Related Experiment Video
Updated: Feb 1, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Using mixed effects logistic regression models for complex survey data on malaria rapid diagnostic test results
Chigozie Louisa J Ugwu1, Temesgen T Zewotir2
1School of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, Westville Campus, Durban, South Africa. 217075063@stu.ukzn.ac.za.
Malaria in Nigeria is a major public health concern. Key risk factors include child
Area of Science:
- Public Health
- Epidemiology
- Biostatistics
Background:
- Malaria remains a critical public health issue in Nigeria, which bore the highest burden in Africa in 2016.
- Nigeria accounted for 80% of global malaria cases among 15 sub-Saharan African countries.
- Addressing malaria is crucial for achieving the Sustainable Development Goals 2030 Agenda.
Purpose of the Study:
- To identify socio-economic, demographic, and geographic risk factors influencing malaria transmission in Nigeria.
- To utilize statistical models for analyzing malaria rapid diagnostic test survey data.
- To inform the redesign of intervention strategies for malaria elimination.
Main Methods:
- Employed generalized linear mixed models to account for complex sample survey design.
- Utilized data from the 2015 Nigeria Malaria Indicator Survey.
- Focused on children aged 6 to 59 months.
Main Results:
- Significant cluster effects indicate heterogeneity in malaria transmission.
- Child's age, presence of anemia, and residing in rural areas increase malaria risk.
- Maternal education, poverty, household size, sanitation, electricity access, roofing material, and region (North, South-West) are significant risk factors.
Conclusions:
- Socio-economic development and improved quality of life are essential for malaria elimination in Nigeria.
- Malaria risk is strongly associated with poverty, under-development, and lower maternal education levels.
More Related Videos
04:35Development of an Individual-Tree Basal Area Increment Model using a Linear Mixed-Effects Approach
Published on: July 3, 2020
06:22Machine Learning-Based Cough Tone Classification: Diagnostic Exploration of Chronic Obstructive Pulmonary Disease and Respiratory Tract Infections
Published on: September 19, 2025
Related Concept Videos
Data Collection by Survey
Surveys
Regression Toward the Mean
Introduction to Surveying, Plane Surveying and Geodetic Surveys
Multiple Regression
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
Correlation and Regression