then be accessed for designing and funding interventions around vitamin supplements, flu jabs, etc. The same applies to SRH and civic participation. Grassroots organizations, to our knowledge, are far better placed to use such data and suggest remedies of societal or environmental issues because they are closer to reality and can easily enrich geo-location data with real-world examples on the ground.
*This blog post was first published at the European Evaluation Society’s website.