Objective:
To classify the prevalence of multi-drug resistant tuberculosis (MDR-TB) in two different
geographic settings in western Kenya using the Lot Quality Assurance Sampling (LQAS)
methodology.
Design:
The prevalence of drug resistance was classified among treatment-naïve smear positive TB
patients in two settings, one rural and one urban. These regions were classified as having
high or low prevalence of MDR-TB according to a static, two-way LQAS sampling plan
selected to classify high resistance regions at greater than 5% resistance and low resistance
regions at less than 1% resistance.
Results:
This study classified both the urban and rural settings as having low levels of TB drug resistance.
Out of the 105 patients screened in each setting, two patients were diagnosed with
MDR-TB in the urban setting and one patient was diagnosed with MDR-TB in the rural setting.
An additional 27 patients were diagnosed with a variety of mono- and poly- resistant
strains.
Conclusion:
Further drug resistance surveillance using LQAS may help identify the levels and geographical
distribution of drug resistance in Kenya and may have applications in other countries in
the African Region facing similar resource constraints.
Description:
Objective:
To classify the prevalence of multi-drug resistant tuberculosis (MDR-TB) in two different
geographic settings in western Kenya using the Lot Quality Assurance Sampling (LQAS)
methodology.
Design:
The prevalence of drug resistance was classified among treatment-naïve smear positive TB
patients in two settings, one rural and one urban. These regions were classified as having
high or low prevalence of MDR-TB according to a static, two-way LQAS sampling plan
selected to classify high resistance regions at greater than 5% resistance and low resistance
regions at less than 1% resistance.
Results:
This study classified both the urban and rural settings as having low levels of TB drug resistance.
Out of the 105 patients screened in each setting, two patients were diagnosed with
MDR-TB in the urban setting and one patient was diagnosed with MDR-TB in the rural setting.
An additional 27 patients were diagnosed with a variety of mono- and poly- resistant
strains.
Conclusion:
Further drug resistance surveillance using LQAS may help identify the levels and geographical
distribution of drug resistance in Kenya and may have applications in other countries in
the African Region facing similar resource constraints.