Geospatial Mapping of Pediatric Febrile Illness in Uganda to Inform Precision Public Health Interventions - Report - MDSpire

Geospatial Mapping of Pediatric Febrile Illness in Uganda to Inform Precision Public Health Interventions

  • By

  • Paddy Ssentongo

  • Misaki Sasanami

  • Camille Moeckel

  • Claudio Fronterrè

  • January 15, 2026

  • 0 min

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Geospatial Analysis of Febrile Illness in Ugandan Children

Overview

This study analyzed data from the 2016 Uganda Demographic and Health Survey to map the prevalence of febrile illness among children under 5 years old. Using geostatistical modeling, the research identified significant spatial and temporal variation in fever prevalence, influenced by environmental, nutritional, and sociodemographic factors.

Background

Febrile illness remains a major cause of morbidity and mortality among children in low- and middle-income countries, accounting for over one-third of childhood deaths globally. Infectious diseases are the primary drivers of pediatric fever, with environmental and climatic factors influencing vector- and water-borne infections, while respiratory and urinary infections show seasonal patterns. Understanding the spatial distribution and environmental determinants of febrile illness is critical for designing targeted public health interventions. Prior to this study, the spatial epidemiology of pediatric fever in Uganda had not been comprehensively characterized.

Data Highlights

ParameterValue
Number of children surveyed14,195
Number of clusters685
Reported fever cases (past 2 weeks)4,990 (35.1%)
Survey periodJune 15 to December 18, 2016
Covariates improving model performancePoverty, anemia, rainfall (2-month lag), enhanced vegetation index (1-month lag), seasonality

Key Findings

  • Febrile illness prevalence among children under 5 was 35.1% in the 2 weeks preceding the survey.
  • Fever prevalence showed significant geographic heterogeneity, with highest rates in eastern and northeastern Uganda.
  • Temporal variation was observed, with increased fever cases following the rainy season.
  • Environmental factors such as rainfall and vegetation index, nutritional status including anemia, and poverty were significantly associated with fever prevalence.
  • Geostatistical binomial modeling effectively predicted spatial and temporal patterns of pediatric fever.

Clinical Implications

These findings highlight the importance of incorporating environmental and nutritional factors into public health strategies addressing pediatric febrile illness in Uganda. Targeted interventions focusing on high-prevalence regions and periods following the rainy season may optimize resource allocation. Additionally, addressing anemia and poverty could contribute to reducing fever burden among children.

Conclusion

The study demonstrates pronounced spatial and temporal heterogeneity in pediatric febrile illness in Uganda driven by environmental and nutritional factors. These insights support precision public health approaches to mitigate childhood fever through region-specific interventions.

References

  1. Uganda Demographic and Health Survey 2016 -- National Population Data
  2. World Health Organization -- Standardized DHS Methodology
  3. Systematic Review on Fever Detection Sensitivity and Specificity

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