Tanzania vs Zimbabwe: AIDS deaths in adults and children (high estimate)
Tanzania
110,000 high estimate
in 2009
Zimbabwe
97,000 high estimate
in 2009
Tanzania rank
3rd
Zimbabwe rank
5th
AIDS deaths in adults and children (high estimate) over time
- Tanzania
- Zimbabwe
How they compare
Tanzania currently reports 110,000 high estimate against 97,000 high estimate in Zimbabwe, a difference of 13,000 high estimate.
That makes Tanzania's figure about 1.1 times Zimbabwe's.
The two have swapped places 2 times across 20 shared years of data; in 1990 it was Tanzania ahead.
Tanzania ranks 3rd and Zimbabwe ranks 5th of 48 countries.
Zimbabwe has averaged higher in every one of the 2 decades both report.
Head to head by decade
| Decade | Tanzania | Zimbabwe | Difference | Ahead |
|---|---|---|---|---|
| 1990s | 75,200 high estimate | 77,500 high estimate | 2,300 high estimate | Zimbabwe |
| 2000s | 129,000 high estimate | 140,700 high estimate | 11,700 high estimate | Zimbabwe |
Averages of every year both report within each decade.
Frequently asked questions
- Which has higher aids deaths in adults and children, Tanzania or Zimbabwe?
- Tanzania, at 110,000 high estimate against 97,000 high estimate in Zimbabwe as of 2009.
- What is the difference in aids deaths in adults and children between Tanzania and Zimbabwe?
- 13,000 high estimate, with Tanzania ahead.
- How many years of comparable data are there for Tanzania and Zimbabwe?
- 20 years are reported by both, from 1990 to 2009.
- How do Tanzania and Zimbabwe rank globally for aids deaths in adults and children?
- Tanzania ranks 3rd and Zimbabwe ranks 5th of 48 countries.
- Where does this data come from?
- UNAIDS and the WHO's Report on the Global AIDS Epidemic, published as AIDS deaths in adults and children (high estimate). Statizoid refreshes it automatically from the source and publishes the full history for both places.
Individual pages
About this data
Deaths due to HIV/AIDS are the estimated number of adults and children that have died in a specific year based in the modeling of HIV surveillance data using standard and appropriate tools.