FacebookTwitterLinkedInEmailThe following is a guest post by Ruth Ashton of MEASURE EvaluationCHAPEL HILL, NC―A new study released today in the Lancet’s eClinicalMedicine shows that routine health management information systems are an important tool for determining the impact of malaria investments in Zanzibar. Demonstrating the effectiveness of interventions is critical for malaria elimination efforts, but incorporating unexposed comparison groups in study designs is often challenging. This study, funded by the United States President’s Malaria Initiative, demonstrates it is possible to conduct rigorous evaluations of malaria interventions without a comparison group.
This study collected routine malaria surveillance data from 129 public outpatient facilities across Zanzibar from January 2000 to December 2015, and used rigorous statistical analysis to explore if the number of new malaria cases changed following the introduction of key interventions. The study takes into account contextual factors — such as temperature, rainfall, access to malaria diagnoses, and changes in data reporting practices — strengthening its ability to attribute disease trends to tested interventions. Specifically, the study found that:
Introduction of artemisinin-based combination therapy (ACT) in 2003 led to a rapid decline in malaria cases in Zanzibar from September 2003 to December 2005.
The number of new malaria cases in Zanzibar remained low between 2006 and 2015 when vector control (insecticide-treated nets and indoor residual spraying) and ACTs were in place.
“Zanzibar will benefit from this research because we now know that we can accurately keep tabs on our malaria trends through our information systems—even as we work to improve those systems further,” says Abdullah Ali, MD, director of the Zanzibar Malaria Elimination Program, adding that HMIS data can be used for decision making. Use of HMIS across Africa will likely expand with improvements in data completeness, timeliness, and quality as well as inclusion of surveillance as a core intervention in the World Health Organization’s 2016–2030 Global Technical Strategy for Malaria.
This study can be adapted to conduct robust impact evaluations in other countries using existing data, particularly in low malaria transmission settings, where other methods are cost-prohibitive. Special surveys to monitor changes in transmission or malaria burden become progressively more expensive as transmission goes down.
Ruth Ashton is lead author of the study, research assistant professor at Tulane University’s School of Public Health and Tropical Medicine and senior evaluation specialist with the MEASURE Evaluation project—USAID, which supported the study.
Citation: Ashton R., et al. Use of routine health information system data to evaluate impact of malaria control interventions in Zanzibar, Tanzania from 2000-2015.eClinicalMedicine, DOI: https://doi.org/10.1016.j.eclinm.2019.05.011https://www.thelancet.com/journals/eclinm/article/PIIS2589-5370(19)30089-6/fulltext
The following is a guest post by Ruth Ashton of MEASURE Evaluation
CHAPEL HILL, NC―A new study released today in the Lancet’s eClinicalMedicine shows that routine health management information systems are an important tool for determining the impact of malaria investments in Zanzibar. Demonstrating the effectiveness of interventions is critical for malaria elimination efforts, but incorporating unexposed comparison groups in study designs is often challenging. This study, funded by the United States President’s Malaria Initiative, demonstrates it is possible to conduct rigorous evaluations of malaria interventions without a comparison group.
This study collected routine malaria surveillance data from 129 public outpatient facilities across Zanzibar from January 2000 to December 2015, and used rigorous statistical analysis to explore if the number of new malaria cases changed following the introduction of key interventions. The study takes into account contextual factors — such as temperature, rainfall, access to malaria diagnoses, and changes in data reporting practices — strengthening its ability to attribute disease trends to tested interventions. Specifically, the study found that:
