Municipality-level spatial clustering and socio-environmental determinants of tuberculosis in Nepal, 2019–2024
BMC Infectious Diseases·
- DOI
- 10.1186/s12879-026-14265-8
- PMID
- —
- PMCID
- —
- OpenAlex
- —
- Study type
- Journal article
- Publisher
- Springer Science and Business Media LLC
- Article type
- journal-article
- Integrity
- current
Why this research matters now
The pronounced regional concentration of reported cases implies that precision resource deployment and area-specific prevention initiatives may better support national elimination objectives.
Structured evidence summary
Research question
This investigation sought to characterize the geographic distribution of tuberculosis notifications across Nepalese municipalities and determine how these patterns correlate with local demographic, residential, and environmental variables.
Study design
The research employed an observational ecological framework utilizing five years of aggregated national case records to perform spatial autocorrelation testing and multivariable spatial regression modeling.
Population and setting
The analysis covered every municipal jurisdiction within Nepal, drawing on consolidated notification data collected between fiscal years 2019/20 and 2023/24.
Main findings
Case counts demonstrated a steady upward trajectory alongside statistically confirmed geographic clustering throughout the observation window. Regression outputs indicated that elevated notification levels aligned with higher population concentrations, specific energy consumption metrics, and warmer nighttime surface temperatures, whereas certain traditional construction materials and fuels displayed inverse correlations that authors attribute to potential healthcare access disparities.
Public-health relevance
The pronounced regional concentration of reported cases implies that precision resource deployment and area-specific prevention initiatives may better support national elimination objectives.
Important limitations
Reliance on aggregated municipal reporting precludes individual-level clinical assessment, and observed protective associations for particular housing types likely represent diagnostic access limitations rather than genuine epidemiological shielding.
GIDS interpretation
The documented municipal aggregation patterns establish baseline contextual information regarding regional disease distribution but do not suggest an anomalous trend or require immediate operational escalation.
Related GIDS surveillance
Literature context does not validate, explain, or change a surveillance signal. Exact and contextual relationships are shown separately.
Evidence relationships
This article has 9 auditable classifier relationships to diseases, places, topics, and study design.