Operational modelling to guide implementation and scale-up of diagnostic tests within the health system: exploring opportunities for parasitic disease diagnostics based on example application for tuberculosis.

Abstract

Research and innovation in the diagnosis of infectious and parasitic diseases has led to the development of several promising diagnostic tools, for example in malaria there is extensive literature concerning the use of rapid diagnostic tests. This means policymakers in many low and middle income countries need to make difficult decisions about which of the recommended tools and approaches to implement and scale-up. The test characteristics (e.g. sensitivity and specificity) of the tools alone are not a sufficient basis on which to make these decisions as policymakers need to also consider the best combination of tools, whether the new tools should complement or replace existing diagnostics and who should be tested. Diagnostic strategies need dovetailing to different epidemiology and structural resource constraints (e.g. existing diagnostic pathways, human resources and laboratory capacity). We propose operational modelling to assist with these complex decisions. Projections of patient, health system and cost impacts are essential and operational modelling of the relevant elements of the health system could provide these projections and support rational decisions. We demonstrate how the technique of operational modelling applied in the developing world to support decisions on diagnostics for tuberculosis, could in a parallel way, provide useful insights to support implementation of appropriate diagnostic innovations for parasitic diseases.