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Am J Trop Med Hyg. 2017 Sep;97(3_Suppl):9-19. doi: 10.4269/ajtmh.15-0363.

Framework for Evaluating the Health Impact of the Scale-Up of Malaria Control Interventions on All-Cause Child Mortality in Sub-Saharan Africa.

Author information

MEASURE Evaluation, ICF, Rockville, Maryland.
Center for Applied Malaria Research and Evaluation, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana.
President's Malaria Initiative, Bureau for Global Health, United States Agency for International Development, Washington, District of Columbia.
Department of Public Health, Erasmus MC, University Medical Center, Rotterdam, The Netherlands.
Avenir Health, Geneva, Switzerland.
United Nations Foundation, Washington, District of Columbia.
Independent Consultant based on Stockholm, Sweden.
Division of Data, Research, and Policy, Data and Analytics Section, United Nations Children's Fund, New York, New York.
President's Malaria Initiative, Malaria Branch, Division of Parasitic Diseases and Malaria, Centers for Disease Control and Prevention, Atlanta, Georgia.
The Global Fund to Fight AIDS, Tuberculosis and Malaria, Geneva, Switzerland.
Global Malaria Programme, World Health Organization, Geneva, Switzerland.
IBTCI, Vienna, Virginia.


Concerted efforts from national and international partners have scaled up malaria control interventions, including insecticide-treated nets, indoor residual spraying, diagnostics, prompt and effective treatment of malaria cases, and intermittent preventive treatment during pregnancy in sub-Saharan Africa (SSA). This scale-up warrants an assessment of its health impact to guide future efforts and investments; however, measuring malaria-specific mortality and the overall impact of malaria control interventions remains challenging. In 2007, Roll Back Malaria's Monitoring and Evaluation Reference Group proposed a theoretical framework for evaluating the impact of full-coverage malaria control interventions on morbidity and mortality in high-burden SSA countries. Recently, several evaluations have contributed new ideas and lessons to strengthen this plausibility design. This paper harnesses that new evaluation experience to expand the framework, with additional features, such as stratification, to examine subgroups most likely to experience improvement if control programs are working; the use of a national platform framework; and analysis of complete birth histories from national household surveys. The refined framework has shown that, despite persisting data challenges, combining multiple sources of data, considering potential contributions from both fundamental and proximate contextual factors, and conducting subnational analyses allows identification of the plausible contributions of malaria control interventions on malaria morbidity and mortality.

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