‘Imaginative captivity’ in modeling future maternal and child health outcomes: A critical analysis of the Lives Saved Tool (LiST)

The Lives Saved Tool (LiST) is a modeling software used to predict the impact of health interventions on maternal and child health and mortality in low-resource settings. LiST is more than a predictive software for maternal and child health. It is also a governance mechanism, organizing maternal and child health actors – including policy makers, program planners, NGOs, and researchers – to address maternal and child health according to donors’ preferences for cost-effective, standalone technical interventions. In this paper, I trace the history of LiST – from its early days as a series of spreadsheets created for a special issue in The Lancet by the Bellagio Group, a cohort of child survival researchers concerned about excess child mortality – to show how and why LiST data and frameworks narrow the scope of interventions considered appropriate for maternal and child health care in low-resource settings. LiST’s data and governance effects produce an imaginative captivity that sidelines other ways of knowing about maternal and child health in poor countries, circumscribing a fuller range of problem solving – such as listening to mothers, children, and local health care providers, and attending to the cultural, social and political economy factors of health – thereby limiting options for maternal and child health futures.