Genomic Investigation of a Mycobacterium tuberculosis Outbreak Involving Prison and Community Cases in Florida, United States

Séraphin, Marie Nancy; Didelot, Xavier; Nolan, David J.; May, Justin R.; Khan, Shafiqul Islam; Murray, Ellen R.; Salemi, Marco; Morris, J. Glenn; Lauzardo, Michael

doi:10.4269/ajtmh.17-0700

Cited by 17 publications

(12 citation statements)

References 32 publications

(58 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The branching process was defined by a number of offspring distribution (i.e., number of individuals one individual can infect) and a generation time distribution [40]. The Transphylo package was chosen to study (Table S4) bacterial transmission (such as M. tuberculosis [48][49][50] and K. pneumoniae outbreaks [51,52]), as well as viral transmission (e.g., part of the recent SARS-CoV-2 pandemic [53] and a large mumps outbreak in Canada [54]). Recently, the Transphylo package [40] was extended to infer transmission trees from multiple phylogenetic trees [55].…”

Section: Sequential Phylogenetic Familymentioning

confidence: 99%

“…None of these transmission tree reconstruction methods explicitly modeled sequence mutation since the method is applied to an already fully reconstructed phylogenetic tree (hence the "not applicable" in Table 3). However, some articles [39,40,48,51,[53][54][55] have used substitution models to reconstruct the phylogenetic tree prior to the implementation of their method.…”

Section: Sequential Phylogenetic Familymentioning

confidence: 99%

See 1 more Smart Citation

Methods Combining Genomic and Epidemiological Data in the Reconstruction of Transmission Trees: A Systematic Review

2022

View full text Add to dashboard Cite

In order to better understand transmission dynamics and appropriately target control and preventive measures, studies have aimed to identify who-infected-whom in actual outbreaks. Numerous reconstruction methods exist, each with their own assumptions, types of data, and inference strategy. Thus, selecting a method can be difficult. Following PRISMA guidelines, we systematically reviewed the literature for methods combing epidemiological and genomic data in transmission tree reconstruction. We identified 22 methods from the 41 selected articles. We defined three families according to how genomic data was handled: a non-phylogenetic family, a sequential phylogenetic family, and a simultaneous phylogenetic family. We discussed methods according to the data needed as well as the underlying sequence mutation, within-host evolution, transmission, and case observation. In the non-phylogenetic family consisting of eight methods, pairwise genetic distances were estimated. In the phylogenetic families, transmission trees were inferred from phylogenetic trees either simultaneously (nine methods) or sequentially (five methods). While a majority of methods (17/22) modeled the transmission process, few (8/22) took into account imperfect case detection. Within-host evolution was generally (7/8) modeled as a coalescent process. These practical and theoretical considerations were highlighted in order to help select the appropriate method for an outbreak.

show abstract

Section: Sequential Phylogenetic Familymentioning

confidence: 99%

Section: Sequential Phylogenetic Familymentioning

confidence: 99%

Methods Combining Genomic and Epidemiological Data in the Reconstruction of Transmission Trees: A Systematic Review

2022

View full text Add to dashboard Cite

show abstract

“…Previous studies have found that the excess risk of tuberculosis within prisons extends to surrounding communities (15,16) and that M. tuberculosis genotypes responsible for jail and prison outbreaks are also found in the surrounding communities. (13,15,17,18) Pathogen genomes can be powerfully harnessed to infer high-resolution transmission histories, including who-infected-whom. (19) However, studies have not yet combined M. tuberculosis genomic and epidemiologic data to reconstruct transmission linkages between potential institutional amplifiers and the community, nor have they estimated the fraction of community transmission attributable to such spillover.…”

Section: Introductionmentioning

confidence: 99%

“…[12,15,16] Further, spillover may occur when incarcerated people, prison staff, or visitors are infected within high-incidence prison environments and transmit M. tuberculosis onwards in communities outside prison. Previous studies have found that the excess risk of tuberculosis within prisons extends to surrounding communities [17,18] and that M. tuberculosis genotypes responsible for jail and prison outbreaks are also found in the surrounding communities [15,17,19,20]. Because transmission is rarely observed, however, it is often difficult to link community cases to transmission from prisons and previous studies have largely been associative.…”

Section: Introductionmentioning

confidence: 99%

The role of prisons in disseminating tuberculosis in Brazil: a genomic epidemiology study

Pcp

To³

et al. 2021

Preprint

View full text Add to dashboard Cite

Prisons are high-incidence settings for tuberculosis around the world, yet the contribution of spillover from prisons in driving community epidemics has not been quantified. We whole genome sequenced 1,152 M. tuberculosis isolates from participants diagnosed with tuberculosis within prisons and in the community in Mato Grosso do Sul, Brazil from 2014 to 2019. By integrating timed phylogenies and detailed location data, we reconstructed probabilistic transmission histories. M. tuberculosis sequences from incarcerated and non-incarcerated people were closely phylogenetically related. We found that 57% of recent community-wide tuberculosis cases were attributable to transmission from individuals with an incarceration history, 2.6% of the population. Further, we find genomic evidence that the prison system disseminates M. tuberculosis genotypes through frequent transfers across the state. This population-wide genomic transmission reconstruction framework can be applied to identify key environments amplifying infectious disease transmission to prioritize public health interventions.

show abstract

“…Recently WGS has been applied in the investigation of national outbreaks. In several investigations WGS was used to estimate the timing and directionality of transmission within clusters defined by spoligotyping and/or 24-loci MIRU-VNTR (13, 18–21); however, not always successfully (19, 20). In another investigation of an outbreak of extensively drug-resistant TB (XDR-TB) in London, the use of WGS confirmed the link between cases and guided early patient treatment (22).…”

Section: Introductionmentioning

confidence: 99%

Whole-Genome Sequencing as Tool for Investigating International Tuberculosis Outbreaks: A Systematic Review

Werf

Ködmön

2019

Front. Public Health

View full text Add to dashboard Cite

Background: Whole-genome sequencing (WGS) can support the investigation of tuberculosis (TB) outbreaks. The technique has been applied to estimate the timing and directionality of transmission and to exclude cases from an investigation. This review assesses how WGS was applied in international outbreak investigations and discusses the advantages and challenges of the application of WGS. Methods: Databases were searched for reports on international TB outbreak investigations. Information was extracted on: Why was WGS applied?; How was WGS applied?; Organizational issues; WGS methodology; What was learned/what were the implications of the WGS investigation?; and challenges and lessons learned. Results: Three studies reporting on international outbreak investigations were identified. Retrospective WGS sequencing was performed in all studies and prospective typing in two to study TB transmission. In one study, WGS data were produced centrally (i.e., in one laboratory) and analysis was done centrally. In two studies, WGS data production was done in a decentralized manner, and analysis was centralized in one laboratory. Three groups of professionals were involved in the international outbreak investigation: public health authorities, laboratory experts, and clinicians. The reported WGS methodology applied differed between the studies in some aspects, e.g., sequencing platform; quality measures, percentage of the reference genome covered, and the mean genomic coverage; analysis, use of a reference genome or de novo assembly; and software used for alignment and analysis. In all three studies, in-house scripts were used for variance calling, and the single nucleotide polymorphism (SNP) approach was used for analysis. All outbreak investigation reports stated that WGS refuted suspected transmission events and provided supporting evidence for epidemiological data. Several challenges were reported of which most were not related to WGS. The only challenge related to WGS was the timeframe of getting WGS data if WGS is not routinely performed. Conclusions: WGS was considered a useful addition in international TB outbreak investigations. Further standardization of the WGS methodology and good structures for international collaboration and coordination are needed to take full advantage of this new technology. Whether the use of WGS results in earlier detection of cases and thus limits transmission still needs to be determined.

show abstract

Genomic Investigation of a Mycobacterium tuberculosis Outbreak Involving Prison and Community Cases in Florida, United States

Cited by 17 publications

References 32 publications

Methods Combining Genomic and Epidemiological Data in the Reconstruction of Transmission Trees: A Systematic Review

Methods Combining Genomic and Epidemiological Data in the Reconstruction of Transmission Trees: A Systematic Review

The role of prisons in disseminating tuberculosis in Brazil: a genomic epidemiology study

Whole-Genome Sequencing as Tool for Investigating International Tuberculosis Outbreaks: A Systematic Review

Contact Info

Product

Resources

About