Perennial transmission of malaria in the low altitude areas of Baringo County, Kenya
Bibliographic record
Abstract
BACKGROUND: Malaria causes the greatest public health burden in sub-Saharan Africa where high mortality occurs mainly in children under 5 years of age. Traditionally, malaria has been reported mainly in the lowlands endemic regions of western Kenya, while the highlands of the Rift Valley have been relatively free except for the sporadic epidemics in some areas. Baringo County is located in the Kenyan highlands. The county generally experiences seasonal transmission of malaria. A few hotspots which experience continuous malaria transmission in the county do however exist. The objective of this study was to assess malaria infection status and identify areas with continuous transmissions with a view to mapping out probable transmission hot spots useful in mounting focused interventions within the county. METHODS: Systematic sampling was employed to identify 1668 primary school pupils from fifteen primary schools located in 4 ecological zones (lowland, midland, highland and riverine) of three sub-counties of Baringo. Finger prick blood sampling was done every 4 months (during the dry season in February/March, after the long rains in June/July and short rains in November 2015). Malaria occurrence was tested using rapid diagnostic test kit (CareStart HRP-2 Pf). Microscopic examination was done on all RDT positive and 10% of negative cases. RESULTS: A total of 268 (16.1%), out of 1668 pupils tested positive for Plasmodium falciparum by RDT; 78% had a single episode, 16.8% had 2 episodes, 4.9% had 3 episodes and 0.4% had 4 episodes. The riverine zone had the highest malaria cases (23.2%) followed by lowlands (0.9%). No malaria cases were detected in the midland zone while highland zone recorded only few cases during the third follow up. Up to 10.7% of malaria cases were reported in the dry season, 2.9% during the long rains and 5.7% in short rains season. CONCLUSIONS: Malaria infection was prevalent in Baringo County and was mainly restricted to the riverine zone where transmission is continuous throughout the year. High malaria prevalence occurred in the dry season compared to the wet season. Even though malaria transmission is relatively low compared to endemic regions of Kenya, there is a need for continued monitoring of transmission dynamics under changing climatic conditions as well as establishing expanded malaria control strategies especially within the riverine zone which would include an integrated mosquito control and chemotherapy for infected individuals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.001 |
| 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".