Tuberculosis

tuberculosis treatment success rate

The increasing presence of drug resistance TB strains produce a serious challenge for the control of TB. This is especially true considering that there have been no new antibiotics against TB
after the 1960s and development of new drugs is not a top priority in rich countries due to their relatively low TB
incidence. It is therefore critical to improve the efficiency of the TB control strategies by fully exploiting the information coming from the electronic TB register and from other management information systems to identify better management strategies.

I can help to analyse the data coming from the electronic TB
register and to organize surveillance strategies to monitor antibiotic resistance.

Examples

(a) I provided technical assistance in epidemiology to the Department of Health (DOH) of KwaZulu-Natal (KZN), South Africa, in monitoring and evaluation of TB
programme. This included the analysis of the complex architecture of the electronic TB
register and the critical interpretation of treatment outcome indicators. One of the issues that I evaluated in KZN was the effect that the absence of patients' ID in the TB
electronic register had on double counting. This was important in identifying potential reliability problems in estimating treatment outcome rates, especially in districts that were characterized by high frequency of transfers.

(b) I have evaluated the electronic TB register through chart audits. This has allowed the DOH of KZN to verify the hypothesis that districts with a high transfers' rate, were producing biased outcome indicators due to an over-inflated denominator. The chart audits allowed to adjust the artificially low treatment success rates due to the above mentioned problem, producing a better estimation of the performance of the TB
programme compared with what was estimated from the electronic TB

(c) I evaluated the TB programme in the district of Umzinyathi in KZN to identify management factors that were associated with treatment outcomes. The evaluation teams visited the outpatients' TB
clinics of the district to collect data on infrastructure, staffing, strategies used to trace defaulters and other factors that were not available from the electronic TB
register. The information was used to predict which factors were significantly associated with treatment outcomes. One operational product of this analysis was the identification of the critical levels of workload in terms of patients per staff that, at parity of other factors, were associated with treatment success rate. This provided a value added criteria to identify management strategies to improve the effectiveness of the TB
programme and to rank the clinic sites that were more at risk for poor performance due to their excessive workload.

(d) I was involved in the surveillance system of the first major outbreak of extensive drug resistant (XDR) TB. In 2005 the Church of Scotland Hospital in Tugela Ferry, Umzinyathi district, KwaZulu-Natal, started to report increasing numbers of HIV/AIDS patients who were not responding to ART treatment. This brought to light the first ever recorded epidemic of XDR TB
 that was associated with extremely high mortality rate. Together with other researchers who were working in this district hospital, I was involved in the surveillance system of this XDR epidemic and in testing the family contacts of the index cases. This produced the first estimate of the transmission rates of XDR to the contacts.

(e) I was engaged as consultant by the University Research Corporation (URC) to improve their monitoring and evaluation system. URC has been providing support to the TB
 program at national, provincial, district and facility level through key experts and Provincial Coordinators. I assessed the Project's Monitoring & Evaluation (M&E) system and I analysed the data from the districts and champion facilities covered by the project. I also evaluated a pilot test on the use of smartphones to collect monitoring data on new TB patients.