Epidemiological Studies Of Malaria In Gboko Metropolis, Gboko Local Government Area Of Benue State, Nigeria
Bibliographic record
Abstract
Abstract We carried out an epidemiological study of malaria in Gboko metropolis in Gboko Local Government Area of Benue State, North - Central Nigeria to determine the malaria prevalence, risk factors and perception to malaria control among patients attending the hospital clinics between April and June, 2021. We used Rapid Diagnostic Test (RDT), thin blood and thick blood film microscopy to sample the blood of 415 patients to determine specie, prevalence and intensity of malaria parasites. Also, structured questionnaire was administered to 400 individuals to obtain information on malaria management practices of the people. Chi-square test P<0.05 was used to check for relationships between prevalence of malaria and other parameters in the study. The prevalence rate was found to be (55.7%) 231/415 and all (100%) were infections of Plasmodium falciparum . There was significant difference (p<0.05) in the prevalence by age with the age groups 20-29 years having the highest prevalence of 68.9% (51/74). General Hospital Gboko recorded the highest prevalence of 74.3% (92/124) while Royal Hospital Gboko recorded the lowest prevalence of 31.6% (12/38) with a significant difference. The intensity of malaria infection showed that 45.9% (106/231) had moderate infection with no significant difference. In the administration of questionnaire, the respondents in Gboko demonstrated a good knowledge of malaria, 93.2% (373/400) opined that they have heard about malaria before. Respondents who do not sleep under LLINs recorded that 32.6% (30/92) do not have the mosquito net recorded, 17.4% (16/92) had no money to buy mosquito net while 10.9% (10/92) averred that it’s not comfortable sleeping under the net. Malaria public enlightenment efforts should be intensified to make malaria elimination not just possible but also achievable in Gboko Metropolis, Benue State.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.015 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".