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Related Experiment Video

Updated: Mar 27, 2026

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Modeling diarrhea in children under five in Somaliland: A machine learning analysis using SLDHS 2020 data.

Yahye Hassan Muse1, Mukhtar Abdi Hassan1, Abdisalam Hassan Muse1

  • 1Faculty of Science and Humanities, School of Postgraduate Studies and Research (SPGSR), Amoud University, Borama, Somalia.

Plos One
|March 25, 2026
PubMed
Summary
This summary is machine-generated.

Diarrhea affects 7.2% of children under five in Somaliland, with nomadic and low-income households most impacted. Improving water and sanitation access is crucial for public health strategies.

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Area of Science:

  • Public Health
  • Epidemiology
  • Pediatrics

Background:

  • Diarrhea is a major cause of illness and death in children under five, especially in low- and middle-income countries.
  • This study examines diarrhea prevalence and its determinants in Somaliland using the 2020 Somaliland Health and Demographic Survey (SLDHS).

Purpose of the Study:

  • To investigate the prevalence and identify key determinants of childhood diarrhea in Somaliland.
  • To inform targeted public health interventions for diarrhea prevention and control.

Main Methods:

  • Cross-sectional study analyzing data from 1,112 women and their children under five.
  • Descriptive statistics, binary logistic regression, and supervised machine learning models (Logistic Regression, Probit, Random Forest, Decision Tree, SVM) were used.
  • Variables included socioeconomic, demographic, and environmental factors.

Main Results:

  • Overall diarrhea prevalence was 7.2% with significant regional variations.
  • Nomadic households showed higher incidence (8.62%) compared to rural and urban households.
  • Region, household wealth, and sanitation access were significant predictors; maternal education was not.

Conclusions:

  • Region-specific public health strategies are vital, focusing on water and sanitation access for nomadic and low-income populations.
  • Machine learning models showed high overall accuracy but require refinement for predicting positive diarrhea cases.
  • Enhancing infrastructure and sanitation in underserved communities is a priority to reduce childhood diarrhea.