Tuberculosis Diagnostic Delays and Treatment Outcomes among Patients with COVID-19, California, USA, 2020.

We assessed tuberculosis (TB) diagnostic delays among patients with TB and COVID-19 in California, USA. Among 58 persons, 43% experienced TB diagnostic delays, and a high proportion (83%) required hospitalization for TB. Even when viral respiratory pathogens circulate widely, timely TB diagnostic workup for at-risk persons remains critical for reducing TB-related illness.

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.

Epidemiology of tuberculosis cases with end-stage renal disease, California, 2010.

BACKGROUND/AIMS: Few studies have compared population-based tuberculosis (TB) incidence rates by end-stage renal disease (ESRD) status. No studies have compared TB genotypes by ESRD status to determine whether TB disease resulted from recent transmission or reactivation of latent TB infection (LTBI). We calculated TB incidence rates and compared demographic and clinical characteristics and genotypes among TB cases by ESRD status. METHODS: This analysis was based on prospective surveillance for TB cases during 2010 in California. Clustered genotype was defined as ≥2 culture-positive TB cases with matching genotypes in the same county. The χ(2) or Wilcoxon rank-sum test was used to compare variables. RESULTS: During 2010, 83 TB cases with ESRD and 2,244 cases without ESRD were reported in California; TB incidence rates were 110.3/100,000 and 6.0/100,000, respectively. ESRD case patients versus patients without ESRD were more likely to be older (median age 66 vs. 49 years; p < 0.001), foreign-born persons who had arrived in the USA >5 years before TB diagnosis (97 vs. 75%; p < 0.001) and dead at TB diagnosis (7 vs. 2%; p = 0.01). ESRD patients were less likely to have a positive tuberculin skin test (50 vs. 80%; p < 0.001), positive acid-fast bacilli sputum smears (33 vs. 53%; p = 0.01) and cavities on chest radiography (6 vs. 21%; p = 0.01). No differences in proportions of clustered TB genotypes were detected (20 vs. 23%; p = 0.54). CONCLUSIONS: Rates of TB are 18 times higher in California's ESRD population, and TB disease likely occurred due to LTBI reactivation because few patients had clustered genotypes. Efforts to prevent TB among ESRD patients may require the use of newer diagnostic tests and promotion of LTBI treatment.

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.

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.