Outbreak of tuberculosis in a closed setting: views on transmission based on results from molecular and conventional methods

Антушева, Е. В.; Mironuk, O M; Тарасова, И. В.; Eliseev, P. I.; Plusnina, G.; Ridell, Malin; Larsson, Lars-Olaf; Mariyandyshev, A.

doi:10.1016/j.jhin.2016.02.015

Cited by 6 publications

(4 citation statements)

References 16 publications

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“…Airborne pathogens from indoor coughing and sneezing may spread to other indoor spaces through air‐conditioning return air ducts. People who are known to be exposed to airborne pathogens from HVAC systems have developed a wide range of health problems including infectious, allergenic, or toxigenic diseases …”

Section: Introductionmentioning

confidence: 99%

“…People who are known to be exposed to airborne pathogens from HVAC systems have developed a wide range of health problems including infectious, allergenic, or toxigenic diseases. [5][6][7][8][9] Fibrous filters are conventionally applied to remove biological and nonbiological particles from HVAC systems. Although highlevel minimum efficiency reporting value (MERV) filters imply high particle removal efficiency, it is not optimal or economical to use high-efficiency particulate air (HEPA) filters in commercial HVAC systems.…”

Section: Introductionmentioning

confidence: 99%

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Disinfection efficacy of ultraviolet germicidal irradiation on airborne bacteria in ventilation ducts

et al. 2018

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A full-scale ventilation duct ultraviolet germicidal irradiation (in-duct UVGI) system was designed to investigate its disinfection efficacy on five airborne pathogens: Serratia marcescens, Pseudomonas alcaligenes, Escherichia coli, Salmonella enterica, and Staphylococcus epidermidis, with airflow Reynolds numbers from 4 × 10 to 8 × 10 . By varying the UV intensity, the susceptibility constants (Z-values) of the bacteria were experimentally determined to be 1.2, 1.0, 0.60, 0.39, and 0.37 m /J for S. marcescens, P. alcaligenes, E. coli, S. enterica, and S. epidermidis, respectively. The disinfection efficacy was numerically investigated on the basis of the predicted irradiance, which included emissive irradiance and diffuse refection irradiance. The results suggest that it is vital to properly evaluate the UV dose (irradiance intensity) received by airborne bacteria to determine their Z-values. In-duct UVGI inactivated nearly all of the test bacteria with Reynolds numbers of 4 × 10 (inlet velocity = 3 m/s), and the disinfection efficacy decreased as Reynolds numbers increased. The in-duct UVGI system would potentially provide a supplementary solution for improving indoor air quality (IAQ) within mechanical ventilated/air-conditioned environment.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Disinfection efficacy of ultraviolet germicidal irradiation on airborne bacteria in ventilation ducts

et al. 2018

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“…In this way, the number of repeats at each VNTR locus can be determined using different DNA sizing techniques for comparing isolates. It was found that 50 studies used VNTRtyping to detect M. tuberculosis MSIs, where 28 studies used it as the sole discriminatory method for this purpose (Allix et al, 2004;Shamputa et al, 2004;Umubyeyi et al, 2007;Fang et al, 2008;Hofmann-Thiel et al, 2009;Mokrousov et al, 2009;Stavrum et al, 2009;Dickman et al, 2010;Mulenga et al, 2010;Cohen et al, 2011;Gardy et al, 2011;Navarro et al, 2011Navarro et al, , 2015Cerezo et al, 2012;Furphy et al, 2012;Huyen et al, 2012;Hingley-Wilson et al, 2013;Muwonge et al, 2013;Peng et al, 2013;Biffa et al, 2014;Chaoui et al, 2014;Lamine-Khemiri et al, 2014;Zetola et al, 2014;Barletta et al, 2015;Mei et al, 2015;Pang et al, 2015;Shin et al, 2015Shin et al, , 2018Ssengooba et al, 2015;Streit et al, 2015;Wang et al, 2015;Zheng et al, 2015;Antusheva et al, 2016;Hajimiri et al, 2016;Hu et al, 2016;Egbe et al, 2017;Farmanfarmaei et al, 2017;Ghielmetti et al, 2017;…”

Section: Tuberculosis Complexmentioning

confidence: 99%

Methods for Detecting Mycobacterial Mixed Strain Infections–A Systematic Review

et al. 2020

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Mixed strain infection (MSI) refers to the concurrent infection of a susceptible host with multiple strains of a single pathogenic species. Known to occur in humans and animals, MSIs deserve special consideration when studying transmission dynamics, evolution, and treatment of mycobacterial diseases, notably tuberculosis in humans and paratuberculosis (or Johne's disease) in ruminants. Therefore, a systematic review was conducted to examine how MSIs are defined in the literature, how widespread the phenomenon is across the host species spectrum, and to document common methods used to detect such infections. Our search strategy identified 121 articles reporting MSIs in both humans and animals, the majority (78.5%) of which involved members of the Mycobacterium tuberculosis complex, while only a few (21.5%) examined non-tuberculous mycobacteria (NTM). In addition, MSIs exist across various host species, but most reports focused on humans due to the extensive amount of work done on tuberculosis. We reviewed the strain typing methods that allowed for MSI detection and found a few that were commonly employed but were associated with specific challenges. Our review notes the need for standardization, as some highly discriminatory methods are not adapted to distinguish between microevolution of one strain and concurrent infection with multiple strains. Further research is also warranted to examine the prevalence of NTM MSIs in both humans and animals. In addition, it is envisioned that the accurate identification and a better understanding of the distribution of MSIs in the future will lead to important information on the epidemiology and pathophysiology of mycobacterial diseases.

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“…Conventional genotyping methods, such as mycobacterial interspersed repetitive unit-variable number of tandem repeat (MIRU-VNTR), insertion sequence 6110 restriction fragment length polymorphism (RFLP), and spoligotyping, have been successfully applied for this purpose for decades (9)(10)(11)(12). Unfortunately, these methods lack sufficient discriminative power to confirm recent person-to-person transmission or distinguish remotely related Mtb strains belonging to the same genotype, which can lead to false clustering (13).…”

Section: Introductionmentioning

confidence: 99%

Unraveling tuberculosis patient cluster transmission chains: integrating WGS-based network with clinical and epidemiological insights

Sadovska,

Ozere,

Pole

et al. 2024

Front. Public Health

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BackgroundTuberculosis remains a global health threat, and the World Health Organization reports a limited reduction in disease incidence rates, including both new and relapse cases. Therefore, studies targeting tuberculosis transmission chains and recurrent episodes are crucial for developing the most effective control measures. Herein, multiple tuberculosis clusters were retrospectively investigated by integrating patients’ epidemiological and clinical information with median-joining networks recreated based on whole genome sequencing (WGS) data of Mycobacterium tuberculosis isolates.MethodsEpidemiologically linked tuberculosis patient clusters were identified during the source case investigation for pediatric tuberculosis patients. Only M. tuberculosis isolate DNA samples with previously determined spoligotypes identical within clusters were subjected to WGS and further median-joining network recreation. Relevant clinical and epidemiological data were obtained from patient medical records.ResultsWe investigated 18 clusters comprising 100 active tuberculosis patients 29 of whom were children at the time of diagnosis; nine patients experienced recurrent episodes. M. tuberculosis isolates of studied clusters belonged to Lineages 2 (sub-lineage 2.2.1) and 4 (sub-lineages 4.3.3, 4.1.2.1, 4.8, and 4.2.1), while sub-lineage 4.3.3 (LAM) was the most abundant. Isolates of six clusters were drug-resistant. Within clusters, the maximum genetic distance between closely related isolates was only 5–11 single nucleotide variants (SNVs). Recreated median-joining networks, integrated with patients’ diagnoses, specimen collection dates, sputum smear microscopy, and epidemiological investigation results indicated transmission directions within clusters and long periods of latent infection. It also facilitated the identification of potential infection sources for pediatric patients and recurrent active tuberculosis episodes refuting the reactivation possibility despite the small genetic distance of ≤5 SNVs between isolates. However, unidentified active tuberculosis cases within the cluster, the variable mycobacterial mutation rate in dormant and active states, and low M. tuberculosis genetic variability inferred precise transmission chain delineation. In some cases, heterozygous SNVs with an allelic frequency of 10–73% proved valuable in identifying direct transmission events.ConclusionThe complex approach of integrating tuberculosis cluster WGS-data-based median-joining networks with relevant epidemiological and clinical data proved valuable in delineating epidemiologically linked patient transmission chains and deciphering causes of recurrent tuberculosis episodes within clusters.

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Outbreak of tuberculosis in a closed setting: views on transmission based on results from molecular and conventional methods

Cited by 6 publications

References 16 publications

Disinfection efficacy of ultraviolet germicidal irradiation on airborne bacteria in ventilation ducts

Disinfection efficacy of ultraviolet germicidal irradiation on airborne bacteria in ventilation ducts

Methods for Detecting Mycobacterial Mixed Strain Infections–A Systematic Review

Unraveling tuberculosis patient cluster transmission chains: integrating WGS-based network with clinical and epidemiological insights

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