The importance of data-informed decision-making: Impact of data quality assessments on routine malaria data

Authors: Sonia Enosse, Neide Canana, Joaquim Chau, Jossias Machava, Kulsum Mussa, Baltazar Candrinho, Maria Rodrigues, Ruth Kigozi, Hannah Edwards

The use and quality of routine malaria data can be improved through regular data quality assessments, supervision and data review, thus optimising programmatic decision-making.

Poor quality of malaria surveillance data affects understanding of malaria epidemiology and the effectiveness of interventions. This can result in ill-informed or untimely decision-making. In Mozambique, we aimed to assess the impact of embedding regular data quality assessment (DQA) activities and data use into programmatic decision-making.

This poster was presented at the Multilateral Initiative on Malaria (MIM) Society's 8th Pan-African Malaria Conference.