Abstract
BACKGROUND: Implementation of an effective Tuberculosis Routine Surveillance System in low-income countries like Tanzania is problematic, despite being an essential tool for the detection and effective monitoring of drug resistant tuberculosis. Long delays in specimen transportation from the facilities to reference laboratory and results dissemination back to the health facilities, result in poor patient management, particularly where multidrug-resistant tuberculosis disease is present. METHODS: Following a detailed qualitative study, a pilot intervention of a revised Tuberculosis Routine Surveillance System was implemented in Mwanza region, Tanzania. This included the use of rapid molecular methods for the detection of both tuberculosis and drug resistance using Xpert MTB/RIF in some Mwanza sites, the use of Xpert MTB/RIF and Line Probe Assay at the Central Tuberculosis Reference Laboratory, a revised communication strategy and interventions to address the issue of poor form completion. A before and after comparison of the intervention on the number of drug resistant tuberculosis cases identified and the time taken for results feedback to the requesting site was reported. RESULTS: The revised system for previously treated cases tested at the Central Reference Laboratory was able to obtain the following findings; the number of cases tested increased from 75 in 2016 to 185 in 2017. The times for specimen transportation from health facilities to the reference laboratory were reduced by 22% (from 9 to 7 days). The median time for the district to receive results was reduced by 36% (from 11 to 7 days). Overall the number of drug resistant tuberculosis cases starting treatment increased by 67% (from 12 to 20). CONCLUSION: Detection of drug resistance could significantly be enhanced, and delays reduced by introduction of new technologies and improved routine surveillance system, including better communication using mobile applications such as 'WhatsApp' and close follow-ups. A larger scale study is now merited to ascertain if these benefits are robust across different contexts.