Outlook for tuberculosis elimination in California: An individual-based stochastic model - PubMed (original) (raw)

Outlook for tuberculosis elimination in California: An individual-based stochastic model

Alex J Goodell et al. PLoS One. 2019.

Abstract

Rationale: As part of the End TB Strategy, the World Health Organization calls for low-tuberculosis (TB) incidence settings to achieve pre-elimination (<10 cases per million) and elimination (<1 case per million) by 2035 and 2050, respectively. These targets require testing and treatment for latent tuberculosis infection (LTBI).

Objectives: To estimate the ability and costs of testing and treatment for LTBI to reach pre-elimination and elimination targets in California.

Methods: We created an individual-based epidemic model of TB, calibrated to historical cases. We evaluated the effects of increased testing (QuantiFERON-TB Gold) and treatment (three months of isoniazid and rifapentine). We analyzed four test and treat targeting strategies: (1) individuals with medical risk factors (MRF), (2) non-USB, (3) both non-USB and MRF, and (4) all Californians. For each strategy, we estimated the effects of increasing test and treat by a factor of 2, 4, or 10 from the base case. We estimated the number of TB cases occurring and prevented, and net and incremental costs from 2017 to 2065 in 2015 U.S. dollars. Efficacy, costs, adverse events, and treatment dropout were estimated from published data. We estimated the cost per case averted and per quality-adjusted life year (QALY) gained.

Measurements and main results: In the base case, 106,000 TB cases are predicted to 2065. Pre-elimination was achieved by 2065 in three scenarios: a 10-fold increase in the non-USB and persons with MRF (by 2052), and 4- or 10-fold increase in all Californians (by 2058 and 2035, respectively). TB elimination was not achieved by any intervention scenario. The most aggressive strategy, 10-fold in all Californians, achieved a case rate of 8 (95% UI 4-16) per million by 2050. Of scenarios that reached pre-elimination, the incremental net cost was 20billion(non−USBandMRF)to20 billion (non-USB and MRF) to 20billion(non−USBandMRF)to48 billion. These had an incremental cost per QALY of 657,000to657,000 to 657,000to3.1 million. A more efficient but somewhat less effective single-lifetime test strategy reached as low as $80,000 per QALY.

Conclusions: Substantial gains can be made in TB control in coming years by scaling-up current testing and treatment in non-USB and those with medical risks.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1

Fig 1. Modelled cases attributable to medical risk factors, recent transmission, and imported cases, 2001–2014.

In 2014, the major risk factors for TB were smoking (267 attributable cases), diabetes (162), ESRD (74), HIV (51), transplant (3) and TNF-alpha (1). Increased risk due to recent transmission accounted to 146 cases, and 80 cases were imported. The remaining 1096 cases had no identified risk factor.

Fig 2

Fig 2. Results of calibration.

Mean number of TB cases predicted by model (250 iterations) and historic TB case data reported to California Department of Public Health, in the US-born (USB) and non-USB (NUSB), 2001–2014. For uncertainty ranges in modeled predictions, see Fig 3.

Fig 3

Fig 3. Annual cases of TB projected for 2017–2065, for LTBI test and treat strategies targeted to those with medical risk factors, the non-USB, both of these groups, and all (universal), for 2, 4, and 10-fold increases in testing rates.

Dotted and dashed lines show elimination and pre-elimination targets. Solid lines represent mean cases from 250 iterations using best available estimates. Shaded areas represent 95% confidence interval from 250 iterations using probabilistic sensitivity analysis.

References

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