New methods for estimating the tuberculosis case detection rate in high-HIV prevalence countries: the example of Kenya.

OBJECTIVE: To develop new methods for estimating the sputum smear-positive tuberculosis case detection rate (CDR) in a country where infection with HIV is prevalent. METHODS: We estimated the smear-positive tuberculosis CDR in HIV-negative and HIV-positive adults, and in all adults in Kenya. Data on time trends in tuberculosis case notification rates and on HIV infection prevalence in adults and in tuberculosis patients were used, along with data on tuberculosis control programme performance. FINDINGS: In 2006, the estimated smear-positive tuberculosis CDR in HIV-negative adults was 79% (95% confidence interval, CI: 64-94) and in HIV-positive adults, 57% (95% CI: 26-88), giving a weighted mean of 68% (95% CI: 49-87). The separate estimate for all smear-positive tuberculosis cases was 72% (95% CI: 53-91), giving an overall average for the three estimates of 70% (95% CI: 58-82). As the tuberculosis CDR in 1996 was 57% (95% CI: 47-67), the estimated increase by 2006 was 13 percentage points (95% CI: 6-20), or 23%. This increase was accompanied by a more than doubling of the resources devoted to tuberculosis control in Kenya, including facilities and staff. CONCLUSION: Using three approaches to estimate the tuberculosis CDR in a country where HIV infection is prevalent, we showed that expansion of the tuberculosis control programme in Kenya led to an increase of 23% in the CDR between 1996 and 2006. While the methods developed here can be applied in other countries with a high prevalence of HIV infection, they rely on precise data on trends in such prevalence in the general population and among tuberculosis patients.

Incongruent HIV and tuberculosis co-dynamics in Kenya: interacting epidemics monitor each other.

OBJECTIVE: Kenya is heralded as an example of declining HIV in Africa, while its tuberculosis (TB) numbers continue rising. We conducted a comparative investigation of TB-HIV co-dynamics in Africa to determine the likelihood of reported trends. METHODS AND RESULTS: Our mathematical modeling analysis exposes the notable incongruence of reported trends in Kenya because TB-HIV co-dynamics, tightly knit worldwide and most dramatically in sub-Saharan Africa, suggest that declining HIV trends should trigger reductions in TB trends. Moreover, a continental-scale analysis of TB-HIV trends places Kenya as an outlier in eastern and southern Africa, and shows TB outpacing HIV in western central Africa. We further investigate which TB processes across HIV stages have greater potential to reduce TB incidence via a sensitivity analysis. CONCLUSIONS: There are two parsimonious explanations: an unaccounted improvement in TB case detection has occurred, or HIV is not declining as reported. The TB-HIV mismatch could be compounded by surveillance biases due to spatial heterogeneity in disease dynamics. Results highlight the need to re-evaluate trends of both diseases in Kenya, and identify the most critical epidemiological factors at play. Substantial demographic changes have occurred in Kenya, including rapid urbanization accompanied by poor living conditions, which could disproportionately increase TB incidence. Other possible contributors include immune reconstitution due to the recent delivery of antiretrovirals, and an increased presence of the virulent Beijing/W TB genotype. Results support the importance of integrating information from closely interacting epidemics, because this approach provides critical insights unobtainable when components of generalized epidemics are considered individually.

Impact of HIV on novel therapies for tuberculosis control.

OBJECTIVE AND DESIGN: The increased risk for tuberculosis in HIV-infected people has fueled a worldwide resurgence of tuberculosis. A major hindrance to controlling tuberculosis is the long treatment duration, leading to default, jeopardizing cure, and generating drug resistance. We investigated how tuberculosis is impacted by reducing treatment duration alone or combined with enhanced case detection and/or cure under different HIV prevalence levels. METHODS: Our model includes HIV stages I-IV and was calibrated to long-term tuberculosis and HIV data from Kenya. Benefits were assessed in terms of absolute and relative reductions in new tuberculosis cases and deaths. RESULTS: Compared with present-day strategies, at 3-20% HIV prevalence we attain a 6-20% decrease in incidence and mortality in 25 years when reducing treatment duration alone; benefits exceed 300% when combined with increased detection and cure. Benefits vary substantially according to HIV status and prevalence. Challenges arise because in absolute terms the number of infected people and deaths increases dramatically with increasing HIV prevalence, and because the relative efficacy of tuberculosis control policies displays a nonlinear pattern whereby they become less effective on a per capita basis at HIV prevalence levels greater than 15%. Benefits of reducing treatment duration may even be reversed at extreme HIV prevalence levels. Benefits of increasing cure versus detection increase as HIV prevalence increases. CONCLUSION: Reducing tuberculosis treatment duration, alone or in combination with other control strategies, can provide enormous benefits at high HIV prevalence. Tuberculosis control policies need to account for HIV levels because the efficacy of different interventions varies substantially with HIV prevalence.