Introduction
The COVID-19 pandemic has seized almost every country in the globe; in India, the number of cases has been steadily rising across waves. The south Indian state of Kerala was the first to announce a case in early 2020; the state’s response was hailed but has also led to some circumspection about what could have been done better.1 2 In a recent global seminar, coordinated efforts in the northern district of Wayanad were credited with saving lives and ensuring economic stability.3
At the time the pandemic broke out, that is, early January, our team had qualitative research underway in this district. Our study sought to understand the perspectives of front-line health workers as well as Kattu-nayakan (tribal) communities in this district of Kerala with respect to health service utilisation. It involved focus group discussions (FGDs) and group interviews with Kattunayakan tribal communities living in hamlets of this area, as well as front-line and facility level health workers tasked with serving them. We had been constructing case studies of these stakeholders from criterion-sampled hamlets, seeking to understand enablers and barriers to care from both the demand and supply side. As we completed one case study and were preparing to begin another, COVID-19 lockdowns were announced.
As research teams around us struggled to keep their research ongoing, we felt relief that our study, employed qualitative methods specifically designed to be sensitive to context.4 However, we were also mindful that our in-person fieldwork may eventually have to be replaced with other, digital or remotely administered methods. As we were working with participants from tribal populations for whom internet access was expensive and irregular, and phone ownership uneven, we anticipated that the most appropriate method would likely have to be telephonic interviews. We were, of course aware of the gamut of concerns when shifting from face-to-face interactions to digital media for data collection,5 which include problems with exclusion in recruitment, difficulties in maintaining flow and ensuring clarity during FGDs, as well as technical/accessibility-related constraints. There were also broader questions of ‘automating inequality’, that is stereotyping, penalising or excluding certain populations in the application of technology5 (including health research fieldwork), which we did not want to contribute towards.
Drawing on this and other literature, as well as inputs from other teams similarly seeking to continue fieldwork in virtuo, we amended our study protocol so as to enable telephonic group and individual interveiws adapting existing aspects of our fieldwork. This paper is a reflection on what we proposed to do, what we ended up doing, and the trade-offs that resulted.