Localising evidence for decision-making: participatory approach to inform schistosomiasis control. (30th September 2020)

• Record Type: Journal Article
• Authors: Fergus, C A; Allen, T; Parker, M; Pearson, G; Storer, L; Dawson, K
• Is Part Of: European journal of public health. Volume 30(2020)Supplement 5
• Publication Date: 2020-09-30
• Subjects: Epidemiology -- Europe -- Periodicals; Public health -- Europe -- Periodicals; 362.109405
• DOI: 10.1093/eurpub/ckaa166.064
• Languages: English
• ISSNs: 1101-1262

Abstract

Abstract: Background: The linear theories of change which ground many interventions do not account for the complex processes and systems in which they are implemented. This reductionist approach prioritises statistical methods which do not accommodate the stochastic, non-linear, dynamic interactions between humans and their environment. The inclusion of practitioners in the process of evidence development and utilisation of complex systems methods mitigates these issues and results in locally relevant, timely evidence for decision-making. Methods: The aim of this work was to develop localised evidence for decision-making for schistosomiasis control in Uganda, Malawi, and Tanzania. Workshops were conducted with practitioners from the Ministries of Health at various levels and partner organisations to identify evidence needs for their decision-making processes and perceptions of disease transmission and control activities. Participatory systems mapping was used to identify factors directly and indirectly related to transmission. The maps were synthesised to a master complex systems map, which served as the blueprint for a generalised spatial agent-based model and specific ABMs tailored to the evidence needs of decision-makers. Results: There was a gap in available evidence for practitioners to advocate for resources within the MoH and government budgets, as well as intervention efficacy and resource allocation. The adaptable and data-inclusive characteristics of the AMBs made them well-suited to produce localised outputs. Converted to NetLogo with a tailored user interface, these models were appropriate and responsive to the needs of decision-makers from village to national levels and across country contexts. Conclusions: Used together, participatory and agent-based modelling resulted in the development of responsive and relevant evidence for practitioner decision-making. This process is generalisable and transferable to other diseases and locations outside of those in this study. Key messages: The use of participatory systems mapping to develop agent-based models resulted in relevant and timely evidence for practitioner decision-making. The approach used here is transferable and generalisable outside schistosomiasis control and the contexts in this study.