The Road to Tuberculosis (Mycobacterium tuberculosis) Elimination in Arkansas; a Re-Examination of Risk Groups

Abstract

ObjectivesThis study was conducted to generate knowledge useful for developing public health interventions for more effective tuberculosis control in Arkansas.MethodsThe study population included 429 culture-confirmed reported cases (January 1, 2004–December 31, 2010). Mycobacterium tuberculosis genotyping data were used to identify cases likely due to recent transmission (clustered) versus reactivation (non-clustered). Poisson regression models estimated average decline rate in incidence over time and assessed the significance of differences between subpopulations. A multinomial logistic model examined differences between clustered and non-clustered incidence.ResultsA significant average annual percent decline was found for the overall incidence of culture-confirmed (9%; 95% CI: 5.5%, 16.9%), clustered (6%; 95% CI: 0.5%, 11.6%), and non-clustered tuberculosis cases (12%; 95% CI: 7.6%, 15.9%). However, declines varied among demographic groups. Significant declines in clustered incidence were only observed in males, non-Hispanic blacks, 65 years and older, and the rural population.ConclusionsThese findings suggest that the Arkansas tuberculosis control program must target both traditional and non-traditional risk groups for successful tuberculosis elimination. The present study also demonstrates that a thorough analysis of TB trends in different population subgroups of a given geographic region or state can lead to the identification of non-traditional risk factors for TB transmission. Similar studies in other low incidence populations would provide beneficial data for how to control and eventually eliminate TB in the U.S.

Effectiveness of contact investigations for tuberculosis control in Arkansas

“…Figures 4A and 4B compare model outputs with results from a recent molecular epidemiology study in which the large majority (87%) of culture-confirmed isolates from TB cases in Arkansas during the period 2004–2010 were genotyped (spoligotype and 12-locus MIRU-VNTR) to identify transmission clusters [21]. In that study, a cluster is defined as at least two cases diagnosed within a year from each other, caused by Mycobacterium tuberculosis isolates sharing the same molecular typing, independently of known epidemiological links [21].…”

“…In that study, a cluster is defined as at least two cases diagnosed within a year from each other, caused by Mycobacterium tuberculosis isolates sharing the same molecular typing, independently of known epidemiological links [21]. The Arkansas molecular epidemiological study found that 61% of cases were non-clustered, a figure well below the national average of 77% [27] because of the time-restricted cluster definition [21]. The fraction of clustered cases is often considered as a proxy of recently transmitted cases (e.g.…”

“…For this reason, we do not compare directly model estimates on the fraction of recently transmitted cases with results of the study. Instead, we reproduce criteria for cluster definition of the molecular epidemiology study within the model and compare model-predicted clusters to epidemiological observations in [21]. Figure 4A shows the percentage of cases identified as “non-clustered” for the entire population and disaggregated by age group.…”

“…The model is calibrated using surveillance data [20] and validated against data from four independent sources: a molecular epidemiology study in Arkansas [21], surveillance data on TB in the foreign-born [20] and nation-wide epidemiological studies on contact tracing in households [22] and workplaces [9]. The 9 free model parameters are calibrated by a procedure minimizing the error between data and model output.…”

A Field-Validated Approach Using Surveillance and Genotyping Data to Estimate Tuberculosis Attributable to Recent Transmission in the United States

“…TB disease attributable to RT represents active transmission in a population, which can be interrupted by prompt public health intervention (2). Measuring TB attributable to RT provides a tool with which public health programs can focus limited public health resources and track progress in TB control efforts to interrupt transmission (3–6). …”