Abstract
Understanding the holistic impact of malaria during pregnancy is essential for improving maternal and child outcomes in malaria endemic settings. To be able to design appropriate research and conduct robust policy analyses, a comprehensive model of the underlying disease, representing the current understanding of mechanisms and consequences, is needed. This study aimed to illustrate a methodology to co-develop a disease policy model with expert stakeholders using malaria during pregnancy as a case study. An initial steering group was convened to develop a first model of malaria during pregnancy and its consequences for mother and child based on their understanding of the literature. Subsequently, this model was refined using a Delphi process to gain consensus amongst twelve experts working in the field of malaria during pregnancy, representing the disciplines of health economics, mathematical modelling, epidemiology and clinical medicine. The experts reviewed drafts of the conceptual model and provided feedback in two rounds of semi-structured questionnaires with the aim of identifying the most important health outcomes and relationships in both mother and child as well as the most relevant stratifiers for the model. Final consensus on any areas of disagreement was reached after two online meetings. The final model is a comprehensive disease policy model of malaria during pregnancy, including ten maternal and ten child health outcomes with four stratifiers. The model developed in this study should be of value to malaria researchers, funders, evaluators and decision makers, though some adaptation will be required for each specific context and purpose. In addition, the methodology and process followed in this study is replicable and can guide researchers aiming to develop a conceptual model for other conditions. The model resulting from this study highlights the complexity required to depict fully the consequences of malaria during pregnancy for both the mother and the child. It also demonstrates how to conduct a rigorous process to develop a disease policy model. In addition, the study has helped to identify a number of areas with scarce data and need for further research.