Breaking disciplinary silos to solve real-life puzzles

Professor Ian Scoones, Institute of Development Studies
February 12, 2018

The Dynamic Drivers of Disease in Africa (DDDAC) project focused on diseases that pass from animals to people. It investigated the links between these diseases (known as zoonoses), ecosystems, poverty, and the influence of wider global dynamics such as climate change. In Zimbabwe, we looked at trypanosomiasis (sleeping sickness in humans), a disease carried by tsetse flies. Puzzlingly, after nearly a century of control efforts, the disease still persists, and even seems to be on the rise.

Much conventional science, and associated monitoring and control efforts, have assumed uniform distribution of the dreaded tsetse fly– and therefore used standard techniques such as random sampling. Initially, the DDDAC project did the same. We used existing data and techniques we were familiar with, expecting that, by combining them, we would find the answer - falling into a safe, classic multidisciplinary approach. The team had different ‘work packages’ and proceeded with approaches we were comfortable with: the social scientists did a survey, the epidemiologists sampled blood from cattle, the entomologists trapped along transects, the Geographic Information Systems (GIS) specialist analysed their images. Driven by standard scientific routines and the pressure to publish in conventional scientific journals, we made the classic mistake of rushing into field investigations, without thinking collectively about research questions, hypotheses to test, and methodologies. From our disciplinary comfort zones, we did not ‘think outside the box’ or really listen to local knowledge.

However, it soon became clear that our standard multidisciplinary approach was not helping us to solve the puzzle. Individual pictures did not add up until we started to think together as a team. We started to pose more general questions – why was it that trypanosomiasis was persisting?  - and looking at each other’s’ data, interrogating our analyses. We went to the field together, discussed with villagers, walked transects across the sites with local people and carried out participatory mapping exercises with different groups. Abandoning our disciplinary silos made it easier to listen to villagers, who knew the disease landscape and its history. Villagers pointed to particular patches of land – small in size, with certain biophysical and social-cultural characteristics, distinct from the wider landscape, where tsetse flies could be found with a much higher prevalence. This was our ‘ah ha’ moment: because distribution is not uniform, random sampling – while statistically rigorous – is ultimately misleading.

Standard disease control approaches tend to adopt a blanket approach, ignoring complex socio-ecologies in fast-changing landscapes. Our research shows more targeted efforts will not only be more effective, but also cheaper.

With hindsight, our mistakes and challenges were not surprising, nor unique to our project. Breaking out of existing institutional cultures, structured around disciplines and sectors, is incredibly difficult. There are different languages and different styles of collecting, analysing and writing up data. Fieldwork means different things to different disciplines; as does paper writing, policy engagement, and so on. All these have to be negotiated. To work together we have to learn both new languages and cultures, and be patient and respectful. It is not easy, it is not quick, it is not cheap – but it is ultimately worth it.


Read the full papers:

People, Patches, and Parasites: The Case of Trypanosomiasis in Zimbabwe

Integrative modelling for One Health: pattern, process and participation