Table 3.
Geographical distribution patterns of M. tuberculosis drug mono resistance strains isolated from HIV negative and positive TB patients in Western Kenya
| County | HIV negative | HIV positive | ||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| RIF R | INH R | STY R | ETH R | PZA R | Total | RIF R | INH R | STY R | ETH R | PZA R | Total | |
| Nyamira | 2 (0.7%) | 0 (0.0%) | 1 (0.3%) | 0 (0.0%) | 0 (0.0%) | 3 (1.0%) | 0 (0.0%) | 2 (0.7%) | 0 (0.0%) | 2 (0.7%) | 0 (0.0%) | 4 (1.5%) |
| Bungoma | 1 (0.3%) | 3 (1.0%) | 2 (0.7%) | 2 (0.7%) | 1 (0.3%) | 9 (3.1%) | 1 (0.4%) | 1 (0.4%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 2 (0.7%) |
| Busia | 2 (3.5%) | 8 (2.8%) | 1 (0.3%) | 0 (0.0%) | 3 (1.0%) | 14 (4.9%) | 1 (0.4%) | 7 (2.6%) | 1 (0.4%) | 0 (0.0%) | 2 (0.7%) | 11 (4.1%) |
| Homabay | 10 (3.5%) | 9 (3.1%) | 1 (0.3%) | 0 (0.0%) | 1 (0.3%) | 21 (7.3%) | 1 (0.4%) | 7 (2.6%) | 1 (0.4%) | 0 (0.0%) | 1 (0.4%) | 10 (3.7%) |
| Kakamega | 1 (0.3%) | 4 (1.4%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 5 (1.7%) | 3 (1.1%) | 2 (0.7%) | 0 (0.0%) | 0 (0.0%) | 1 (0.4%) | 6 (2.2%) |
| Kisumu | 4 (1.4%) | 7 (2.4%) | 4 (1.4%) | 1 (0.3%) | 2 (0.7%) | 18 (6.3%) | 7 (2.6%) | 3 (1.1%) | 2 (0.7%) | 3 (1.1%) | 1 (0.4%) | 15 (5.6%) |
| Migori | 3 (1.0%) | 7 (2.4%) | 1 (0.3%) | 0 (0.0%) | 1 (0.3%) | 12 (4.2%) | 4 (1.5%) | 5 (1.9%) | 0 (0.0%) | 1 (0.4%) | 0 (0.0%) | 10 (3.7%) |
| Kisii | 2 (0.7%) | 4 (1.4%) | 0 (0.0%) | 1 (0.3%) | 0 (0.0%) | 7 (2.4%) | 2 (0.7%) | 1 (0.4%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 3 (1.1%) |
| Vihiga | 1 (1.0%) | 5 (1.7%) | 0 (0.0%) | 1 (0.3%) | 1 (0.3%) | 8 (2.8%) | 1 (1.4%) | 3 (1.1%) | 1 (0.4%) | 1 (0.4%) | 0 (0.0%) | 6 (2.2%) |
| Siaya | 1 (0.3%) | 5 (1.7%) | 1 (0.3%) | 0 (0.0%) | 1 (0.3%) | 8 (2.8%) | 4 (1.5%) | 3 (1.1%) | 0 (0.0%) | 0 (0.0%) | 0 (0.0%) | 7 (2.6%) |
| Total | 27 (9.4%) | 52 (18.2%) | 11 (3.8%) | 5 (1.7%) | 10 (3.5%) | 105 (36.7%) | 24 (9.0%) | 34 (12.7%) | 5 (1.9%) | 7 (2.6%) | 4 (1.5%) | 74 (27.7%) |
The bold was just used to track entries