Zanzibar's malaria case notification (MCN) platform reports near real-time data on all malaria cases confirmed at public and private health facilities (index cases) and allows for case follow-up and reactive case detection of case household members (secondary cases).

Continued use of the MCN platform enabled Zanzibar to identify an additional 21.7% malaria cases, with an additional secondary case detected through reactive case detection for every 4.6 index cases.

Operational challenges affecting the MCN platform's full functionality and operationalization have included shortage of and delays in replacement of hardware, software bugs, strained human resources bandwidth, relevance and use of indicator selection, and data divergence across multiple health information systems.

To be fully functional and operational, a malaria surveillance platform such as MCN needs adequate resourcing, including timely provision and, as needed, hardware replacement, software maintenance, and adequate number of trained personnel that can manipulate, analyze, use, and act upon the data in the platform, definitions, and inclusion of indicators that are used by malaria programs for evidence-based decision-making and streamlining and interoperability with other health information systems.

Testing and treating asymptomatic populations have the potential to reduce the population's parasite reservoir and reduce malaria transmission. Zanzibar's malaria case notification (MCN) platform collects detailed sociodemographic and epidemiological data from all confirmed malaria cases to inform programmatic decision-making. We describe the design and operationalization process of the platform and other malaria surveillance resources that are enabling Zanzibar's progress toward malaria elimination.

The MCN platform consists of an interactive short message service (SMS) system for case notification, a software application for Android mobile devices, a visual question set and workflow manager, a back-end database server, and a web browser-based application for data analytics, configuration, and management. Malaria case data were collected from August 2012 to December 2021 and reported via SMS from all public and private health facilities to a central database and then to district malaria surveillance officers' mobile devices. Data included patient names, shehia (administrative area), and date of diagnosis, enabling officers to track patients, ideally within 24 hours of reporting. Patients' household members were tested for malaria using conventional rapid diagnostic tests (RDTs). Treatment using artemisinin-based combination therapy was provided for persons testing positive.

Between 2012 and 2021, a total of 48,899 index malaria cases were confirmed at health facilities, 22,152 (45.3%) within 24 hours of reporting; 41,886 (85.7%) cases were fully investigated and followed up to the household level. A total of 111,811 additional household members were tested with RDTs, of whom 10,602 (9.5%) were malaria positive.

The MCN platform reports malaria case data in near real time, enabling prompt follow-up of index cases and prompt testing and treatment of members in index case households. Along with routine testing and treatment and other preventive interventions, the MCN platform is foundational to the programmatic efforts in further reducing malaria and ultimately eliminating autochthonous malaria transmission in Zanzibar.

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