Second Nationwide Tuberculosis Outbreak Caused by Bone Allografts Containing Live Cells - United States, 2023.

During July 7-11, 2023, CDC received reports of two patients in different states with a tuberculosis (TB) diagnosis following spinal surgical procedures that used bone allografts containing live cells from the same deceased donor. An outbreak associated with a similar product manufactured by the same tissue establishment (i.e., manufacturer) occurred in 2021. Because of concern that these cases represented a second outbreak, CDC and the Food and Drug Administration worked with the tissue establishment to determine that this product was obtained from a donor different from the one implicated in the 2021 outbreak and learned that the bone allograft product was distributed to 13 health care facilities in seven states. Notifications to all seven states occurred on July 12. As of December 20, 2023, five of 36 surgical bone allograft recipients received laboratory-confirmed TB disease diagnoses; two patients died of TB. Whole-genome sequencing demonstrated close genetic relatedness between positive Mycobacterium tuberculosis cultures from surgical recipients and unused product. Although the bone product had tested negative by nucleic acid amplification testing before distribution, M. tuberculosis culture of unused product was not performed until after the outbreak was recognized. The public health response prevented up to 53 additional surgical procedures using allografts from that donor; additional measures to protect patients from tissue-transmitted M. tuberculosis are urgently needed.

Model-based Analysis of Tuberculosis Genotype Clusters in the United States Reveals High Degree of Heterogeneity in Transmission and State-level Differences Across California, Florida, New York, and Texas.

BACKGROUND: Reductions in tuberculosis (TB) transmission have been instrumental in lowering TB incidence in the United States. Sustaining and augmenting these reductions are key public health priorities. METHODS: We fit mechanistic transmission models to distributions of genotype clusters of TB cases reported to the Centers for Disease Control and Prevention during 2012-2016 in the United States and separately in California, Florida, New York, and Texas. We estimated the mean number of secondary cases generated per infectious case (R0) and individual-level heterogeneity in R0 at state and national levels and assessed how different definitions of clustering affected these estimates. RESULTS: In clusters of genotypically linked TB cases that occurred within a state over a 5-year period (reference scenario), the estimated R0 was 0.29 (95% confidence interval [CI], .28-.31) in the United States. Transmission was highly heterogeneous; 0.24% of simulated cases with individual R0 >10 generated 19% of all recent secondary transmissions. R0 estimate was 0.16 (95% CI, .15-.17) when a cluster was defined as cases occurring within the same county over a 3-year period. Transmission varied across states: estimated R0s were 0.34 (95% CI, .3-.4) in California, 0.28 (95% CI, .24-.36) in Florida, 0.19 (95% CI, .15-.27) in New York, and 0.38 (95% CI, .33-.46) in Texas. CONCLUSIONS: TB transmission in the United States is characterized by pronounced heterogeneity at the individual and state levels. Improving detection of transmission clusters through incorporation of whole-genome sequencing and identifying the drivers of this heterogeneity will be essential to reducing TB transmission.

Logically Inferred Tuberculosis Transmission (LITT): A Data Integration Algorithm to Rank Potential Source Cases.

Understanding tuberculosis (TB) transmission chains can help public health staff target their resources to prevent further transmission, but currently there are few tools to automate this process. We have developed the Logically Inferred Tuberculosis Transmission (LITT) algorithm to systematize the integration and analysis of whole-genome sequencing, clinical, and epidemiological data. Based on the work typically performed by hand during a cluster investigation, LITT identifies and ranks potential source cases for each case in a TB cluster. We evaluated LITT using a diverse dataset of 534 cases in 56 clusters (size range: 2-69 cases), which were investigated locally in three different U.S. jurisdictions. Investigators and LITT agreed on the most likely source case for 145 (80%) of 181 cases. By reviewing discrepancies, we found that many of the remaining differences resulted from errors in the dataset used for the LITT algorithm. In addition, we developed a graphical user interface, user's manual, and training resources to improve LITT accessibility for frontline staff. While LITT cannot replace thorough field investigation, the algorithm can help investigators systematically analyze and interpret complex data over the course of a TB cluster investigation. Code available at: https://github.com/CDCgov/TB_molecular_epidemiology/tree/1.0; https://zenodo.org/badge/latestdoi/166261171.

Mutation of Mycobacterium tuberculosis and Implications for Using Whole-Genome Sequencing for Investigating Recent Tuberculosis Transmission.

Tuberculosis (TB) control programs use whole-genome sequencing (WGS) of Mycobacterium tuberculosis (Mtb) for detecting and investigating TB case clusters. Existence of few genomic differences between Mtb isolates might indicate TB cases are the result of recent transmission. However, the variable and sometimes long duration of latent infection, combined with uncertainty in the Mtb mutation rate during latency, can complicate interpretation of WGS results. To estimate the association between infection duration and single nucleotide polymorphism (SNP) accumulation in the Mtb genome, we first analyzed pairwise SNP differences among TB cases from Los Angeles County, California, with strong epidemiologic links. We found that SNP distance alone was insufficient for concluding that cases are linked through recent transmission. Second, we describe a well-characterized cluster of TB cases in California to illustrate the role of genomic data in conclusions regarding recent transmission. Longer presumed latent periods were inconsistently associated with larger SNP differences. Our analyses suggest that WGS alone cannot be used to definitively determine that a case is attributable to recent transmission. Methods for integrating clinical, epidemiologic, and genomic data can guide conclusions regarding the likelihood of recent transmission, providing local public health practitioners with better tools for monitoring and investigating TB transmission.

Solid Organ Transplant-Transmitted Tuberculosis Linked to a Community Outbreak - California, 2015.

In the spring of 2015, a local health department (LHD) in county A notified the California Department of Public Health (CDPH) about three adults with close ties to one another and a congregate community site who had received diagnoses of tuberculosis (TB) disease within a 3-month period. Subsequent review revealed matching TB genotypes indicating that the cases were likely part of a chain of TB transmission. Only three TB cases in California in the preceding 2 years shared this same genotype. One of those three previous cases occurred in a lung-transplant recipient who had no identified epidemiologic links to the outbreak. CDPH, multiple LHDs, and CDC conducted an investigation and determined that the lung-transplant donor (patient 1) was epidemiologically linked to the three outbreak cases and had a tuberculin skin test (TST) conversion detected in 2012 upon reentry at a local jail. Three other solid organ recipients from this donor were identified; none had developed TB disease. This investigation suggests that review of organ donors' medical records from high-risk environments, such as jails, might reveal additional information about TB risk. The evaluation of TB in organ recipients could include genotyping analysis (1) and coordination among local, state, and national partners to evaluate the potential for donor-derived TB.

Genomic epidemiology of multidrug-resistant Mycobacterium tuberculosis during transcontinental spread.

The transcontinental spread of multidrug-resistant (MDR) tuberculosis is poorly characterized in molecular epidemiologic studies. We used genomic sequencing to understand the establishment and dispersion of MDR Mycobacterium tuberculosis within a group of immigrants to the United States. We used a genomic epidemiology approach to study a genotypically matched (by spoligotype, IS6110 restriction fragment length polymorphism, and mycobacterial interspersed repetitive units-variable number of tandem repeat signature) lineage 2/Beijing MDR strain implicated in an outbreak of tuberculosis among refugees in Thailand and consecutive cases within California. All 46 MDR M. tuberculosis genomes from both Thailand and California were highly related, with a median difference of 10 single-nucleotide polymorphisms (SNPs). The Wat Tham Krabok (WTK) strain is a new sequence type distinguished from all known Beijing strains by 55 SNPs and a genomic deletion (Rv1267c) associated with increased fitness. Sequence data revealed a highly prevalent MDR strain that included several closely related but distinct allelic variants within Thailand, rather than the occurrence of a single outbreak. In California, sequencing data supported multiple independent introductions of WTK with subsequent transmission and reactivation within the state, as well as a potential super spreader with a prolonged infectious period. Twenty-seven drug resistance-conferring mutations and 4 putative compensatory mutations were found within WTK strains. Genomic sequencing has substantial epidemiologic value in both low- and high-burden settings in understanding transmission chains of highly prevalent MDR strains.

Improved outcomes found after implementing a systematic evaluation and program improvement process for tuberculosis.

California's state and local tuberculosis (TB) programs collaborated to develop the Tuberculosis Indicators Project (TIP), a program evaluation and improvement process. In TIP, local and state staff review data, identify program gaps, implement plans to improve local TB program performance, and evaluate outcomes. After 10 years of project implementation, indicator performance changes and patient outcomes were measured. Eighty-seven percent of participating programs showed a performance increase in targeted indicators after three years compared with 57% of comparison groups. Statistically significant performance change was more common in the intervention local health departments (LHDs) than in comparison groups. The most notable performance changes were in the contact investigation and case management indicators. These results indicate that this systematic evaluation and program improvement project was associated with improved LHD TB control performance and may be useful to inform improvement projects in other public health programs.

Developing and using performance measures based on surveillance data for program improvement in tuberculosis control.

California state and local tuberculosis (TB) programs used a systematic process to develop a set of indicators to measure and improve program performance in controlling TB. These indicators were the basis for a quality improvement process known as the TB Indicators Project. Indicators were derived from guidelines and legal mandates for clinical, case management, and surveillance standards and were assessed using established criteria. The indicators were calculated using existing surveillance data. The indicator set was field tested by local programs with high TB morbidity and subsequently revised. Collaboration with key stakeholders at all stages was crucial to developing useful and accepted indicators. Data accessibility was a critical requirement for indicator implementation. Indicators most frequently targeted for performance improvement were those perceived to be amenable to intervention. Indicators based on surveillance data can complement other public health program improvement efforts by identifying program gaps and successes and monitoring performance trends.

Multistate outbreak of MDR TB identified by genotype cluster investigation.

In 2008, diagnosis and investigation of 2 multidrug-resistant tuberculosis cases with matching genotypes led to identification of an outbreak among foreign-born persons who performed short-term seafood production work in Alaska during 2006. Tuberculosis control programs should consider the possibility of domestic transmission even among foreign-born patients.