Surveillance as a Core Intervention to Strengthen Malaria Control Programs in Moderate to High Transmission Settings

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  • 1 Malaria Branch, Centers for Disease Control and Prevention, Atlanta, Georgia;
  • | 2 ICF, Rockville, Maryland;
  • | 3 Malaria Consortium, London, United Kingdom;
  • | 4 The Global Fund to Fight AIDS, Tuberculosis and Malaria, Geneva, Switzerland;
  • | 5 National Malaria Control Program, Conakry, Guinea;
  • | 6 Research Triangle International, Conakry, Guinea;
  • | 7 National Malaria Control Program, Maputo, Mozambique;
  • | 8 National Malaria Elimination Centre, Lusaka, Zambia;
  • | 9 National Malaria Control Program, Dakar, Senegal;
  • | 10 President’s Malaria Initiative, Washington, District of Columbia

New tools are needed for malaria control, and recent improvements in malaria surveillance have opened the possibility of transforming surveillance into a core intervention. Implementing this strategy can be challenging in moderate to high transmission settings. However, there is a wealth of practical experience among national malaria control programs and partners working to improve and use malaria surveillance data to guide programming. Granular and timely data are critical to understanding geographic heterogeneity, appropriately defining and targeting interventions packages, and enabling timely decision-making at the operational level. Resources to be targeted based on surveillance data include vector control, case management commodities, outbreak responses, quality improvement interventions, and human resources, including community health workers, as they contribute to a more refined granularity of the surveillance system. Effectively transforming malaria surveillance into a core intervention will require strong global and national leadership, empowerment of subnational and local leaders, collaboration among development partners, and global coordination. Ensuring that national health systems include community health work can contribute to a successful transformation. It will require a strong supply chain to ensure that all suspected cases can be diagnosed and data reporting tools including appropriate electronic devices to provide timely data. Regular data quality audits, decentralized implementation, supportive supervision, data-informed decision-making processes, and harnessing technology for data analysis and visualization are needed to improve the capacity for data-driven decision-making at all levels. Finally, resources must be available to respond programmatically to these decisions.

Author Notes

Address correspondence to Alison Fountain, Malaria Branch, Centers for Disease Control and Prevention, Atlanta, GA. E-mail:

Financial support: Support for this paper was provided by the U.S. President’s Malaria Initiative.

Disclaimer: The findings and conclusions in this report are those of the author(s) and do not necessarily represent the official position of the Centers for Disease Control and Prevention or the U.S. Agency for International Development.

Authors’ addresses: Alison Fountain and Julie Thwing, Malaria Branch, Centers for Disease Control and Prevention, Atlanta, GA, E-mails: and Yazoumé Yé, ICF, PMI Measure Malaria, Rockville, MD, E-mail: Arantxa Roca-Feltrer, Malaria Consortium, London, UK, E-mail: Alexander Rowe, The Global Fund to Fight AIDS Tuberculosis and Malaria, Malaria, Grand-Saconnex, Genève, Switzerland, E-mail: Alioune Camara, Ministry of Health, National Malaria Control Program, Conakry, Guinea, E-mail: Aissata Fofana, Research Triangle International, StopPalu, Conakry, Guinea, E-mail: Baltazar Candrinho, Mozambique Ministry of Health, Maputo, Mozambique, E-mail: Busiku Hamainza, Ministry of Health Zambia, National Malaria Elimination Centre, Lusaka, Zambia, E-mail: Medoune Ndiop, Senegal National Malaria Control Program, Dakar, Senegal, E-mail: Richard W. Steketee, PATH, MACEPA, Seattle, WA, and PATH, MACEPA, Ferney-Voltaire, France, E-mail: