Prevalence of Haemoglobinopathy and Malaria Diseases in the Populationof Old Aguata Division, Anambra State, Nigeria
Bibliographic record
Abstract
The prevalence of haemoglobinophy and malaria were determined in 12812 inhabitants (5227 males and 7585 females) of the twenty-one (21) autonomous communities of Old Aguata Division, Anambra State, Nigeria. The intention was not only to reveal their most current incidences but also to adduce the most probable reason(s) for the widespread myths peddled about sickle cell disease (SCD) in the area. Results revealed high incidences of sickle cell anaemia (3.54%) and sickle gene trait (26.94%), low incidences of sickle haemoglobin C (0.02%) and haemoglobin CC (0.01%) diseases and an average high prevalence of malaria (47.95%). Most of the malaria attack was caused by Plasmodium falciparum (P.f) infection. The possession of over 20% of persisting concentration of foetal haemoglobin (HbF) by 65.86% (299/454) of identified sickle cell anaemia (SCA) subjects and the striking limited knowledge of SCD and its method of control by the inhabitants of the communities are inconsonance with the high incidence of SCA in the population. The low percentage HbC gene frequency (0.07%) computed from the data could explain the rarity of HbSC and HbCC diseases in the population. Their probable frequencies of occurrence are of the order of one in every 20,000 and 600,000 persons respectively while that of SCA is of the order of one in every 200 persons. Further results showed that dominant homozygotes (HbAA) were more susceptible to plasmodial parasite infection than sickle heterozygotes (HbAS) while recessive homnozygotes (HbSS) were most vulnerable to malaria than the other two members of genotypic groups. Furthermore, random administration of sub-standard and under-dose of anti-malaria drugs by patent medicine dealers operating in the area is suspected to be the main factor responsible for the emergence of the observed anti-malaria drug-resistant strains of P.f which is not in consonance with high prevalence of malaria in this area.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".