Mapping local hot spots with routine tuberculosis data: A pragmatic approach to identify spatial variability.

Area of Science:

• Epidemiology
• Spatial Analysis
• Public Health

Background:

• Tuberculosis (TB) remains a significant global health challenge.
• Understanding the geographic distribution of TB cases is crucial for effective control strategies.

Purpose of the Study:

• To identify local
• hot spots
• of reported tuberculosis cases using routinely collected data, geographic information, and census data.

Main Methods:

• Utilized residential locations of 1,295 TB cases (2013-2018) from eight public health facilities in Lima, Peru.
• Linked case data with census data to calculate neighborhood-level annual case rates.
• Employed heat maps and Local Indicators of Spatial Autocorrelation (Moran's I) to identify spatial clusters and outliers.

Main Results:

• Identified an average annual rate of 124.2 reported TB cases per 100,000 population across 74 neighborhoods.
• Observed significant geographic heterogeneity, with case rates ranging from 0 to 800 per 100,000.
• Found higher case rates in individuals aged 15-44 and in men, with overlapping hot and cold spots across age- and gender-specific maps.

Conclusions:

• Significant geographic variation in reported TB case rates exists within the study area.
• Identification of spatial distribution and local hot spots can inform targeted TB interventions.
• Spatial analysis provides a practical tool for public health coalitions to focus resources on high-risk areas.