A qualitative review of implementer perceptions of the national community-level malaria surveillance system in Southern Province, Zambia
Bibliographic record
Abstract
BACKGROUND: Parts of Zambia with very low malaria parasite prevalence and high coverage of vector control interventions are targeted for malaria elimination through a series of interventions including reactive case detection (RCD) at community level. When a symptomatic individual presenting to a community health worker (CHW) or government clinic is diagnostically confirmed as an incident malaria case an RCD response is initiated. This consists of a CHW screening the community around the incident case with rapid diagnostic tests (RDT) and treating positive cases with artemether-lumefantrine (AL, Coartem™) in accordance with national policy. Since its inception in 2011, Zambia's RCD programme has relied on anecdotal feedback from staff to identify issues and possible solutions. In 2014, a systematic qualitative programme review was conducted to determine perceptions around malaria rates, incentives, operational challenges and solutions according to CHWs, their supervisors and district-level managers. METHODS: A criterion-based sampling framework based on training regime and performance level was used to select nine rural health posts in four districts of Southern Province. Twenty-two staff interviews were completed to produce English or bilingual (CiTonga or Silozi + English) verbatim transcripts, which were then analysed using thematic framework analysis. RESULTS: CHWs, their supervisors and district-level managers strongly credited the system with improving access to malaria services and significantly reducing the number of cases in their area. The main implementation barriers included access (e.g., lack of rain gear, broken bicycles), insufficient number of CHWs for programme coverage, communication (e.g. difficulties maintaining cell phones and "talk time" to transmit data by phone), and inconsistent supply chain (e.g., inadequate numbers of RDT kits and anti-malarial drugs to test and treat uncomplicated cases). CONCLUSIONS: This review highlights the importance of a community surveillance system like RCD in shaping Zambia's malaria elimination campaign by identifying community-based infections that might otherwise remain undetected. At this stage the system must ensure it can meet growing public demand by providing CHWs the tools and materials they need to consistently carry out their work and expand programme reach to more isolated communities. Results from this review will be used to plan programme scale-up into other parts of Zambia.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".