A National Assessment of Zambia’s Malaria Surveillance System Performance for Elimination readiness by 2030

Abstract Background Malaria surveillance is the “eyes and ears” of public health in Zambia, providing the critical intelligence needed to track transmission, guide interventions, and evaluate progress toward elimination. As the backbone of malaria control, its performance reflects the system’s ability to detect cases, generate reliable data, and respond effectively to emerging threats. In this study, performance was assessed using a composite score derived from multiple survey indicators, offering a clear measure of how well the surveillance system is functioning. Methods A cross-sectional survey of health workers involved in malaria surveillance was conducted across ten Zambian provinces from 2022 to 2024 using a structured questionnaire administered via KoBoToolbox at facility, district, and provincial levels. Performance for each surveillance attribute was measured as the mean proportion of positive responses across mapped indicators, with scores at or above 80% considered to meet the performance standard. Districts were then categorized as high (≥ 80%), moderate (60–79%), or low performing (< 60%). Performance was defined as a single score that combines many different survey questions about how well the malaria surveillance system was working. Results Of the ten attributes evaluated, five (50%) met or exceeded the 80% performance threshold. The system achieved an overall mean score of 80.4%, marginally meeting the benchmark. Simplicity was the highest-performing attribute (93.8%) and Flexibility the lowest (57.6%). Acceptability had a composite score of 89.0%, Completeness at 87.1%, Sensitivity scored 84.9%, Usefulness at 84.0%, Timeliness (79.7%), Data Quality (78.5%), Positive Predictive Value (78.2%) and Stability (70.6%). Major challenges included inadequate logistics (62.3%), insufficient trained staff (48.1%), limited community health worker motivation (55.8%), and health worker attrition (34.2%). Conclusion Five surveillance attributes remain below the required performance threshold. Weak flexibility reduces the system's ability to adapt to case-based and foci-level surveillance. Weak stability threatens continuous case detection, especially in areas at risk of imported malaria. Poor positive predictive value and data quality reduce the reliability of confirmed malaria case data. Weak timeliness limits rapid case investigation and response within the 1-3-7 elimination framework. Improving these five attributes is critical for strengthening Zambia's malaria surveillance system and achieving malaria elimination by 2030.