Malaria micro-stratification using routine surveillance data in Western Kenya.

Area of Science:

• Epidemiology
• Spatial Statistics
• Public Health

Background:

• Increasing need for high-resolution malaria risk data for sub-national strategic planning.
• Routine health data can be leveraged to map malaria test positivity rate (TPR) heterogeneities.

Purpose of the Study:

• To use spatial-statistical techniques to depict sub-national variations in malaria TPR in Western Kenya.
• To adjust for population distribution and spatial structures to reveal fine-scale malaria risk.

Main Methods:

• Utilized routine health facility data (n=1804) from 2018-2019 across 8 counties in Western Kenya.
• Employed statistical model-based approaches to quantify TPR heterogeneities and uncertainty at fine spatial resolution.
• Adjusted for missing data, population distribution, spatial structure, month, and health facility type.

Main Results:

• Public health facilities reported more consistently than private ones.
• Significant sub-county level variations in population-weighted TPR were observed, with the highest rates in the north of the lake-endemic region.
• Identified areas with low TPR, often associated with indoor residual spraying interventions.

Conclusions:

• Routine health data, when adjusted for population and spatial factors, effectively highlights small-scale malaria risk variations.
• Findings underscore the importance of micro-stratification for malaria control planning.
• Future research should link TPR heterogeneities with community prevalence for improved malaria control tailoring.