Urban and Rural Tuberculosis Prevalence Estimates for 26 Countries (2000-2024)

Estimated numbers and percentages of prevalent TB cases across urban and rural areas in 26 study countries from 2000 to 2024. Seyed Alireza Mortazavi created this dataset using a Bayesian multivariate regression model to estimate incidence and case detection ratios. The data was last updated in April 2026.

Use Cases

• Analyze trends in `urban_prevalence` and `rural_prevalence` columns over the 24-year `year` range.
• Compare the `percentage_of_prevalent_TB` between urban and rural classifications across the 26 `country` entries.
• Validate Bayesian spatiotemporal disease models using the provided `estimated_numbers` of prevalent cases.
• Assess the impact of population distribution assumptions on modelled `TB_prevalence` estimates.

Strengths

• 24 years of temporal coverage from 2000 to 2024.
• Data includes estimates for both urban and rural areas across 26 countries.
• Estimates derived from a specified Bayesian multivariate regression model.

Limitations

• Dataset is very small at 81.1 KB, indicating limited detail or aggregation.
• Contains modelled estimates, not directly observed case counts, introducing uncertainty.
• Specific row count and column details are unknown, limiting assessment of granularity.

Provenance

Source

Seyed Alireza Mortazavi via figshare.

Collection Method

Estimated from a Bayesian multivariate regression model combining incidence, case detection ratio, and assumptions on duration and population distribution.

Time Range

2000 to 2024.

Freshness

Last updated in April 2026, providing recent model estimates.

Geography

26 study countries (specific countries not listed).