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Record W4381328587 · doi:10.21203/rs.3.rs-3072905/v1

LONG-LASTING INSECTICIDE NETS OWNERSHIP AND MALARIA MORBIDITY IN KRACHI EAST MUNICIPALITY, GHANA

2023· preprint· en· W4381328587 on OpenAlexaff
Israel Wuresah, Siman Elmi, Martin Adjuik

Bibliographic record

VenueResearch Square · 2023
Typepreprint
Languageen
FieldMedicine
TopicMalaria Research and Control
Canadian institutionsYork University
Fundersnot available
KeywordsMalariaIndoor residual sprayingEnvironmental healthCluster samplingBed netsSocioeconomicsGeographyCluster (spacecraft)OutreachMedicineDemographyEconomic growthPopulationPlasmodium falciparum

Abstract

fetched live from OpenAlex

Abstract Background: Malaria-related morbidity and mortality are issues of great concern to public health globally though, a higher proportion of cases reside within Sub-Saharan Africa. The situation in Ghana though not new, is very disturbing, as millions of people especially children and pregnant women suffer severely from malaria. Seasonal chemoprevention and indoor residual spraying are among many measures deployed in the northern parts of Ghana with nationwide outreach and point distribution of LLINs across the country but reports from OPDs indicate millions of malaria cases annually. Objective: To identify the levels of ownership and usage of the treated bed nets, and describe the relationship between ownership of LLINs and malaria morbidity. Methods: The 30-cluster sampling method was deployed. Using both a modified WHO EPI survey method for more rural areas and a random walk sampling for more urban areas, each community had a listed starting point where the use of a spun pen determined the direction to conduct the surveys within the specified cluster. Selected households’ heads/representatives (any adult aged 18 years and above, in a household where the head is absent) participated voluntarily. STATA version 16.0 was used to run the statistical analysis and the results were presented in tables and figures. Results: Findings revealed high levels of ownership of LLINs (73.4%) but moderately low usage levels (49.5%). Some other uses of LLINs (22.9%) aside from sleeping under them were identified. Malaria morbidity (59.6%) was also determined. Multivariate analysis results revealed statistically significant association between some socio-demographic characteristics and LLINs ownership including female sex (AOR = 2.1 (95% CI: 1.15, 3.87) p=0.016), being married (AOR = 3.4 (95% CI: 1.76, 6.74) p<0.001), cohabiting (AOR = 6.1 (95% CI: 2.15, 17.02) p=0.001) and being separated or divorced (AOR = 9.4 (95% CI: 1.09, 81.27) p=0.041). A positive correlation was identified between ownership of LLINs and their usage, however both ownership and usage had no influence on malaria morbidity. Conclusion: The study highlights a high ownership rate but lower usage of Long-Lasting Insecticidal Nets (LLINs), indicating the need to address barriers to consistent utilization. There is a significant burden of malaria within the surveyed population, emphasizing the importance of effective malaria control measures. Further research is required to validate the impact of LLINs ownership and sociodemographic characteristics on malaria morbidity.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.212
GPT teacher head0.431
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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