Malaria in Uganda: school-based rapid diagnostic testing and treatment
Bibliographic record
Abstract
Malaria is the main reason a school-aged child in sub-Saharan Africa will die and the principal reason why a child will be absent from school.1–3 The duration of malaria-related absence, frequency of absence due to repeated infection, residual malaise from suboptimal treatment or permanent neurological complications of falciparum malaria can all compromise a child’s potential to learn.2,4,5 The burden of malaria is greatest among children in low-resource settings and rural areas. Diagnosis and treatment are not straightforward as symptoms are not specific, diagnostic blood tests are often not readily available and lack of knowledge and limited access to care contribute to morbidity and mortality.6 The World Health Organization (WHO) advocates early, accurate diagnosis and prompt, effective treatment, and recommends combined use of Rapid Diagnostic Test (RDT) kits and administration of Artemisinin Combination Therapy (ACT).7 However, the social engagement required to make RDT/ACT accessible to rural populations in developing countries is largely missing.8 RDTs require a drop of blood;9,10 if malaria antigens are present they bind to the dye-labelled antibody in the kit, forming a visible complex in the results window. Their sensitivity and specificity mean they can replace conventional testing for malaria.11,12 ACTs are the best anti-malarial drugs available nowadays; WHO recommends them as first-line therapy worldwide for P. falciparum malaria.13–15 ACTs combine artemisinin, which kills the majority of parasites within a few hours of treatment starting, with a partner drug of a different class and longer half-life, which eliminates residual parasites16. We implemented a school-based intervention in four low-resource communities in Uganda where teachers were trained to conduct RDT and administer ACT among children falling sick at school, and evaluated the effect on absenteeism as a surrogate for morbidity due to malaria.17 Sick children are usually just sent home for parents to manage. Year 1 involved baseline data collection, community enquiry on malaria management, and teacher training; in year 2, all sick children had a teacher-administered RDT and prompt ACT treatment if they tested positive. Malaria is the principal reason for which a child misses school in Africa. In low-resource communities, knowledge on the mechanisms of infection and awareness of effective preventive methods are often lacking;17 < 50% of Ugandan households own a mosquito net and 77% of children do not sleep under insecticide treated nets. 18 net use is a rarity due to limited knowledge of the mechanisms of infection and methods for effective prevention. All schools display daily counts of numbers present and absent. We built on this data collection process for the study. Rapid diagnostic test (RDT) kits in the laboratory at the training facility. A training workshop for teachers on using RDT kits, administering ACT and data collection practices. Pre-intervention: pupils identified as sick by class teachers waiting in the school office before being sent home. During intervention, 67.5% of pupils identified as sick, using the same criteria, tested positive for malaria. 17. A teacher obtaining the finger prick blood sample to conduct an RDT at a participating school. Immediate treatment of those positive reduced duration of absence from approximately 1 week to < 1 day. 17. Project data collection sheet developed to capture each school's daily count of pupils present and absent. Pictogram used for community education regarding conduct of the RDT for malaria. Community teaching session at participating school. Pre-intervention < 1:5 children knew that malaria is mosquito borne, can be prevented and responds to rapid diagnosis and prompt treatment ; post-intervention essentially 100% had this knowledge.17 Children respond to questions with a show of hands and stand up to give answers or ask questions. RDT and ACT are widely employed, but their use by trained teachers in a school-based initiative to address the health-related consequences of malaria on absenteeism has not previously been implemented. Our model represents a community-based approach applicable globally where morbidity from malaria is high. The people (identifiable) photographed have given their consent for their pictures to be used in the dissemination and publication of this research. This work was supported by a grant from the Hillman Medical Education Fund. Conflict of interest: None. This paper is dedicated to the memory of Faith Gagnon who helped in the concept of this school-based care model for children with malaria during the Stellenbosch Institute for Advanced Study (STIAS) international colloquium on WHO Heath Promoting Schools in 2011. Faith was a gifted photographer and contributed throughout her life to medical research that improved the lives of children. We acknowledge the collaboration of the teachers and pupils involved in this health promotion project, and the support of the parents, elders and village health teams in the communities where the participating schools were located. The authors collaborated as a team through the Health and Development Agency (HEADA) Uganda to establish, coordinate and evaluate this initiative. HEADA is a non-governmental agency established to implement comprehensive health education, training and support programmes in Ugandan schools and rural communities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".