[nb. this is an old post from when I started – the post here probably best represents what I’m working on]
A few weeks ago I started an economics PhD at the London School of Hygiene and Tropical Medicine, after The topic is an economic evaluation of an urban sanitation intervention in Maputo, Mozambique. I’ll be estimating cost-effectiveness of the shared sanitation programme led by Water and Sanitation for the Urban Poor (WSUP) in Maputo.
After about 10 years working in the WASH sector (in NGO policy research and then consulting), it is energising to be looking at a specific few questions in a lot of depth and having time to read and think a lot. I hope to find time to blog here about interesting ideas and papers that I come across along the way, as well as research challenges I am grappling with.
Maputo is a good place to look at my research questions, because LSHTM is involved in the ongoing ‘Maputo Sanitation’ (MapSan) trial of this intervention. MapSan has a Controlled, Before-and-After (CBA) study design, and is carrying out three rounds of health-related data collection (see protocol here). Their robust data on health effects of the intervention (which is complex and costly to collect) will be one of my two key data sources.
In health economics, cost-effectiveness analysis (CEA) involves dividing costs by outcomes. Accordingly, MapSan is already collecting the denominator of my calculation – my primary data collection will focus on the numerator (i.e. intervention costs).
Nonetheless, a further aspect of the PhD is to develop new measures of sanitation outcome based on wellbeing . My lead supervisor (the health economist Giulia Greco) has worked on these kinds of measures for other types of programmes, see e.g. this paper. This is important because traditional economic evaluation methods under-state the performance of public health interventions with multiple outcomes (see this paper). The PhD therefore has an empirical angle (‘traditional’ CEA of the intervention) and a methodological one (developing and testing new measures of sanitation outcome).
Why is this important? Urban sanitation is a huge challenge. For sanitation in general, behaviour change is more than half the battle. In urban Sub-Saharan Africa, however, most people already use a toilet. The biggest problem is that a large proportion of people are using low-quality pit toilets and, what’s more, little is being done about what happens when they fill up. See the graph below – there are 70 million urban Sub-Saharan Africans who use a toilet but which is unimproved and does not effectively contain excreta. Therefore, we need to move people up the sanitation ladder – but there is limited evidence on the cost-effectiveness of different options (more on that another time).
The focus of WSUP’s intervention (about which I’ll write another blog in due course) is moving people up the sanitation ladder from unimproved to “limited”, i.e. a latrine which is shared within a compound. In other words, it moves people from the yellow part of the graph below to the light green part.
Surprisingly, we don’t know a lot about the cost-effectiveness, and even the costs, of urban sanitation interventions. This is something which surprised me when trying to develop a cost-benefit analysis as part of of this project on Fecal Sludge Management which I led for the World Bank while at OPM. Battling with poor data on costs and outcomes was also a major challenge on this project on Value for Money I managed as part of a consortium for DFID. So this PhD topic comes out of c.5 years of frustration with poor-quality data. Hopefully in the next three years I can carry out some research which will move us forward a little on these questions. Another blog to follow on why all this matters…
source: JMP 2017 data from www.washdata.org