INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016
Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
Lassa fever, a hemorrhagic illness transmitted through the Mastomys natalensis rodent, continues to pose a significant public health threat in West Africa. In Ondo State, Nigeria, it remains a dominant infectious disease, accounting for a concerning 35% of reported cases. Predicting outbreaks and implementing targeted interventions is crucial for curbing its spread. This research developed a robust model for predicting Lassa fever cases in Ondo State by employing a Bayesian linear regression approach. The Bayesian Ridge Regression model was used to predict Lassa fever incidence. The model's performance was evaluated using two key metrics: R-squared and Mean Squared Error (MSE). The model achieved a 99% R-squared value which indicated a near-perfect fit between the predicted and actual Lassa fever cases. Furthermore, the relatively low MSE score confirmed the model's accuracy in capturing the variability in outbreak patterns. These compelling results showcase the effectiveness of the Bayesian Ridge Regression model in predicting Lassa fever incidence within Ondo State.
Keywords:
Lassa Fever, Bayesian Linear Model, Bayesian Ridge, Prediction
Cite Article:
"A Bayesian Linear Regression Model For Predicting Lassa Fever in Nigeria: A Case Study of Ondo State", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 4, page no.d289-d298, April-2024, Available :http://www.ijnrd.org/papers/IJNRD2404336.pdf
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ISSN:
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
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