Use cases for genetic epidemiology in malaria elimination

Ronit Dalmat,Brienna Naughton,Erin M Stuckey,Jennifer Slyker,Tao Sheng Kwan-Gett

doi:10.1186/s12936-019-2784-0

Abstract

BackgroundWhile traditional epidemiological approaches have supported significant reductions in malaria incidence across many countries, higher resolution information about local and regional malaria epidemiology will be needed to efficiently target interventions for elimination. The application of genetic epidemiological methods for the analysis of parasite genetics has, thus far, primarily been confined to research settings. To illustrate how these technical methods can be used to advance programmatic and operational needs of National Malaria Control Programmes (NMCPs), and accelerate global progress to eradication, this manuscript presents seven use cases for which genetic epidemiology approaches to parasite genetic data are informative to the decision-making of NMCPs.MethodsThe use cases were developed through a highly iterative process that included an extensive review of the literature and global guidance documents, including the 2017 World Health Organization’s Framework for Malaria Elimination, and collection of stakeholder input. Semi-structured interviews were conducted with programmatic and technical experts about the needs and opportunities for genetic epidemiology methods in malaria elimination.ResultsSeven use cases were developed: Detect resistance, Assess drug resistance gene flow, Assess transmission intensity, Identify foci, Determine connectivity of parasite populations, Identify imported cases, and Characterize local transmission chains. The method currently used to provide the information sought, population unit for implementation, the pre-conditions for using these approaches, and post-conditions intended as a product of the use case were identified for each use case.DiscussionThis framework of use cases will prioritize research and development of genetic epidemiology methods that best achieve the goals of NMCPs, and ultimately, inform the establishment of normative policy guidance for their uses. With significant engagement of stakeholders from malaria endemic countries and collaboration with local programme experts to ensure strategic implementation, genetic epidemiological approaches have tremendous potential to accelerate global malaria elimination efforts.

Highlights

While traditional epidemiological approaches have supported significant reductions in malaria inci‐ dence across many countries, higher resolution information about local and regional malaria epidemiology will be needed to efficiently target interventions for elimination
Seven use cases are presented where genetic epidemiology approaches are informative to decision-making within the efforts of National Malaria Control Pro‐ gramme (NMCP)
The description section conveys, briefly, the objective sought by use of the method—what information the genetic epidemiology method is providing—as well as the current method used to achieve that objective in the absence of a genetic method

Summary

Introduction

While traditional epidemiological approaches have supported significant reductions in malaria inci‐ dence across many countries, higher resolution information about local and regional malaria epidemiology will be needed to efficiently target interventions for elimination. The application of genetic epidemiological methods for the analysis of parasite genetics has, far, primarily been confined to research settings To illustrate how these techni‐ cal methods can be used to advance programmatic and operational needs of National Malaria Control Programmes (NMCPs), and accelerate global progress to eradication, this manuscript presents seven use cases for which genetic epidemiology approaches to parasite genetic data are informative to the decision-making of NMCPs. In recent years, public health campaigns have achieved major reductions in malaria morbidity and mortality globally, with incidence decreasing by 18% globally between 2010 and 2016 [1]. A global scientific network providing framework for generating, integrating and sharing malaria parasite and vector genetic and genomic data is available through the Malaria Genomic Epidemiology Network (MalariaGEN) [6]

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