Elsevier

Health Policy

Volume 92, Issues 2–3, October 2009, Pages 133-140
Health Policy

Using decision analysis to improve malaria control policy making

https://doi.org/10.1016/j.healthpol.2009.02.011Get rights and content

Abstract

Malaria and other vector-borne diseases represent a significant and growing burden in many tropical countries. Successfully addressing these threats will require policies that expand access to and use of existing control methods, such as insecticide-treated bed nets (ITNs) and artemesinin combination therapies (ACTs) for malaria, while weighing the costs and benefits of alternative approaches over time. This paper argues that decision analysis provides a valuable framework for formulating such policies and combating the emergence and re-emergence of malaria and other diseases. We outline five challenges that policy makers and practitioners face in the struggle against malaria, and demonstrate how decision analysis can help to address and overcome these challenges. A prototype decision analysis framework for malaria control in Tanzania is presented, highlighting the key components that a decision support tool should include. Developing and applying such a framework can promote stronger and more effective linkages between research and policy, ultimately helping to reduce the burden of malaria and other vector-borne diseases.

Introduction

Vector-borne diseases affect millions of people every year, mostly in tropical countries. In particular, malaria is the most deadly vector-borne disease, killing over one million people annually [1]. After substantial progress in battling the spread of malaria in the 1960s and 1970s, the number of reported malaria cases and the geographic extent of the disease grew dramatically in the past 25 years. Beyond mortality losses, malaria imposes devastating costs on local economies, through direct costs of treatment and prevention, indirect costs of lost productivity, and lower economic growth at the national and regional level [2], [3].

In the face of this substantial and growing public health challenge, many have emphasized the need for new and improved “technological” solutions such as malaria vaccines and genetic modification of vector populations [4], [5]. However, it is important to recognize that the malaria threat has continued to grow despite the existence of effective control technologies such as insecticide-treated bed nets (ITNs), indoor residual spraying (IRS), artemesinin combination therapies (ACTs), and rapid diagnostic tests. While there is evidence that each of these approaches may be effective in combating malaria, significant implementation challenges have prevented more widespread adoption of potentially effective solutions. Without more attention to these policy challenges, malaria control efforts will be severely hampered.

This paper examines the application of decision analysis methods to address the challenges of developing and implementing more effective malaria control policies. We enumerate key challenges that policy makers and practitioners face in their efforts to combat malaria and other vector-borne diseases. We argue that a comprehensive decision analysis framework can help to address these challenges, guiding the selection of more effective, evidence-based control strategies. After developing theoretical and practical arguments for the decision analysis approach, we present a prototype malaria decision analysis support tool (MDAST) for Tanzania.

Section snippets

A need for decision analysis to guide control of malaria and other vector-borne diseases

Malaria poses a unique set of challenges that limit decision makers’ ability to effectively confront and control the burden of this disease. Decision analysis offers several advantages that are particularly suited to the complex problem of controlling malaria and other vector-borne diseases [6]. Decision analysis is a structured approach to making choices, enabling a systematic evaluation of the consequences of alternative courses of action that one might take in the face of uncertainties about

Demand for decision analysis tools among East African stakeholders

To gauge the degree of interest in a decision support approach to malaria control, preliminary field work was conducted in Tanzania, Uganda, and Kenya in 2005–2007. Our interdisciplinary research team queried policy makers, researchers, and other stakeholders with semi-structured interviews and a small Internet survey of a dozen experts. We also conducted a workshop in Dar es Salaam in June 2006, and presented our conceptual framework to a national medical research conference in Arusha,

The malaria decision analysis support tool (MDAST): a prototype

In this section, we describe a prototype malaria decision analysis support tool that has been developed with the assistance of malaria decision makers in Tanzania. The development of MDAST draws on other applications of decision analysis to health issues in developing countries. For example, Hu et al. used decision analysis to study the policy implications of HIV infection and breast-feeding [25]. Bertolli et al. developed a decision analysis approach to examine a range of interventions to

Conclusions: using MDAST to promote evidence-based policy and policy-relevant research

Moving from the prototype to a more elaborated MDAST for Tanzania, we are focusing on making the tool more empirically based. We are currently engaged in: (1) expanding the prototype MDAST model components to better capture the specific processes involved in malaria transmission and control, and (2) populating the model using a number of datasets, including environmental variables, behavioral and social factors, data on malaria vectors and malaria cases, and costs and poverty data. In some

Acknowledgements

This research was supported by funding from the National Institute of Environmental Health Sciences, 1 P30 ES-011961-01A1, and from the Duke Provost Common Fund.

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