Niger vs Tanzania, United Republic of: Tuberculosis prevalence rate, low uncertainty bound

Niger
81 per 1000,000 population, WHO
in 2011
Tanzania, United Republic of
93 per 1000,000 population, WHO
in 2011
Niger rank
36th
Tanzania, United Republic of rank
34th

Tuberculosis prevalence rate, low uncertainty bound over time

  • Niger
  • Tanzania, United Republic of
100200300400199020002011

How they compare

Tanzania, United Republic of currently reports 93 per 1000,000 population, WHO against 81 per 1000,000 population, WHO in Niger, a difference of 12 per 1000,000 population, WHO.

That makes Tanzania, United Republic of's figure about 1.1 times Niger's.

The two have swapped places 1 time across 22 shared years of data; in 1990 it was Niger ahead.

Niger ranks 36th and Tanzania, United Republic of ranks 34th of 53 countries.

Across the 3 decades both report, Niger averaged higher in 2 and Tanzania, United Republic of in 1.

Head to head by decade

Decade Niger Tanzania, United Republic of Difference Ahead
1990s 273.5 per 1000,000 population, WHO 135.3 per 1000,000 population, WHO 138.2 per 1000,000 population, WHO Niger
2000s 129.6 per 1000,000 population, WHO 114.1 per 1000,000 population, WHO 15.5 per 1000,000 population, WHO Niger
2010s 83.5 per 1000,000 population, WHO 95.5 per 1000,000 population, WHO 12 per 1000,000 population, WHO Tanzania, United Republic of

Averages of every year both report within each decade.

Frequently asked questions

Which has higher tuberculosis prevalence rate, low uncertainty bound, Niger or Tanzania, United Republic of?
Tanzania, United Republic of, at 93 per 1000,000 population, WHO against 81 per 1000,000 population, WHO in Niger as of 2011.
What is the difference in tuberculosis prevalence rate, low uncertainty bound between Niger and Tanzania, United Republic of?
12 per 1000,000 population, WHO, with Tanzania, United Republic of ahead.
How many years of comparable data are there for Niger and Tanzania, United Republic of?
22 years are reported by both, from 1990 to 2011.
How do Niger and Tanzania, United Republic of rank globally for tuberculosis prevalence rate, low uncertainty bound?
Niger ranks 36th and Tanzania, United Republic of ranks 34th of 53 countries.
Where does this data come from?
World Health Organization, Global Tuberculosis Control Report, published as Tuberculosis prevalence rate, low uncertainty bound (per 1000,000 population, WHO). Statizoid refreshes it automatically from the source and publishes the full history for both places.

Individual pages

Share, cite or embed this page

Cite this page

Niger vs Tanzania, United Republic of: Tuberculosis prevalence rate, low uncertainty bound. Statizoid, drawing on World Health Organization, Global Tuberculosis Control Report. Retrieved 07 September 2026, from https://health.statizoid.com/compare/tuberculosis-prevalence-rate-low-uncertainty-bound-per-1000-000-population-who/niger/tanzania/

Embed or link this data

Paste this into a page to link back to these figures. The data itself is free to reuse under CC BY 4.0 (World Bank Open Data); please keep the attribution.

<a href="https://health.statizoid.com/compare/tuberculosis-prevalence-rate-low-uncertainty-bound-per-1000-000-population-who/niger/tanzania/">Niger vs Tanzania, United Republic of: Tuberculosis prevalence rate, low uncertainty bound</a> — Statizoid

About this data

Indicator
Tuberculosis prevalence rate, low uncertainty bound (per 1000,000 population, WHO)
Unit
per 1000,000 population, WHO
Source
World Health Organization, Global Tuberculosis Control Report
Licence
CC BY 4.0 (World Bank Open Data)
Coverage
53 places, 1,166 data points, 1990–2011
Last refreshed

The number of cases of tuberculosis (all forms) in a population at a given point in time (the middle of the calendar year), expressed as the rate per 100 000 population. It is sometimes referred to as "point prevalence" low uncertainty bound. Estimates include cases of TB in people with HIV. Published values are rounded to three significant figures. Uncertainty bounds are provided in addition to best estimates.