Mapping Urinary Schistosomiasis Risk in Ogun State, Nigeria
Author Information
Author(s): Ekpo Uwem F, Mafiana Chiedu F, Adeofun Clement O, Solarin Adewale R, Idowu Adewumi B
Primary Institution: University of Agriculture, Abeokuta, Nigeria
Hypothesis
Can geographical information systems and environmental data predict the risk of urinary schistosomiasis in Ogun State, Nigeria?
Conclusion
The developed risk maps provide valuable information for health officials to target areas for intervention and resource allocation.
Supporting Evidence
- The study found that 98.99% of school-aged children are living in areas suitable for urinary schistosomiasis transmission.
- Logistic regression identified Land Surface Temperature as a significant predictor of urinary schistosomiasis presence.
- The model achieved an overall accuracy of 86.7% in predicting high and low-risk schools.
Takeaway
This study created maps to show where urinary schistosomiasis is likely to occur in Ogun State, helping health workers know where to focus their efforts.
Methodology
The study used logistic regression analysis on infection data from school children and environmental data to create predictive risk maps.
Potential Biases
Potential bias due to reliance on self-reported symptoms and the lack of validation for the models due to funding constraints.
Limitations
The study relied on self-reported data for infection prevalence, which may not be entirely accurate.
Participant Demographics
School-aged children (5–14 years) from 1,092 schools in Ogun State.
Statistical Information
P-Value
0.013
Confidence Interval
95% CI for Exp (B)
Statistical Significance
p<0.05
Digital Object Identifier (DOI)
Want to read the original?
Access the complete publication on the publisher's website