Methods

Study design and setting
The evaluation utilised a descriptive cross-sectional design to assess the performance of the community malaria surveillance system in the Bukombe District Council, Geita Region. The study was carried out in Bukombe District Council, one of the six councils in Geita Region, northwestern Tanzania. The district is largely rural with a population of approximately 426,000 people, living in 26 wards and 122 villages. Malaria transmission in the district remains perennial, with prevalence above 13.4% based on national malaria indicator surveys. Health services are delivered through 33 health facilities (one health center and 32 dispensaries). Community-based malaria surveillance through the iCCM program began in December 2024 and was operational in six service delivery points: Kerezia, Burumbaga, Nampalahala, Ihako, Msingo, and Igulike [8]

Description of the community malaria surveillance system
Case definitions
Suspected malaria: Any individual presenting with fever, with or without any other symptoms. All patients with suspected malaria should receive a diagnostic test for malaria, by microscopy or a rapid diagnostic test [1].
Confirmed malaria: Suspected malaria cases in which malaria parasites have been demonstrated in a patient’s blood by a rapid diagnostic test (RDT) [1].
Uncomplicated malaria case: Patient with symptomatic malaria parasitaemia without signs of severity or evidence of vital organ dysfunction [1].
Severe/complicated malaria case: A patient with symptomatic malaria parasitaemia with the presence of one or more of the following clinical features classifies the patient as suffering from severe malaria: impaired consciousness, generalised weakness, failure to feed, multiple convulsions (more than two episodes in 24 hours), deep breathing, circulatory collapse or shock, and clinical jaundice [1,2].

Population under surveillance and flow of information
People of all ages residing in high-endemic and hard-to-reach areas are included in the surveillance system. The flow of information within the community malaria surveillance system begins at the community level, where iCCM providers (Community Health Workers) register clients using the WAJA application, as well as paper-based registers and tally sheets. Data entered into the WAJA application is synchronised to the Unified Community System (UCS) dashboard, making it accessible at the district and national levels. iCCM providers are primarily responsible for data entry and can also generate monthly reports from the system. At the health facility level, paper reports submitted by iCCM providers are received monthly, validated, and archived for record-keeping and verification against electronic data. These reports are also used for commodity management, including monitoring the availability of diagnostic tools and medications.

The District Malaria Focal Person (DMFP) compiles aggregated malaria data from health facility reports using standardised reporting templates and submits them to the National Malaria Control Programme (NMCP). At the national level, data are uploaded and analysed using both the UCS dashboard and the District Health Information System 2 (DHIS2), although integration between the two systems remains partial. Feedback is then disseminated from the national level to regional, district, and community levels through meetings, training sessions, and workshops to support continuous improvement of the surveillance system

Purpose and objectives of the system
The broad system objective was to provide universal access to malaria services among all age groups. The specific objectives were to reduce malaria burden in high-burden councils through early detection and treatment; strengthen referral linkages between communities and nearby health facilities; and improve community health-seeking behaviour through health promotion and prevention.

Data extraction
Data is collected daily by iCCM providers from clients at the community level. Recorded in registers, UCS (WAJA App), tally sheets, and monthly summary forms. Summaries are sent to health facilities, then to DMFP and NMCP for aggregation and analysis.

Data storage and confidentiality
Data is stored in both paper-based and electronic systems (UCS, DHIS2). Access is limited to authorised personnel at health facilities and the NMCP. Patient information is handled confidentially and stored securely at source facilities.

Data analysis and presentation
Data collected through this surveillance is analyzed at the facility, council and national level. The presentation of data is done in the form of notes, tables, graphs, and reports, depending on the needs and the targeted audience.

Resources needed to operate the system
Funding sources: Global Fund (GF), President’s Malaria Initiative (PMI), and the Government of Tanzania (MOH/NMCP).
Personnel: Community Health Workers (CHWs/iCCM providers), clinicians, nurses, DMFPs, RHMTs, CHMTs, and NMCP coordinators.
Materials and equipment
• Medical supplies (MRDTs, ACTs, gloves, thermometers).
• Stationery, bicycles, boots, raincoats, mobile phones, and internet access.
• ICT systems: UCS dashboard, WAJA & KITUONI applications, DHIS2.
Data sharing: De-identified data may be shared upon request and after approval of a proposal and a signed data access agreement (via MOH/NMCP).

Study population
The study included key stakeholders engaged in the design, coordination, and implementation of the community malaria surveillance system. These included iCCM providers, facility-based healthcare workers, the district malaria focal person (DMFP), and the National Malaria Control Program (NMCP) iCCM coordinator.

Sampling and sample size
A purposive sampling technique was applied to select ten respondents who were directly involved in the design, implementation, supervision, and use of the surveillance system. These comprised one NMCP coordinator (national level), one District Malaria Focal Person (DMFP) (district level), two healthcare providers from affiliated health facilities, and six iCCM providers (community level), one provider per service delivery site.

The two health facilities were purposively selected as referral and reporting centres supporting iCCM implementation. The six service delivery sites (Kerezia, Burumbaga, Nampalahala, Ihako, Msingo, and Igulike) represent community-level implementation areas, with one iCCM provider selected from each site. Sampling continued until thematic saturation was achieved, where no new information emerged from additional interviews

System attributes evaluated
The performance of the community malaria surveillance system was evaluated using seven surveillance attributes: simplicity, acceptability, data quality, timeliness, representativeness, flexibility, and stability. For each attribute, specific indicators were developed and assessed using both quantitative and qualitative methods, in accordance with the Centers for Disease Control and Prevention (CDC) guidelines for evaluating public health surveillance systems. The CDC guidelines were selected due to their comprehensive framework and widespread application in evaluating public health surveillance systems, particularly in low- and middle-income settings.

Data collection techniques, tools, and data sources
Data were collected at the national, district, facility, and community levels. At the national level, an interview was conducted with the NMCP iCCM Coordinator to understand system design, objectives, funding mechanisms, and data flow. At the district level, the District Malaria Focal Person (DMFP) was interviewed to assess coordination, data management, and feedback processes. At the facility level, two healthcare providers were interviewed to evaluate operational attributes of the system, while at the community level, six iCCM providers were interviewed to understand how the system operates and how data collection and reporting are conducted. Mixed methods were applied, combining document review, electronic data extraction, and key informant interviews.

Semi-structured questionnaires were used at both national and subnational levels, and a data review checklist guided the assessment of timeliness, completeness, and accuracy of UCS and DHIS2 data. The main data sources included the Unified Community System (UCS) reports, DHIS2 malaria database, iCCM reference and user manuals, facility-based monthly summary forms, and interview responses from iCCM providers, facility staff, and district and national coordinators.

Data analysis
All extracted data were cleaned before analysis, and no records were excluded. Therefore, 100% of the extracted dataset was retained and analysed using Microsoft Excel 2021. A direct comparison of data was not conducted due to incomplete interoperability between UCS and DHIS2 during the evaluation period.

Quantitative indicators were scored using a 3-point scale adapted from studies that evaluated surveillance systems in Africa: less than 60% scored 1 (weak performance); 60–79% scored 2 (moderate performance); and equal to or greater than 80% scored 3 (good performance). For each attribute, mean scores were calculated to determine overall system performance. Results are presented in tables, graphs, and charts [10]
Usefulness: The usefulness of the system was assessed by reviewing how surveillance data were used to inform malaria control actions, resource allocation, and expansion of community services. Indicators assessed included the number of malaria cases detected and treated in the community, evidence of data use for planning and policy, and health education or awareness activities conducted by iCCM providers.
Representativeness: Representativeness was determined by reviewing the demographic and geographical coverage of reported malaria cases between December 2024 and February 2025. Indicators included the proportion of councils implementing iCCM among high-risk malaria councils with hard-to-reach areas and the demographic distribution of malaria cases by age group (under-five and above five years).
Timeliness: Timeliness was evaluated by comparing the number of reports submitted on time to those expected. Each iCCM provider is required to submit three reports (client summary, test summary, and dispensing summary) by the 30th of each month. The timeliness percentage was calculated as:

$$ \text{Timeliness (\%)} = \left( \frac{\text{Reports submitted on time}}{\text{Expected reports}} \right) \times 100 $$

Indicators assessed included the percentage of reports submitted on time and the timeliness of data upload to UCS.

Data quality: Data quality was assessed by reviewing the validity, accuracy, and completeness of key data fields in UCS and DHIS2. Validity was defined as the absence of data entry errors, accuracy as consistency between UCS and facility-based reports, and completeness as the proportion of filled data fields relative to expected entries. The assessment examined the percentage of valid records, the proportion of missing or incomplete records, and consistency between data sources.
Simplicity: Simplicity was evaluated by assessing the ease of data collection, entry, and reporting using the WAJA App and manual registers. Indicators included the proportion of trained iCCM providers, the average time taken to assess, diagnose, and report a client (less than 20 minutes), and the providers’ perception of system usability.
Flexibility: Flexibility was assessed by examining the system’s ability to adapt to changes and integrate additional services. The assessment considered integration of pneumonia and diarrhea management under iCCM and the system’s functionality in both online and offline modes.
Acceptability: Acceptability was measured through the willingness of providers and facilities to use the system and comply with reporting requirements. Indicators included the percentage of providers submitting complete reports monthly, provider satisfaction, community acceptance, and the level of training provided to participants, along with their perceived ease of use of the system.
Stability: Stability was assessed using both primary data from sampled sites and secondary data from routine program reports covering all councils implementing the community malaria surveillance system. The assessment focused on operational and financial sustainability of the system. Indicators included functionality of the Unified Community System (UCS) in both online and offline modes, availability of essential commodities such as rapid diagnostic tests (RDTs) and artemisinin-based combination therapies (ACTs), funding sources and continuity of support from partners such as the Global Fund and the President’s Malaria Initiative (PMI), and the frequency of service interruptions.
Sensitivity and predictive value positive (PVP): Sensitivity and predictive value positive (PVP) were intended to assess the accuracy of the system in detecting malaria cases. However, due to the short evaluation period and absence of a comparison dataset for undetected or false-positive cases, these indicators were not calculated.

Ethical considerations
This evaluation utilised routine surveillance data and did not involve experimental procedures. Therefore, formal ethical clearance was not required. Permission to conduct the evaluation was obtained from the Ministry of Health through the National Malaria Control Programme (NMCP). The Geita Regional Secretariat granted additional approvals, as did the Bukombe District Council CHMT and the respective health facilities. Verbal informed consent was obtained from all interview participants, and no personal identifiers were collected to ensure confidentiality.