Optimising the delivery of routine malaria data quality assessments in Mozambique
Published:
Resources: Poster
Authors: Ann-Sophie Stratil, Maria Rodrigues, Sarmento Armando, Sergio Gomane, Kulssum Mussa, Baltazar Candrinho, Arantxa Roca-Feltrer
Modelling exercises can optimise operational delivery of routine data quality assessments and support institutionalising this approach.
Quality surveillance data are essential for malaria programmes to make accurate decisions, but the accuracy of reported data remains low. To address this, the National Malaria Control Programme in Mozambique has been implementing routine data quality assessments (DQAs) at health facilities since 2019. However, the influence of different operational factors on DQAs — including baseline accuracy, location and size of health facilities, frequency of DQAs and lags between visits — has never been systematically investigated. We developed a statistical model to aid optimisation of operational delivery of routine DQAs in Mozambique.
This poster was presented at the 71st annual meeting of the American Society of Tropical Medicine and Hygiene.
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Conference
American Society of Tropical Medicine and Hygiene Annual Meeting