Explore the vast range of titles available.

Background. Pyrazinamide (PZA) is essential in tuberculosis treatment. We describe the prevalence, trends, and predictors of PZA resistance in Mycobacterium tuberculosis complex (MTBC) in the United States. Methods. We analyzed culture-positive MTBC cases with reported drug susceptibility tests for PZA in 38 jurisdictions routinely testing for PZA susceptibility from 1999 to 2009. National Tuberculosis Genotyping Service data for 2004–2009 were used to distinguish M. tuberculosis from Mycobacterium bovis and determine phylogenetic lineage. Results. Overall 2.7% (2167/79 321) of MTBC cases had PZA resistance, increasing annually from 2.0% to 3.3% during 1999–2009 (P < .001), largely because of an increase in PZA monoresistance. PZA-monoresistant MTBC (vs drug-susceptible) was associated with an age of 0–24 years (adjusted prevalence ratio [aPR],1.50; 95% confidence interval [CI], 1.31–1.71), Hispanic ethnicity (aPR, 3.52; 95% CI, 2.96–4.18), human immunodeficiency virus infection (aPR, 1.43; 95% CI, 1.15–1.77), extrapulmonary disease (aPR, 3.02; 95% CI, 2.60–3.52), and normal chest radiograph (aPR, 1.88; 95% CI, 1.63–2.16) and was inversely associated with Asian (aPR, 0.59; 95% CI, .47–.73) and black (aPR, 0.37; 95% CI, .29–.49) race. Among multidrug-resistant (MDR) cases, 38.0% were PZA-resistant; PZA resistance in MDR MTBC was associated with female sex (aPR, 1.25; 95% CI, 1.08–1.46) and previous tuberculosis diagnosis (aPR, 1.37; 95% CI, 1.16–1.62). Of 28 080 cases with genotyping data, 925 (3.3%) had PZA resistance; 465 of 925 (50.3%) were M. bovis. In non-MDR M. tuberculosis cases, PZA resistance was higher in the Indo-Oceanic than the East Asian lineage (2.2% vs 0.9%, respectively; aPR, 2.26; 95% CI, 1.53–3.36), but in MDR cases it was lower in the Indo-Oceanic lineage (22.0% vs 43.4%, respectively; aPR, 0.54; 95% CI, .32–.90). Conclusions. Specific human and mycobacterial characteristics were associated with PZA-resistant MTBC, reflecting both specific subgroups of the population and phylogenetic lineages of the mycobacteria.

Mycobacterium tuberculosis transmission dynamics in high-burden settings are poorly understood. Growing evidence suggests transmission may be characterized by extensive individual heterogeneity in secondary cases (i.e., superspreading), yet the degree and influence of such heterogeneity is largely unknown and unmeasured in high burden-settings. We conducted a prospective, population-based molecular epidemiology study of TB transmission in both an urban and rural setting of Botswana, one of the highest TB burden countries in the world. We used these empirical data to fit two mathematical models (urban and rural) that jointly quantified both the effective reproductive number, R , and the propensity for superspreading in each population. We found both urban and rural populations were characterized by a high degree of individual heterogeneity, however such heterogeneity disproportionately impacted the rural population: 99% of secondary transmission was attributed to only 19% of infectious cases in the rural population compared to 60% in the urban population and the median number of incident cases until the first outbreak of 30 cases was only 32 for the rural model compared to 791 in the urban model. These findings suggest individual heterogeneity plays a critical role shaping local TB epidemiology within subpopulations.

Ongoing symptoms might follow acute COVID-19. Using electronic health information, we compared pre‒ and post‒COVID-19 diagnostic codes to identify symptoms that had higher encounter incidence in the post‒COVID-19 period as sequelae. This method can be used for hypothesis generation and ongoing monitoring of sequelae of COVID-19 and future emerging diseases.

Combining genomic and geospatial data can be useful for understanding Mycobacterium tuberculosis transmission in high-burden tuberculosis (TB) settings. We performed whole-genome sequencing on M. tuberculosis DNA extracted from sputum cultures from a population-based TB study conducted in Gaborone, Botswana, during 2012-2016. We determined spatial distribution of cases on the basis of shared genotypes among isolates. We considered clusters of isolates with ≤5 single-nucleotide polymorphisms identified by whole-genome sequencing to indicate recent transmission and clusters of ≥10 persons to be outbreaks. We obtained both molecular and geospatial data for 946/1,449 (65%) participants with culture-confirmed TB; 62 persons belonged to 5 outbreaks of 10-19 persons each. We detected geospatial clustering in just 2 of those 5 outbreaks, suggesting heterogeneous spatial patterns. Our findings indicate that targeted interventions applied in smaller geographic areas of high-burden TB identified using integrated genomic and geospatial data might help interrupt TB transmission during outbreaks.

Tuberculosis caused by concurrent infection with multiple Mycobacterium tuberculosis strains (i.e., mixed infection) challenges clinical and epidemiologic paradigms. We explored possible transmission mechanisms of mixed infection in a population-based, molecular epidemiology study in Botswana during 2012-2016. We defined mixed infection as multiple repeats of alleles at >2 loci within a discrete mycobacterial interspersed repetitive unit-variable-number tandem-repeat (MIRU-VNTR) result. We compared mixed infection MIRU-VNTR results with all study MIRU-VNTR results by considering all permutations at each multiple allele locus; matched MIRU-VNTR results were considered evidence of recently acquired strains and nonmatched to any other results were considered evidence of remotely acquired strains. Among 2,051 patients, 34 (1.7%) had mixed infection, of which 23 (68%) had recently and remotely acquired strains. This finding might support the mixed infection mechanism of recent transmission and simultaneous remote reactivation. Further exploration is needed to determine proportions of transmission mechanisms in settings where mixed infections are prevalent.

Contact investigation is one public health measure used to prevent tuberculosis by identifying and treating persons exposed to Mycobacterium tuberculosis. Contact investigations are a major tenet of global tuberculosis elimination efforts, but for many reasons remain ineffective. We describe a novel neighbor-based approach to reframe contact investigations.

Private Practitioners (PP) are the primary source of health care for patients in India. Limited representative information is available on TB management practices of Indian PP or on the efficacy of India's Revised National Tuberculosis Control Programme (RNTCP) to improve the quality of TB management through training of PP. We conducted a cross-sectional survey of a systematic random sample of PP in one urban area in Western India (Pune, Maharashtra). We presented sample clinical vignettes and determined the proportions of PPs who reported practices consistent with International Standards of TB Care (ISTC). We examined the association between RNTCP training and adherence to ISTC by calculating odds ratios and 95% confidence intervals. Of 3,391 PP practicing allopathic medicine, 249 were interviewed. Of these, 55% had been exposed to RNTCP. For new pulmonary TB patients, 63% (158/249) of provider responses were consistent with ISTC diagnostic practices, and 34% (84/249) of responses were consistent with ISTC treatment practices. However, 48% (120/249) PP also reported use of serological tests for TB diagnosis. In the new TB case vignette, 38% (94/249) PP reported use of at least one second line anti-TB drug in the treatment regimen. RNTCP training was not associated with diagnostic or treatment practices. In Pune, India, despite a decade of training activities by the RNTCP, high proportions of providers resorted to TB serology for diagnosis and second-line anti-TB drug use in new TB patients. Efforts to achieve universal access to quality TB management must account for the low quality of care by PP and the lack of demonstrated effect of current training efforts.

Background HIV is a major driver of the tuberculosis epidemic in sub-Saharan Africa. The population-level impact of antiretroviral therapy (ART) scale-up on tuberculosis rates in this region has not been well studied. We conducted a descriptive analysis to examine evidence of population-level effect of ART on tuberculosis by comparing trends in estimated tuberculosis notification rates, by HIV status, for countries in sub-Saharan Africa. Methods We estimated annual tuberculosis notification rates, stratified by HIV status during 2010–2015 using data from WHO, the Joint United Nations Programme on HIV/AIDS, and the United Nations Population Division. Countries were included in this analysis if they had ≥4 years of HIV prevalence estimates and ≥ 75% of tuberculosis patients with known HIV status. We compared tuberculosis notification rates among people living with HIV (PLHIV) and people without HIV via Wilcoxon rank sum test. Results Among 23 included countries, the median annual average change in tuberculosis notification rates among PLHIV during 2010–2015 was -5.7% (IQR -6.9 to -1.7%), compared to a median change of -2.3% (IQR -4.2 to -0.1%) among people without HIV ( p -value = 0.0099). Among 11 countries with higher ART coverage, the median annual average change in TB notification rates among PLHIV was -6.8% (IQR -7.6 to -5.7%) compared to a median change of -2.1% (IQR -6.0 to 0.7%) for PLHIV in 12 countries with lower ART coverage ( p  = 0.0106). Conclusion Tuberculosis notification rates declined more among PLHIV than people without HIV, and have declined more in countries with higher ART coverage. These results are consistent with a population-level effect of ART on decreasing TB incidence among PLHIV. To further reduce TB incidence among PLHIV, additional scale-up of ART as well as greater use of isoniazid preventive therapy and active case-finding will be necessary.

Diagnosis of tuberculosis (TB) among young children (<5 years) is challenging due to the paucibacillary nature of clinical disease and clinical similarities to other childhood diseases. We used machine learning to develop accurate prediction models of microbial confirmation with simply defined and easily obtainable clinical, demographic, and radiologic factors. We evaluated eleven supervised machine learning models (using stepwise regression, regularized regression, decision tree, and support vector machine approaches) to predict microbial confirmation in young children (<5 years) using samples from invasive (reference-standard) or noninvasive procedure. Models were trained and tested using data from a large prospective cohort of young children with symptoms suggestive of TB in Kenya. Model performance was evaluated using areas under the receiver operating curve (AUROC) and precision-recall curve (AUPRC), accuracy metrics. (i.e., sensitivity, specificity), F-beta scores, Cohen’s Kappa, and Matthew’s Correlation Coefficient. Among 262 included children, 29 (11%) were microbially confirmed using any sampling technique. Models were accurate at predicting microbial confirmation in samples obtained from invasive procedures (AUROC range: 0.84–0.90) and from noninvasive procedures (AUROC range: 0.83–0.89). History of household contact with a confirmed case of TB, immunological evidence of TB infection, and a chest x-ray consistent with TB disease were consistently influential across models. Our results suggest machine learning can accurately predict microbial confirmation of M . tuberculosis in young children using simply defined features and increase the bacteriologic yield in diagnostic cohorts. These findings may facilitate clinical decision making and guide clinical research into novel biomarkers of TB disease in young children.

Development of resistance to antituberculosis drugs during treatment (i.e., acquired resistance) can lead to emergence of resistant strains and consequent poor clinical outcomes. However, it is unknown whether Mycobacterium tuberculosis complex species and lineage affects the likelihood of acquired resistance. We analyzed data from the U.S. National Tuberculosis Surveillance System and National Tuberculosis Genotyping Service for tuberculosis cases during 2004-2011 with assigned species and lineage and both initial and final drug susceptibility test results. We determined univariate associations between species and lineage of Mycobacterium tuberculosis complex bacteria and acquired resistance to isoniazid, rifamycins, fluoroquinolones, and second-line injectables. We used Poisson regression with backward elimination to generate multivariable models for acquired resistance to isoniazid and rifamycins. M. bovis was independently associated with acquired resistance to isoniazid (adjusted prevalence ratio = 8.46, 95% CI 2.96-24.14) adjusting for HIV status, and with acquired resistance to rifamycins (adjusted prevalence ratio = 4.53, 95% CI 1.29-15.90) adjusting for homelessness, HIV status, initial resistance to isoniazid, site of disease, and administration of therapy. East Asian lineage was associated with acquired resistance to fluoroquinolones (prevalence ratio = 6.10, 95% CI 1.56-23.83). We found an association between mycobacterial species and lineage and acquired drug resistance using U.S. surveillance data. Prospective clinical studies are needed to determine the clinical significance of these findings, including whether rapid genotyping of isolates at the outset of treatment may benefit patient management.